TL;DR

• Shift to Edge Automation: Data centers are moving away from inefficient, manually monitored Security Operations Centers (SOCs) toward automated, decentralized security located directly at the “edge” (the entrance of the data hall).
• Operational Efficiency: Implementing automated entry and screening lowers operational expenses (OpEx) by using AI to handle routine access, freeing up human staff for strategic oversight, and logging all events centrally for audit compliance.
• The Orion DataGuard™ Solution: To support this new “Lean SOC” model, Orion DataGuard™ offers a single modular unit that integrates AI/LiDAR tailgating prevention, biometric authentication, and digital-media detection to provide highly secure and frictionless access.

# # #

The traditional Security Operations Center (SOC) is under siege; not by threats, but by its own inefficiency. The 2026 SIA Security Megatrends explicitly notes that SOCs and monitoring will be disrupted and automated. For data center operators, this disruption is the key to unlocking massive ROI.

For years, physical security at data centers relied on a “manual triage” model: cameras and sensors fed data to an SOC, where security monitoring staff spent most of their time on repetitive tasks. In 2026, that model is turning obsolete. The goal now is the reduction or elimination of the SOC as we know it, moving security intelligence directly to the “edge”, the actual entrance of the data hall. This reflects a shift toward more decentralized, real-time security – positioned closer to the physical infrastructure.

Turning Security into a Value Chain

Data centers are moving away from security staff and implementing fewer SOC’s, towards remotely monitored/controlled automated security systems; especially for security entrance control, visitor management, and surveillance. By implementing self-service, automated security screening, data centers can finally bridge the gap between high security and low OpEx. This is where the ROI becomes undeniable.

Moving authentication and screening to an automated portal can:

• Eliminate Tier 1 Bottlenecks: AI handles the “noise” of daily access.
• Optimize Staffing: Shift human capital from “watching doors” to high-level strategic oversight.
• Ensure Compliance: Every event is centrally logged via AI based event management systems, such as Orion Infinity™ for audit-ready reporting.

Introducing Orion DataGuard™: The Modular Solution for 2026

At Orion Entrance Control, Inc., we’ve listened to the pressure data center developers face; balancing many conflicting priorities like real estate and energy costs with the absolute need for data center server security. Orion DataGuard™ is our answer.

DataGuard™ integrates AI/LiDAR-based tailgating prevention through Orion DoorGuard™, identity and biometric authentication, digital-media detection and secure asset management into a single modular unit. It is a highly secure, ADA-accessible screening environment that satisfies stringent AHJ fire codes while providing a frictionless experience. Whether for new builds or retrofits, DataGuard™ enables a “Lean SOC” model by automating all the processes involved in providing secure entry. By partnering with best-of-breed technology providers, Orion ensures that DataGuard™ fits into your existing tech stack while preparing you for a future where security is automated, autonomous, and incredibly efficient.

# # #

About the Author

Mike McGovern, VP Data Center Security at Orion Entrance Control, Inc.

For over 26 years Mike has helped develop, design and integrate pedestrian entrance control systems (security revolving doors, turnstiles, speed gates, security portals) working with end users, architects, integrators and security engineer consultants. His portfolio includes architectural optical turnstile, revolving door, and portals systems at many of the USA’s most iconic and recognizable buildings and campuses. He is a frequent speaker and panel moderator on integrated security and data center security topics at leading data center trade shows and seminars. McGovern is an active member of the ASIS SAEC (Security Architecture and Engineering Community) Steering Committee and the SIA (Security Industry Association) Data Center Advisory Panel. As VP Business Development at Orion Entrance Control, Inc., he leads their data center security entrance control business and product development strategy.

About Orion Entrance Control, Inc.

Orion Entrance Control, Inc. is an American technology company that specializes in speed lanes, optical turnstiles, full height turnstiles, security tailgating solutions, and occupancy sensor solutions. Serving high-rise buildings, government and corporate offices, and other facilities, Orion delivers secure, visually appealing, and easily integrated entry solutions. With decades of experience working with security integrators and architectural planners, Orion provides the expertise and tools to streamline lobby security projects while delivering actionable data and metrics that enhance operational efficiency and safety. For more information, please visit www.orioneci.com or follow us on LinkedIn.

The post Data Center Security Enhanced with DataGuard™: The Disruption and Automation of Security Operations Centers (SOCs) appeared first on Data Center POST.

TL;DR

• Massive Market Growth: The global data center refrigerant market is projected to reach $1.62 billion by 2035 (up from $633 million in 2025), driven by the rapid expansion of artificial intelligence, cloud platforms, and high-density computing.
• Shift to Sustainable Solutions: Regulatory pressures and sustainability goals are forcing a transition to low-emission alternatives, with Hydrofluoroolefins (HFOs) capturing a dominant 67.7% market share in 2025 due to their low global warming potential and high cooling efficiency.
• U.S. Market Leadership: The United States accounted for a massive 79% of the market in 2025, heavily supported by continuous investments in hyperscale expansions and strict energy efficiency mandates.

# # #

The global data center refrigerant market was valued at USD 633 million in 2025 and is estimated to grow at a CAGR of 9.6% to reach USD 1.62 billion by 2035, according to recent report by Global Market Insights Inc.

The market is undergoing a major transformation driven by the rapid expansion of digital infrastructure, including hyperscale facilities, cloud platforms, and accelerating global data consumption. Increasing computational workloads from artificial intelligence, big data analytics, and high-density computing environments are significantly raising thermal management requirements across modern data centers. As a result, demand for advanced refrigerants that ensure efficient heat control, operational stability, and optimized energy performance is increasing steadily.

The industry is also experiencing a structural shift away from traditional high-global-warming-potential refrigerants toward low-emission and energy-efficient alternatives. Regulatory pressure from global climate agreements and regional environmental policies is accelerating the adoption of next-generation refrigerants. Operators are increasingly focusing on reducing emissions, improving leakage control, and enhancing lifecycle management practices to comply with evolving sustainability requirements. This transition is further reinforced by rising emphasis on lowering operating costs and improving energy efficiency across large-scale digital infrastructure.

The data center refrigerant market from HFOs segment held a 67.7% share in 2025 and is projected to grow at a CAGR of 10.2% through 2035. HFO refrigerants continue to dominate due to tightening environmental regulations and the global push toward decarbonization. Their significantly lower global warming potential, combined with strong cooling efficiency, makes them a preferred solution for next-generation data center cooling systems. The ongoing phase-out of high-GWP refrigerants is further accelerating their adoption across the industry.

The hyperscale segment accounted for 40% share in 2025 and is expected to grow at a CAGR of 10.4% from 2026 to 2035. This segment leads the market due to extremely high computing densities and large-scale infrastructure operated by major cloud and technology providers. These facilities generate substantial heat loads from artificial intelligence workloads, cloud computing, and advanced digital services, requiring highly efficient refrigerant-based cooling systems to maintain continuous operations and system stability.

U.S. data center refrigerant market held a 79% share in 2025, generating USD 176.3 million. Growth in the country is strongly supported by rapid hyperscale data center expansion driven by artificial intelligence, cloud computing, and data-intensive applications. Continuous investments in new facilities by leading technology firms are increasing demand for advanced cooling systems. Rising adoption of high-density server infrastructure is further intensifying thermal loads, strengthening the need for high-performance refrigerants. In addition, strict energy efficiency regulations and sustainability mandates are encouraging the shift toward low-GWP refrigerant solutions and modern thermal management technologies.

Key companies operating in the global data center refrigerant industry include Daikin Industries, Linde plc, Honeywell, Chemours, AGC, Dongyue, Zhejiang Juhua, Arkea and Sinochem. Companies in the market are actively focusing on developing low-global warming potential refrigerants that align with tightening environmental regulations and sustainability targets.

A major strategy involves increasing investment in research and development to enhance refrigerant efficiency, thermal stability, and compatibility with high-density computing environments. Market players are also strengthening partnerships with data center operators and cooling system manufacturers to integrate advanced refrigerant solutions into next-generation infrastructure. Expansion of production capabilities in high-demand regions is being prioritized to ensure supply chain stability and faster delivery. Additionally, firms are emphasizing compliance-driven innovation, improving leakage detection systems, and enhancing lifecycle management solutions.

The post Data Center Refrigerant Market to Surpass USD 1.62 Billion by 2035 appeared first on Data Center POST.

TL;DR

• The Hyperscale Mismatch: Large wholesale data centers in Miami cater to massive enterprise volumes, forcing small and medium-sized businesses (SMBs) into expensive minimum commitments that far exceed their actual requirements.
• The Cost of Unused Capacity: Under these enterprise models, SMBs end up paying for stranded power and empty rack space, making professional colocation financially unviable and leaving them vulnerable to risks like housing critical systems in office server closets during hurricane season.
• Fractional Colocation Solutions: Instead of accepting preset sales minimums, businesses can utilize right-sized options like quarter-rack (10U) or half-rack (20U) setups, which provide the same enterprise-grade facility standards but scale power and space commitments to exact hardware loads.
• Accessible Resilience: Local, right-sized colocation allows South Florida businesses to affordably access vital infrastructure, such as robust hurricane resilience, physical security, and low-latency connectivity, while preserving the flexibility to scale up seamlessly as demand grows.

# # #

The South Florida business landscape is booming, cementing its status as a critical gateway for national and international commerce.

As a growing business or enterprise IT leader in this region, migrating your core infrastructure to a Miami data center can solve on-premises space limitations, remove cooling headaches, and provide real physical security against extreme weather events. But when evaluating local options, smaller businesses quickly hit a commercial wall with the industry’s massive wholesale giants.

Search for Miami colocation today, and the biggest names dominate the results: global hyperscale and wholesale providers with massive campuses, enterprise sales teams, and pricing models built for customers leasing entire cages and data halls. What those results don’t show is the fine print that matters most to a small or medium-sized business: the minimum commitment.

For a South Florida business that needs to house a handful of servers, a storage appliance, and a firewall, that floor can make professional colocation an impossible infrastructure decision because of the budget problem. The business ends up paying for empty cabinet space and stranded power capacity, or it walks away from colocation entirely and accepts the risk of an office server closet during hurricane season.

This guide explains why hyperscale minimums fail smaller deployments, what a right-sized data center engagement looks like with quarter-rack, half-rack, and full-rack options, and why power should be provisioned to your actual requirements rather than the maximum a cabinet can support.

The Enterprise-Focused Structure of the Miami Colocation Market

Miami is one of the most strategically important data center markets in the Western Hemisphere. It is the primary connectivity gateway between North America, Latin America, and the Caribbean, home to dense subsea cable landings and carrier ecosystems that route an enormous share of intercontinental traffic. That strategic value has attracted the largest global colocation operators, and their presence shapes how Miami colocation is sold.

Hyperscale and wholesale providers optimize for volume. Their ideal customer leases hundreds of kilowatts across cages and suites, signs multi-year enterprise agreements, and consumes interconnection services at scale. Everything about their operation, from sales process to contract structure, reflects that buyer. The smallest unit they are willing to sell is set accordingly: one full cabinet, a 5 kW committed power floor, and terms designed for enterprise procurement.

None of that is wrong as a business strategy, it just means that the most visible Miami data center options are built around enterprise buyers, without consideration for smaller businesses that make up a significant part of the South Florida market.

What Large Provider Minimums Mean for Small Businesses

At the largest Miami colocation providers, retail colocation often starts at one full rack paired with a 5 kW minimum power commitment. For a multinational enterprise, that may be a small line item. For an SMB, it can define the entire economics of the deal.

Consider a typical small business deployment: 8 to 12 rack units of equipment drawing 1 to 2 kW under normal load. Under a hyperscale minimum, that business may pay for:

• A 42U or 45U cabinet where most of the space sits empty
• 5 kW of committed power when actual draw peaks closer to 2 kW
• Cross-connect fees, remote hands rates, and setup charges scaled to enterprise budgets
• Multi-year terms with escalators built around enterprise renewal cycles

Power is usually where the mismatch hurts most: if a business draws 1.8 kW but commits to 5 kW, the unused 3.2 kW still shows up on the bill every month, and over a multi-year term, that stranded capacity can become a serious cost. It can seriously raise the bill, and push smaller businesses into awkward infrastructure choices, from delaying hardware refreshes to keeping critical systems in office server rooms or moving steady workloads into cloud environments that may cost more over time.

What Right-Sized Data Center Colocation Looks Like

Right-sized Miami data center colocation starts with the actual deployment, not a preset sales minimum. The amount of space and power should reflect what the business is really putting in the rack.

Smaller environments may only need a quarter rack or half rack, while larger or denser deployments may require a full rack with a higher committed power level. The footprint follows the equipment, not the other way around.

Power should follow the same logic as space, with the commitment based on the actual hardware load rather than the maximum theoretical capacity of the rack. A deployment drawing 1.5 kW should be provisioned differently from a high-density setup that needs 8 kW. The hardware profile sets the number, with enough headroom to grow without overbuying from day one.

Half-Rack and Quarter-Rack Miami Colocation Options Exist for Small Businesses

Many SMBs don’t realize these options exist because many Miami colocation options are marketed around full racks and enterprise deployments. In reality, though, smaller footprints like quarter racks and half racks can be a much better fit for businesses that only need a modest amount of equipment.

A quarter rack provides roughly 10U of secure, individually lockable space, which is often enough for a basic production environment with a few servers, storage, a firewall, and a switch. The smaller footprint doesn’t mean a lower facility standard. Quarter rack deployments can still use core data center infrastructure like redundant power paths, N+1 cooling, physical security, fire suppression, and 24/7 monitoring.

A half rack, around 20U, gives growing businesses more room for virtualization clusters, shared storage, network equipment, and backup infrastructure. It is also useful for companies consolidating servers from multiple offices or closets into one professional environment. In both cases, power should scale to the deployment itself: a half rack drawing 2.5 kW commits to 2.5 kW, not an arbitrary floor.

Scaling From Quarter Rack to Full Rack Without Overcommitting

Businesses that genuinely need a full cabinet still benefit from the right-sizing principle. The goal is not to stay small, but to match the deployment to current requirements.

Because the model is fractional by design, scaling is built in. A company can start in a quarter rack, move into a half rack, and later expand to a full rack within the same facility. That kind of path helps avoid buying more space and power than the business is ready to use.

Why Location Is Still Part of the Equation

Right-sizing addresses the economics. Location addresses operations. For businesses across Miami-Dade, Broward, and Palm Beach counties, local colocation can offer advantages that are difficult to replicate from another market.

For South Florida businesses, hurricane resilience is often the biggest driver behind moving infrastructure out of an office server room and into a professional facility. Proximity makes everyday operations easier, too. When hardware needs to be installed, replaced, or physically inspected, engineers can drive to the facility instead of coordinating logistics across the country. Miami’s position as a connectivity hub also benefits organizations serving Latin America and the Caribbean, serving a core need: lower latency.

The Bottom Line: Miami Colocation Should Fit Your Business

Miami colocation doesn’t have to start with a full rack, an excessive power commitment, or more infrastructure than the business currently needs. The better approach is to look at the actual hardware first, then choose the footprint and power profile that fits it. That sounds obvious, but it’s often missing from the way colocation is sold. In many cases, the better fit already exists; businesses simply have to know where to look.

# # #

About the Author

Michael Zrihen is the Senior Director of Marketing & Internal Operations Manager at Volico Data Centers

The post Why Hyperscale Data Center Pricing Fails Small Businesses Seeking Miami Colocation appeared first on Data Center POST.

TL;DR

• AI Workloads Overwhelming Traditional Cooling: AI’s demand for concentrated compute power is driving rack densities from 5-10 kW to beyond 50-100 kW, creating extreme heat that traditional, water-intensive air cooling systems can no longer handle.
• Infrastructure Must Evolve: Thermal management, power delivery, and resource efficiency are now co-dependent, requiring developers to treat data center infrastructure as an integrated system rather than sacrificing sustainability for performance.
• The Immersion Cooling Advantage: Fully submerging IT components in thermally conductive fluid provides superior, uniform heat removal, enabling higher rack densities while significantly lowering both water and energy consumption compared to traditional methods.
• Fluid Selection is the Linchpin: The ultimate success and sustainability of immersion cooling rely on selecting the right engineered fluids, which dictate heat transfer efficiency, hardware lifespan, and overall environmental impact.

# # #

The Current State of Data Center Cooling

In 2026, data centers are caught between surging demand and tightening constraints. AI workloads are driving the need for higher compute density, while developers face limits related to power availability, water usage, and permitting timelines. Policymakers and communities are scrutinizing new projects, slowing approvals due to various concerns ranging from grid strain to land and water use. Meanwhile, hyperscalers and enterprise operators must meet aggressive sustainability targets even as their infrastructure footprints expand.

These pressures are exposing fundamental structural challenges in how data centers are built. Traditional air cooling with water-intensive systems cannot scale to meet AI’s mounting demands. Developers must now tackle multiple variables at once: more compute per square foot, lower energy and water intensity, and alignment with evolving regulatory frameworks. Meeting these challenges requires rethinking infrastructure as an integrated system where performance, efficiency, and sustainability are engineered together, not sacrificed for each other.

AI as the Catalyst for Convergence

Artificial intelligence has fundamentally changed infrastructure development strategies. Unlike traditional workloads, AI training and inference require highly concentrated compute power, delivered through GPUs and accelerators operating at significantly higher thermal design power (TDP). Rack densities that once averaged 5–10 kW are now pushing beyond 50–100 kW, with next-generation deployments expected to drive densities even higher.

The implications for power infrastructure are already appearing. According to Dean Nelson, founder and chairman of Infrastructure Masons, the industry is building as much data center capacity in the next three years as was built in the past thirty. The infrastructure required to support that pace of growth must align with these operational realities. After all, the cascading effects are significant. Higher compute density drives more heat, which demands more cooling. Cooling systems consume more power and, in many cases, more water, putting compounding pressure on resources already under strain. Power availability is becoming a gating factor, with utilities struggling to keep pace with the speed and scale of data center growth.

As a result, AI performance is determined by the infrastructure that supports it, not just by model architecture or silicon. Thermal management, power delivery, and resource efficiency are now co-dependent variables. As such, decisions from the chip to the facility cooling plant must be evaluated through a single, system-wide lens that takes these factors into account.

Immersion Cooling as an Infrastructure Strategy

Cooling is now a critical lever for enhancing performance and efficiency. As TDPs rise across the technology stack, liquid cooling is becoming a requirement at leading AI facilities. Immersion cooling, in particular, is uniquely positioned to address the three constraints underpinning modern data center development: heat management, water use, and power consumption.

Compared to traditional air cooling and direct-to-chip liquid cooling, immersion cooling delivers significant improvements in thermal management efficiency. By fully submerging IT components in a thermally conductive fluid, heat is removed directly and uniformly at the source, eliminating the limitations of air cooling and the complexity of localized cold plates and plumbing. Direct-to-chip cooling targets high-heat components like GPUs and CPUs but still relies on air or secondary systems to cool the rest of the hardware. Immersion cooling, by contrast, manages the entire system within a single thermal environment.

The Operational Benefits of Immersion Cooling

The superior heat capacity and thermal conductivity of immersion fluids enable consistent, high-efficiency heat transfer across all components, even at extreme power densities. This helps data centers support significantly higher rack densities without complex airflow management, extensive piping networks, or oversized mechanical cooling systems. Benefits such as better performance, longer hardware lifespan, and greater operational reliability are proving critical for high-density AI workloads.

Immersion cooling also reduces reliance on air handling and evaporative systems, significantly lowering water consumption. It mitigates overall energy demand for cooling as well, easing pressure on constrained power infrastructure. The net effect is not only thermal efficiency, but a more balanced and sustainable resource profile that regulators, investors, and communities increasingly prioritize.

Fluid Selection: The Linchpin of Data Center Infrastructure Sustainability

However, realizing these benefits depends on fluid selection. Fluid qualities like thermal stability, heat transfer efficiency, material compatibility, and environmental profile all determine system performance and lifecycle outcomes. The right fluid enhances heat transfer, extends system longevity, and reduces maintenance requirements. It also shapes sustainability metrics, from lifecycle emissions to end-of-life handling.

As the demands of AI workloads intensify, these decisions carry increasing weight. Now, when selecting a cooling technology, data center developers are making long-term infrastructure commitments that will determine performance, scalability, and environmental impact for years to come. Immersion cooling, when paired with thoughtfully engineered fluids and integrated system architectures, can help developers align all three qualities to improve operational efficiency while addressing common challenges.

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About Robert Schuetzle

Robert Schuetzle is President and CEO of Infinium, a technology company transforming how the world powers, moves, and computes. Backed by strategic investors including Amazon, MHI, NextEra Energy, and AP Ventures, Infinium is best known for its leadership in ultra-low carbon electrofuels and is now expanding that expertise into digital infrastructure through Infinium Edge™, its platform focused on energy efficiency and thermal management for power- and heat-intensive systems such as data centres.

The post Fueling Performance at the Edge: Why Cooling, Power, and Sustainability Are Intertwined in the AI Data Center Era appeared first on Data Center POST.

TL;DR

• A Labor Agreement Built Around People: Quantica Infrastructure and the Southeastern Montana Building and Construction Trades Council have signed a Memorandum of Understanding (MOU) to guide union construction for the Big Sky Campus, a large-scale data center and energy project.
• Workforce Development as a Core Commitment: The agreement establishes a framework focused on apprenticeship opportunities, training pathways, workforce development, and qualified local labor.
• Long-Term Benefits for Montana: The partnership is designed to support job creation, career development, and economic activity while helping deliver critical infrastructure for the state’s future.

# # #

As discussions around data centers often focus on power, technology, and infrastructure, one critical component can sometimes get overlooked: the people who build them.

For the Big Sky Campus, Quantica Infrastructure, LLC (“Quantica”) and the Southeastern Montana Building and Construction Trades Council (SEMTBCTC) are working to make workforce development part of the project from the beginning.

The two organizations recently announced a labor Memorandum of Understanding (MOU) that will help guide construction of the Big Sky Campus, a large-scale data center and energy project being developed by Big Sky Digital Infrastructure (BSDI), a Quantica company.

The agreement establishes a cooperative framework focused on workforce development, apprenticeship and training pathways, project stability, and qualified local labor. It also creates opportunities to expand participation in the skilled trades while supporting construction of the infrastructure needed to power the next generation of digital growth.

For Montana’s construction workforce, that means more than jobs on a single project. It means opportunities for training, career development, and long-term participation in an industry that continues to grow across the country.

“The Big Sky Campus represents a significant opportunity for Montana’s skilled trades workforce,” said Clint A. McCulloch, President of SEMTBCTC and Business Manager of UA Plumbers and Pipefitters Local Union 30. “We are pleased to work alongside Quantica to help create family-supporting careers, expand apprenticeship opportunities, and ensure Montana workers have a role in building the infrastructure that will support the state’s future economy.”

The partnership also reflects a broader goal shared by both organizations: ensuring that major infrastructure investment creates lasting local benefits.

Through apprenticeship programs, training opportunities, and a focus on qualified local labor, the agreement is intended to help build a highly skilled workforce while creating pathways into the construction trades for future generations of Montana workers.

“Major infrastructure projects like the Big Sky Campus have the potential to deliver meaningful economic benefits when they prioritize skilled labor and long-term workforce development,” said Riley McCauley, Vice President of SEMTBCTC and Representative of Western States Regional Council of Carpenters. “We see a real opportunity to support a strong, skilled workforce in Montana by partnering with Quantica on apprenticeship programs, training pipelines, and local hiring efforts, helping create durable career pathways while supporting responsible infrastructure development in the region.”

For Quantica, the agreement aligns with the company’s vision for how large-scale infrastructure projects should be developed.

“Our vision for the Big Sky Campus extends beyond digital infrastructure,” said John Chesser, Chief Executive Officer of Quantica. “We are committed to creating high-quality jobs, supporting workforce development, and building lasting opportunities for Montanans. This agreement reflects our belief that strong partnerships with Montana workers can help deliver world-class infrastructure safely, efficiently, and with meaningful benefits for our communities.”

The Big Sky Campus is expected to bring substantial investment, long-term employment, and economic activity to the region. BSDI has also emphasized its commitment to funding the new generation and infrastructure required for the campus without increasing electricity costs for Montana ratepayers.

As development moves forward, the agreement provides a framework for ensuring that the benefits of the project extend beyond the infrastructure itself and into the workforce, businesses, and communities that will help build it.

The post Union Partnership Powers the Big Sky Campus: Quantica and Montana Trades Council Forge Labor Framework appeared first on Data Center POST.

Originally posted on Mod42.

TL;DR

• Modular is a manufacturing methodology, not a shipping container.
• Mod42 manufactures complete data center buildings off-site using volumetric modular construction.
• Factory-built modules enable parallel construction, reducing deployment timelines by up to 50%.
• Purpose-built modular facilities deliver the same performance, quality, and serviceability as traditional data centers.
• The modular approach provides greater flexibility to adapt to evolving AI workloads, cooling technologies, and power requirements.
• Mod42 helps organizations deploy AI infrastructure faster while maintaining long-term scalability and future readiness.

# # #

A common misconception in the digital infrastructure industry is equating modular data centers with shipping containers filled with servers. In reality, modular construction is a manufacturing methodology that shifts work into a controlled factory environment to reduce risk and accelerate schedules. Moving beyond simple containerized solutions, Mod42 utilizes volumetric modular construction to manufacture entire building sections off-site. These purpose-built modules incorporate the exact same structural, electrical, mechanical, and cooling systems found in traditional facilities, resulting in a fully operational, enterprise-grade data center rather than a temporary deployment.

The rapid deployment speed of this methodology comes from parallel manufacturing rather than the physical shape of a container. While site preparations, foundations, and utilities are being completed on location, the actual data center is built simultaneously in the factory. By overlapping these critical phases instead of executing them sequentially, organizations can bypass traditional construction bottlenecks and bring complete, factory-built AI capacity online in under seven months.

Beyond speed, this volumetric approach provides the critical adaptability required by rapidly evolving artificial intelligence workloads. Because these facilities are engineered as actual buildings rather than restricted transportation packages, they offer the necessary flexibility to accommodate soaring rack densities, changing cooling strategies, and future hardware upgrades. This ensures that operators can efficiently scale their operations, easily add modules as demand grows, and future-proof their long-term infrastructure investments.

To continue reading, please click here.

The post A Modular Data Center Is Not a Container: Why Mod42 Manufactures Complete AI Data Centers appeared first on Data Center POST.

TL;DR

• Tournament proceeds will fund workforce development initiatives focused on digital infrastructure education and career access.
• Supported programs include scholarships, mentorship, internships, educational tours, conference participation, and industry engagement.
• The event aims to unite executives, investors, and technology leaders around a shared commitment to developing future industry talent.
• Sponsorship opportunities enable organizations to support educational initiatives while participating in a high-level networking experience.

# # #

As the digital infrastructure industry continues to expand to support AI, cloud, and connectivity demands, workforce development remains a critical priority. To help address this need, the Nomad Futurist Foundation has announced the inaugural Nomad Ho’ohui Invitational, an invitation-only charity golf tournament that will take place January 15-16, 2027, on Oahu, Hawaii, immediately preceding PTC’27.

Hosted at the Kapolei Golf Club, the two-day Ryder Cup-style competition is designed to bring together executives, investors, technology leaders, and innovators from across the digital infrastructure ecosystem. Beyond the competition itself, the event will feature networking receptions, a gala dinner, and opportunities for industry participants to build relationships while supporting a larger philanthropic mission.

Unlike many industry gatherings that focus primarily on business development, the Nomad Ho’ohui Invitational is centered on investing in the future workforce. Proceeds from the event will directly benefit the Nomad Futurist Foundation’s initiatives to increase awareness of careers in digital infrastructure and provide students with meaningful educational and professional opportunities. Funding will support scholarships, educational resources, data center tours, mentorship programs, internships, conference participation, and direct engagement with industry professionals.

The name “Hoʻohui,” a Hawaiian term meaning to join, unite, or connect, reflects the event’s broader purpose of bringing together the industry to create lasting impact. By aligning with PTC’27, one of the sector’s premier annual gatherings, the Invitational provides participants with an opportunity to strengthen professional relationships while contributing to programs that help prepare the next generation of talent.

Industry leaders have emphasized that the future of digital infrastructure depends not only on continued investment in technology, but also on sustained investment in people. As AI infrastructure, cloud computing, telecommunications, and data center development accelerate worldwide, organizations increasingly recognize that cultivating skilled professionals will be essential to supporting long-term growth and innovation.

The Nomad Futurist Foundation is inviting organizations to participate as founding partners through sponsorship opportunities that include player participation, event branding, guest access, and advisory committee involvement. Every contribution supports programs intended to expand career pathways and increase access for students and underserved communities interested in pursuing opportunities within digital infrastructure.

As the industry prepares to gather in Hawaii for PTC’27, the Nomad Ho’ohui Invitational offers a unique opportunity to combine networking, collaboration, and philanthropy in support of workforce development. By investing in education, mentorship, and career access today, participants can help strengthen the talent pipeline that will power tomorrow’s digital economy. To learn more about the Nomad Ho’ohui Invitational, please click here.

The post Nomad Ho’ohui Invitational Combines Industry Collaboration and Workforce Development Ahead of PTC’27 appeared first on Data Center POST.

TL;DR

• From Policy to Infrastructure: AI governance is no longer just a high-level policy issue; because AI is increasingly embedded directly into operational platforms and automation pathways, it must be managed as a core infrastructure strategy.
• Visibility Precedes Governance: AI capabilities are quietly accumulating within everyday SaaS apps and monitoring tools, meaning organizations must first establish a clear inventory of where AI exists, what data it processes, and what decisions it influences to prevent systems from gaining unchecked operational authority.
• Transparency as a Competitive Edge: With customers increasingly demanding to know how AI interacts with their environments and data, service providers that proactively communicate their governance frameworks, vendor controls, and safeguards will differentiate themselves as trusted operational partners.

# # #

For many organizations, AI governance still sounds like a policy discussion. In reality, it is rapidly becoming an infrastructure discussion.

AI systems are increasingly embedded into the platforms organizations use to manage infrastructure, monitor environments, automate workflows, support users, and analyze operational data. In some cases, AI systems directly influence operational changes across environments. As adoption accelerates, organizations are facing a new challenge: governing the AI models themselves, and also the infrastructure access, automation pathways, and operational influence those systems inherit inside the environment.

For MSPs and SMBs, this shift carries significant implications. AI capabilities are quietly appearing inside monitoring systems, endpoint operations, automation engines, service management platforms, and collaboration tools. In many environments, organizations may already be relying on AI-assisted capabilities without formally recognizing them as AI systems.

Visibility Must Come Before Governance

One of the biggest AI governance mistakes organizations can make is assuming AI systems are easy to identify. AI is increasingly embedded across SaaS applications and operational tooling in ways that may bypass centralized oversight. A workflow platform introduces automatic AI-assisted script creation, a monitoring tool adds AI-generated recommendations, or a collaboration platform that begins summarizing operational data automatically. In each case, the AI recommendation itself acts as an anchor: the first number, option or plan presented becomes the reference point around which human judgement is adjusted. Over time, organizations accumulate a growing number of AI-enabled capabilities without a centralized understanding of what systems exist, what they can access, or what operational decisions they can influence.

The first step toward effective governance is visibility. Organizations need a clear operational inventory of where AI exists across the environment, what infrastructure it connects to, what data it processes, what decisions it influences, and what level of operational authority it possesses. Without centralized tracking and accountability, businesses risk creating environments where AI systems quietly gain operational influence without sufficient oversight.

AI Is Changing the Meaning of Change Management

Traditional change management processes were designed around human-driven activity. AI introduces a more dynamic operating model, where systems can generate recommendations, accelerate workflows, and potentially influence operational decisions at machine speed. Even when humans remain involved, the pace and scale of operational activity can change dramatically.

Organizations should begin treating AI-enabled systems with the same operational discipline they apply to automation platforms and critical infrastructure tooling. That includes understanding whether AI systems can modify infrastructure directly, trigger automation workflows, or influence operational decisions without clear approval boundaries. It also means ensuring rollback mechanisms exist, maintaining strong audit logging, and validating whether human oversight remains in place before operational changes occur.

The operational failures associated with AI may not resemble traditional outages. In many cases, organizations are more likely to encounter subtle configuration drift, unintended automation behavior, or operational decisions made from incomplete context. These issues can spread quietly across environments before teams fully understand what changed or why.

Transparency Is Becoming a Competitive Requirement

Organizations are also facing growing pressure from customers who increasingly want transparency into how AI systems interact with their environments and data. Customers want to understand whether AI systems process operational information, whether external vendors are involved, whether customer data contributes to model training, and what safeguards exist if systems behave unexpectedly.

For MSPs and service providers, this creates both risk and opportunity. Organizations that proactively communicate governance practices, including oversight models, logging standards, vendor controls, and data handling policies, will increasingly differentiate themselves as trusted operational partners rather than reactive adopters of emerging technology.

Operational Maturity Will Define AI Governance Success

The organizations making the most progress today are not necessarily the ones building the most complex governance frameworks. They are the ones building practical governance models grounded in operational reality. The goal is to establish enough visibility, accountability, and operational control to scale AI safely while maintaining resilience and customer trust.

Organizations that move early on operational AI governance will be better positioned to scale automation safely, respond to customer concerns confidently, and adapt as regulatory expectations continue evolving.

Ultimately, AI governance is also a conversation about infrastructure access, operational influence, automation boundaries, and accountability. As AI systems become more deeply integrated into operational environments, governance will increasingly determine whether organizations can scale AI safely and confidently over the long term. That makes AI governance more than a compliance issue – it should be a core infrastructure strategy.

# # #

About the Author

Nicole Reineke is a technology executive and AI strategist currently serving as a Distinguished Product Manager and Director of AI Strategy at N-able. She previously served as Senior Vice President of Innovation at Iron Mountain and Senior Distinguished Engineer at Dell Technologies, and brings more than 25 years of experience leading high-tech ventures and driving enterprise innovation. In addition to holding dozens of granted patents, she teaches AI and innovation at Georgetown University and co-authors publications focused on breakthrough success and applied AI strategy.

The post Why AI Governance Must Become an Infrastructure Strategy appeared first on Data Center POST.

TL;DR

• The Rise of Bare Metal: Bare metal is now the dominant model for renting GPU clusters, sitting directly between traditional colocation and public cloud by allowing customers to rent entire, provider-owned servers without an intervening virtualization layer.
• A Distinct New Asset Class: GPUs have separated from data center real estate to become a standalone asset class because they possess all four necessary traits: identifiable assets, observable pricing, active resale markets, and lenders willing to accept them as collateral.
• The Portability Advantage: Unlike traditional real estate, GPU servers are portable and serial-numbered, meaning lenders can physically repossess and re-market the hardware in the event of a loan default.

# # #

Bare metal has become the dominant way GPU clusters are rented. The customer’s software runs directly on the hardware, with no hypervisor, no virtualization layer, and no managed services in between.

Since 2023, it has pulled the server into a separate asset class of its own from Data Centers. GPU clusters are financed in the capital markets, where it is now priced, traded, and borrowed against.

Where bare metal sits between colocation and cloud

Bare metal sits between the two models the industry already knows. Colocation has the tenant owning the servers and renting space, power, and cooling. Public cloud has the provider owning everything and selling virtual slices with managed services on top.

Bare metal is in the middle. The provider owns the servers, and the customer rents them whole, by the hour or on multi-year contracts. Neoclouds such as CoreWeave, Lambda, and Crusoe, cloud providers built specifically around GPU capacity, run their entire business on this model.

And now, traditional colocation operators are looking to do it too. They’re adding bare metal and GPU-as-a-service lines to capture the same demand, taking on hardware ownership their business model never required before.

The hardware became an asset class

An asset class needs four things: identifiable assets, observable pricing, a resale market, and lenders willing to take the asset as collateral. GPU servers now have all four.

The GPU can leave the building. When a data center loan defaults, the lender ends up owning real estate in one location. But when a GPU loan defaults, the lender holds serial-numbered servers that can be repossessed and re-marketed. That portability is what allows the hardware to be financed separately from the building it sits in.

In March 2026, CoreWeave closed an $8.5 billion facility rated A3 by Moody’s, the first investment-grade rating ever assigned to GPU-backed debt, supported in part by Meta contracts worth at least $19 billion.

The pricing of that debt tells the story faster than the headlines. CoreWeave’s earliest GPU-backed borrowing reportedly priced in the low teens. The floating-rate portion of the March 2026 facility priced at 2.25 percentage points over SOFR, the overnight benchmark rate. Lenders re-rated the asset from exotic to ordinary in under three years.

The data center industry spent three decades learning to finance buildings. Now, racks inside carry capital markets of their own.

# # #

About the Author

Bernie Margulies is the founder and CEO of American Compute, which helps GPU buyers get access to better GPU financing, and structures residual value insurance for lenders/lessors.

The post The New GPU Asset Class appeared first on Data Center POST.

TL;DR

• Grain Management announced plans to combine Ritter Communications and Great Plains Communications under a new organization and brand, Rightfiber.
• The combined company will serve more than 400 communities across 20 states with a 28,000-mile fiber network connecting 300,000 homes and businesses.
• Rightfiber aims to pair expanded scale and investment capacity with the local service, community focus, and customer relationships that have defined both organizations.

# # #

The broadband industry is often described in terms of speed, scale, and coverage. But the reason this deal matters now is simpler: Communities, businesses, and service providers all need reliable fiber networks that can grow with demand, not just keep up with it.

That is the context behind Grain Management’s announced combination of Ritter Communications and Great Plains Communications into a new organization called Rightfiber. The move brings together two established regional providers with long operating histories and a shared focus on fiber infrastructure, customer service, and community investment.

Two Companies, One Direction

Ritter Communications and Great Plains Communications each built their reputations in different parts of the country, but their business philosophies are closely aligned. Both companies have spent decades expanding fiber access, serving local markets, and investing in the kind of infrastructure that supports everyday life as well as business growth.

According to the announcement, the new company will be led by Heath Simpson as CEO, with Todd Foje serving as Executive Chairman. The leadership structure brings together executives from both organizations as the combined company moves forward under the Rightfiber brand.

What Rightfiber Brings

The new organization will serve more than 400 communities across 20 states and connect 300,000 homes and businesses through a 28,000-mile regional fiber network. Those numbers matter because they show how much the company’s footprint expands with this combination.

But the story is not just about size. It is also about what scale can make possible. Rightfiber is expected to have more resources to support network expansion, continued investment, and growth through both organic buildout and acquisitions. For customers, the promise is that local service and personalized support remain part of the model even as the company gets bigger.

Why Local Still Matters

In telecom, bigger can sometimes feel distant. This announcement makes a point of saying the opposite: The combined company will continue to operate with a strong local focus, preserve customer relationships, and keep investing in the communities it serves.

That matters because fiber is not just a technical upgrade. It is the backbone for remote work, education, health care, business operations, and the digital tools people now expect to use every day. A stronger network can change what is possible for a town, a business district, or a region that needs better connectivity to compete.

The Takeaway

Rightfiber brings together two established fiber providers under a single organization designed to expand scale, resources, and investment while maintaining a local operating approach.

The transaction still needs customary approvals and regulatory review, but the larger message is already clear: The future of broadband will be shaped by companies that can combine reach, investment, and local trust. That is what makes this combination worth watching.

For full details, read the press release here.

The post One Fiber Story, Bigger Reach: Strategic Combination Forms Rightfiber appeared first on Data Center POST.

TL;DR

• AI demand is accelerating infrastructure investment and driving major changes in facility design, deployment strategies, and capacity planning.
• Power availability has emerged as one of the most significant constraints on future data center growth.
• Investors continue to support digital infrastructure expansion, but financing structures are becoming more sophisticated and risk-conscious.
• Workforce development remains essential as operators seek the talent needed to support long-term industry growth.

# # #

The rapid expansion of artificial intelligence is creating unprecedented demand for digital infrastructure, forcing the industry to rethink everything from power procurement and cooling strategies to financing models and workforce development. Those themes dominated conversations at Datacloud Global Congress 2026, held June 1-4 in Cannes, France, where industry leaders examined how to scale capacity while navigating increasingly complex operational, regulatory, and economic challenges.

Across four days of sessions, networking events, and the  Datacloud Awards, one theme remained constant: AI is accelerating infrastructure demand at a pace that is forcing the industry to rethink how future capacity will be planned and deployed. As AI workloads continue to grow, the industry is facing a reality where traditional development approaches are no longer sufficient. Operators are being asked to deploy larger facilities faster, secure power in constrained markets, attract investment, and build infrastructure that can remain relevant despite rapidly evolving technology requirements.

AI Demand Is Reshaping Infrastructure Strategy

Artificial intelligence remained the dominant topic throughout the event as operators, technology providers, and investors assessed how the market is evolving to support next-generation compute requirements. Conversations focused on how the growing share of AI workloads is changing infrastructure priorities, from facility design and cooling architectures to deployment models and regional investment strategies.

During the keynote panel examining how the data centre ecosystem is keeping pace with AI demand, Olivier Micheli, CEO & President of DATA4, joined fellow industry leaders to explore how rapidly changing workload requirements are influencing infrastructure strategies. Panelists discussed the projected growth of AI workloads, the increasing importance of inference-driven deployments, and how neocloud providers are emerging as a disruptive force with infrastructure requirements that differ from traditional hyperscale and enterprise environments. The conversation also examined how enterprise AI adoption is reshaping demand patterns and what Europe must do to remain competitive as global investment in AI infrastructure accelerates.

Many sessions also explored Europe’s efforts to strengthen its position in the global AI market. Discussions surrounding AI gigafactories, sovereign cloud initiatives, and large-scale infrastructure investments reflected growing momentum across the region as governments and private-sector organizations work to expand digital capacity.

Power Has Become the Industry’s Most Valuable Resource

While AI is driving demand, power availability is increasingly determining where and how projects move forward. Multiple sessions focused on the challenge of securing reliable energy in markets facing grid constraints, permitting delays, and growing competition for available capacity.

One of the recurring themes was the need to diversify power strategies. Industry leaders explored a range of solutions including battery energy storage systems, behind-the-meter generation, renewable energy partnerships, microgrids, and emerging nuclear technologies. Discussions also addressed the growing importance of flexibility, as operators seek to build facilities capable of adapting to changing energy markets over the coming decades.

The industry’s focus is shifting from simply obtaining power to managing energy risk. As data centers become larger and more energy-intensive, operators are evaluating how to improve resiliency while balancing sustainability goals, operating costs, and long-term growth plans.

New Financing Models Are Emerging to Support AI Expansion

The scale of AI-driven infrastructure investment is creating demand for more sophisticated funding approaches. Traditional financing structures are being supplemented by joint ventures, alternative debt vehicles, portfolio financing strategies, and new forms of risk sharing between investors, operators, and customers.

During the keynote panel, “How are DC Projects Being Funded?”, Alex Hernandez, CEO of PowerBridge, joined industry leaders to examine how capital is being deployed across traditional and AI-focused data center developments. The discussion explored the quality of customer offtake agreements, the long-term profitability of AI investments, how neocloud providers are securing financing, and the increasing use of joint venture structures to fund large-scale infrastructure projects.

Several investment-focused sessions also explored consolidation across the sector, off-balance-sheet financing models, and evolving approaches to underwriting AI infrastructure projects. While capital remains available, investors are placing greater emphasis on execution capability, power availability, and the long-term viability of infrastructure assets.

Risk Allocation Continues to Evolve

As projects grow larger and more complex, operators and customers are reassessing how risk is allocated throughout the development lifecycle. Contracting structures that worked for traditional data center projects are being reexamined as AI facilities require significantly larger investments and longer planning horizons.

Atif Ansar, Executive Chairman and Co-Founder of Foresight, participated in a panel examining how contracting models are evolving as AI gigafactories increase the scale and complexity of infrastructure projects. Discussions focused on balancing risk between tenants and operators, including how power failures, supply chain disruptions, early termination rights, and warranty and indemnity insurance are being addressed in a new generation of AI-focused agreements.

The conversation reflected a broader trend across the industry. As infrastructure projects become larger and more expensive, contractual frameworks are evolving to provide greater certainty for both developers and customers while supporting continued investment in new capacity.

Developing the Workforce Needed for Future Growth

The industry’s expansion is creating significant demand for skilled workers across engineering, construction, operations, sustainability, and energy management disciplines. While AI is driving much of the growth, workforce development remains a critical factor in determining how quickly new capacity can be delivered.

During a panel focused on creating a resilient workforce pipeline, Susanna Kass, Senior Advisor to the Board and Operating Partner at Digital Gravity Infrastructure Partners, joined industry leaders to discuss how workforce development programs can help address ongoing labor shortages across the sector. The conversation explored the evolving skill sets needed to support data center growth and strategies for expanding the talent pool across engineering, construction, operations, and energy disciplines.

Workforce challenges continue to affect projects across multiple regions, particularly as operators pursue larger campuses and increasingly complex infrastructure deployments. Industry leaders emphasized that long-term growth will depend on building sustainable talent pipelines capable of supporting the next generation of digital infrastructure.

Preparing for the Next Phase of Growth

Throughout the conference, discussions repeatedly returned to a common challenge: how to scale infrastructure quickly without sacrificing resiliency, efficiency, or long-term value. AI may be the catalyst driving today’s investment cycle, but the decisions being made around power, financing, workforce development, and facility design will influence the industry for years to come.

The path forward will require collaboration across the entire digital infrastructure ecosystem. As operators pursue larger campuses, higher-density deployments, and more ambitious growth targets, success will increasingly depend on the industry’s ability to align capital, energy, technology, and talent at unprecedented scale.

To learn more about Datacloud Global Congress and future Datacloud events, visit the official Datacloud website.

The post AI Infrastructure Growth Tests the Limits of Power, Capital and Scale  appeared first on Data Center POST.

TL;DR

• The Midwest AI Boom: A massive 100-Terabit connectivity corridor is being built in the Midwest, which is rapidly becoming a strategic hub for AI infrastructure due to its availability of land, power, and buildable space.
• Symphonic Collaboration: Building such large-scale network infrastructure requires immense trust and deep coordination across service providers, equipment vendors, and operational teams to achieve shared goals.
• Supply Chain and Efficiency: High global demand is creating supply chain bottlenecks for critical networking gear, pushing the industry to focus on smarter transport models that prioritize power and spectral efficiency over pure speed.
• Future Constraints: Moving forward, massive fiber and multi-gigawatt power requirements will be the industry’s biggest hurdles, alongside community permitting resistance. Furthermore, the extreme cost of downtime makes network diversity and resilience an absolute business imperative.

# # #

In Episode 66 of the NEDAS Live! Podcast, host Ilissa Miller sits down with Priscilla Favors of Aureon, Chris Crowe of T3 Broadband, Kurt Raaflaub of Nokia, and Jeff Sanders of Midco for a timely conversation about one of the industry’s most coordinated transport builds to date. Centered on the theme “Delivering the AI Era: Building a 100TB Midwest Connectivity Corridor,” the discussion explores why the Midwest is becoming increasingly important to AI infrastructure, and what it takes to bring large-scale network projects like this to life.

As Miller notes, the conversation goes beyond data centers and compute to spotlight the transport layer that makes AI possible. The panel makes clear that none of the AI buildout works without the underlying network infrastructure, or the “nervous system,” as one speaker describes it, that moves massive amounts of data between facilities, regions, and end users.

Why the Midwest, Why Now

One of the most compelling themes in the episode is the Midwest’s rising role in the digital infrastructure landscape. Priscilla Favors explains that the region is benefiting from the growing need for land, power, and buildable space, especially as hyperscale and AI deployments expand beyond traditional coastal markets. What once may have been viewed as secondary territory is now proving to be strategically positioned for the next wave of infrastructure growth.

Chris Crowe adds that the industry is in a period of unprecedented adoption, with demand rising faster than many expected. As AI accelerates, so does the need for connectivity that can support new workloads, new architectures, and new expectations around speed and resilience.

Collaboration at Scale

A major takeaway from the conversation is that projects of this magnitude cannot be executed by one company alone. Jeff Sanders describes the deployment as a symphony, with each participant contributing specialized expertise while staying tightly aligned on the shared goal. From design and fulfillment to construction and interconnection, the build required deep coordination across service providers, equipment vendors, and operational teams.

Favors reinforces that point by emphasizing how critical trust was throughout the process. The work moved quickly, required executive approval at unusual hours, and demanded collaboration across technical, financial, and leadership levels. In her view, the project succeeded because the partners were willing to move together, adapt quickly, and rely on one another’s expertise.

Supply Chain Pressure

The episode also highlights a growing operational challenge across the industry: supply chain constraints. Crowe explains that major and minor components alike can become bottlenecks when global demand spikes. From cabling and shelves to amplifiers and other critical gear, large projects are increasingly impacted by component availability and timing.

Kurt Raaflaub expands on the larger market backdrop, pointing to dramatic increases in data center capital expenditures and the pressure that AI and cloud providers are placing on the broader ecosystem. He notes that regional service providers and integrators are essential to keeping projects moving, especially as the market decentralizes and more connectivity is needed between secondary markets.

Networks Need to Evolve

If the first phase of digital infrastructure was about more bandwidth, the next phase is about efficiency, flexibility, and smarter transport. Raaflaub explains that optical networking is moving beyond pure speed and toward spectral efficiency, lower power consumption, and better cost per bit. In his view, the infrastructure that worked a decade ago is no longer enough for today’s AI-driven requirements.

Sanders echoes that shift, pointing to solutions such as 800-gig wavelength services, managed optical fiber network services, and more adaptable transport models. The era of simply “throwing bandwidth at it” is giving way to a more nuanced approach built around customer needs, geography, diversity, and timing.

Looking Ahead

When asked what the industry may underestimate over the next five years, the panel repeatedly returns to two words: fiber and power. Sanders predicts that intra-building fiber requirements inside AI campuses may become even more massive than many expect, while power demands could escalate toward multi-gigawatt clusters.

Favors adds that land and power availability will remain significant constraints, while also warning that downtime is becoming far too expensive to ignore. She shares that even a single day of outage can cost millions, reinforcing why diversity and resilience are now business imperatives, not just technical preferences.

A Race Defined by Partnerships

The episode closes on a bigger industry truth: AI infrastructure is not just a technical race, but a partnership race. The panel agrees that success will depend on collaboration across suppliers, integrators, service providers, and customers, as well as the ability to educate stakeholders and adapt to changing political, social, and operational realities. Sanders, in particular, warns that community resistance and permitting hurdles may become defining constraints on where AI data centers are built.

As Miller concludes, the industry is at the tip of a much larger transformation, and this Midwest deployment may be just the beginning. With AI demand accelerating and infrastructure expectations changing rapidly, the message from Episode 66 is clear: the next era will be built by those who can move fast, think collaboratively, and deliver at scale.

To continue the conversation, listen to the full episode here.

The post Delivering the AI Era: Building a 100-Terabit Midwest Connectivity Corridor appeared first on Data Center POST.

TL;DR

• The True Data Center Bottleneck: While power and space often dominate the conversation, the real strategic obstacle facing operators is a severe lack of trusted, near-real-time visibility into their own physical, logical, and virtual infrastructure.
• The Demise of Static Records: Managing dense, distributed infrastructure via fragmented spreadsheets and outdated documentation is now a major liability; operators must replace passive record-keeping with a continuous, audit-ready layer of operational intelligence.
• The HDIM Solution: To eliminate these blind spots, organizations are adopting Hybrid Digital Infrastructure Management (HDIM) platforms to create a unified operational digital twin, which translates disconnected data into actionable facts for capacity, compliance, and resilience planning.

# # #

By Herman Chan, President and CEO, Sunbird Software

Data Center Infrastructure Management (DCIM) software has matured considerably over the past decade. Deployments are faster, interfaces are easier to use, integrations are deeper, and organizations across industries are seeing real, measurable results.

According to Gartner, DCIM software has reached a critical inflection point in the Hype Cycle: the “Plateau of Productivity.” This is a recognition that DCIM software has gone mainstream, adoption is accelerating, and proven solutions are delivering measurable value.

That’s why, if DCIM software is not yet in your plans, now is the time to take a serious look.

What Is the Gartner Hype Cycle and Where Does DCIM Software Stand?

The Gartner Hype Cycle tracks how technologies mature from early innovation through inflated expectations, disillusionment, and eventually to sustained productivity. It is used by organizations to assess and reduce the risk of adopting new technologies.

DCIM software’s trajectory through the hype cycle began about 15 years ago. First-generation tools struggled with long deployment cycles, poor usability, and limited integration capabilities. Early adopters found a significant gap between vendor hype and the reality of slow, difficult tools. DCIM software fell into the Trough of Disillusionment, and many vendors that couldn’t close that gap didn’t survive.

Over the past decade, modern DCIM platforms have addressed those shortcomings. Deployments became faster. Interfaces became more intuitive. Out-of-the-box connectors and open APIs enabled easier integration with adjacent tools. As successful customers evangelized their results, DCIM software climbed the Slope of Enlightenment.

Today, Gartner’s placement of DCIM software in the Plateau of Productivity confirms that DCIM has earned its place as a proven, mainstream tool for data center operations.

Uptime Institute offers a complementary view. Rather than seeing DCIM software as a standalone product, Uptime Institute frames it within a broader concept called Data Center Management and Control (DCM-C): a framework in which multiple specialized tools work together across complex environments. In that model, DCIM software serves as the central hub connecting facility systems, IT operations tools, and business platforms.

What’s Driving DCIM Software Deployments Today?

At a certain point, the complexity of managing distributed infrastructure outgrows the point tools most teams are still relying on. Spreadsheet updates take too much time, manual processes break down, and inaccurate data leads to increased risk.

That’s the problem DCIM software was built to solve, and that’s why adoption has accelerated as environments have gotten harder to manage and the C-suite is recognizing the importance of data centers supporting their mission critical corporate operations.

Today, more and more organizations are deploying DCIM software to:

• Maintain an accurate asset inventory across all sites, including remote edge sites and IDF closets, plus manage the lifecycle of those assets.
• Visualize sites with 3D digital twin modeling to support remote management
• Make informed capacity planning decisions to reduce overprovisioning or stranded capacity of space, power, and cooling
• Automate repetitive tasks such as updating rack elevations, generating reports, and processing move, add, and change requests
• Monitor power and environmental conditions with threshold alerts for early issue detection
• Map relationships and dependencies for faster troubleshooting and impact analysis
• Consolidate key information from multi-vendor tools into a single pane of glass

What ROI Are DCIM Software Customers Achieving?

The business case for DCIM software is now well-documented. Real-world DCIM ROI stories include:

• 40% more usage out of facilities and power resources
• 33% fewer cabinets to do the same work
• 66% consolidation of colo cages, saving $40,000 per month
• $160,000 saved by identifying decommissioned assets still under active maintenance contracts
• 75% less manual effort to perform asset audits
• 75% fewer physical visits to the data center
• $100,000 saved through tool consolidation

What drives these results is visibility. DCIM software surfaces what manual tracking misses: stranded capacity, inaccurate asset records, and operational inefficiencies.

How Are Organizations Leveraging DCIM Software to Achieve a Single Pane of Glass?

The most mature DCIM software deployments go beyond a standalone implementation. Organizations are integrating DCIM software with their multi-vendor toolset to create a single pane of glass: one intuitive GUI with one enterprise-class relational database for all users.

Common integration points with DCIM software include CMDB and ticketing systems, server and network management tools, public and private cloud platforms, colocation monitoring tools, observability platforms, and DevOps tools. When DCIM software serves as the single pane of glass and single source of truth, assets automatically stay synchronized across systems, workflows cross team boundaries without manual handoffs, and leadership has access to real-time dashboards rather than static reports.

Published case studies of real-world deployments illustrate what this looks like in practice.

The World Bank integrated DCIM software with ServiceNow to automate provisioning throughout the asset lifecycle from purchasing through deployment. ServiceNow, in turn, is integrated with SAP, creating an end-to-end automated workflow. Assets flow from purchase orders in SAP into ServiceNow, and from there into DCIM software with cabinet locations, installation status, and lifecycle events synchronized to the other systems without manual effort.

eBay used DCIM software APIs to integrate DCIM software with ServiceNow to synchronize 600 daily activities across systems. Moves, adds, changes, and decommissions that are documented in ServiceNow automatically flow to their DCIM tool, eliminating the double manual data entry that had previously been required to keep both platforms up to date.

Brussels University Hospital integrated DCIM software with Dell OpenManage Enterprise to automatically pull key asset and configuration data into their DCIM. With DCIM software as their single pane of glass, they eliminated manual lookups and gained the ability to launch a server console with a single click from its asset record in their DCIM tool.

These integrations were built using out-of-the-box connectors and documented APIs available in modern DCIM software and reflect how far DCIM’s integration capabilities have come.

What Should You Look for When Selecting a DCIM Vendor?

The time is now to deploy DCIM software, but selecting the right vendor for your organization is critical. When evaluating vendors, focus on:

• Ease of deployment and use. Prioritize platforms that are fast to deploy, easy to use, and fully browser-based and mobile-ready.
• Completeness of functionality. For a comprehensive solution, look for coverage across asset, capacity, change, energy, environment, power, visualization, security BI & analytics, and connectivity.
• Openness and integration. Fully documented RESTful APIs and out-of-the-box connectors are essential. The platform should fit into your existing tool ecosystem, not require you to rebuild around it.
• Vendor focus. A pure-play DCIM vendor will invest more consistently in the platform than one managing it as a secondary product line.
• Customer results and references. Ask for documented case studies and peer references in environments similar to yours.
• Quality of support. Look for strong customer satisfaction data, responsive technical teams, and SLA commitments.
• User engagement and community. The best vendors treat customers as partners and are focused on their success. Look for active user groups, customer workshops, and opportunities to provide input on the product roadmap.

The Time to Act Is Now

According to Gartner, DCIM software has reached a turning point by achieving its place on the Plateau of Productivity.

The organizations that have switched to modern DCIM software are already operating more efficiently, making better capacity decisions, and achieving real cost savings.

The question is no longer whether DCIM software can deliver, but how much longer it makes sense to manage your data centers without it.

# # #

About the Author

Herman Chan is the CEO and President of Sunbird Software, a global leader in DCIM software. Since Sunbird’s 2015 spin-off from Raritan, Chan has led Sunbird through a period of significant growth, scaling the organization into a global company that serves Global 2000 customers. He is recognized for his strategic leadership, focus on product innovation, and commitment to delighting customers by simplifying complex data center operations through second-generation DCIM software.

The post The State of DCIM and the Gartner Hype Cycle appeared first on Data Center POST.

TL;DR

• The True Data Center Bottleneck: While power and space often dominate the conversation, the real strategic obstacle facing operators is a severe lack of trusted, near-real-time visibility into their own physical, logical, and virtual infrastructure.
• The Demise of Static Records: Managing dense, distributed infrastructure via fragmented spreadsheets and outdated documentation is now a major liability; operators must replace passive record-keeping with a continuous, audit-ready layer of operational intelligence.
• The HDIM Solution: To eliminate these blind spots, organizations are adopting Hybrid Digital Infrastructure Management (HDIM) platforms to create a unified operational digital twin, which translates disconnected data into actionable facts for capacity, compliance, and resilience planning.

# # #

By Oliver Lindner, Director of Product Management at FNT Software 

Data centers have long been considered an organization’s operational backbone. While that is still true today, they are also, unfortunately, becoming a strategic bottleneck. Several forces are driving this shift. AI demand is accelerating capacity requirements, power and water availability are shaping site decisions, and new regulations are turning infrastructure documentation into compliance evidence. At the same time, operators are expected to scale faster, report more transparently, and run increasingly distributed environments with limited specialist talent.

Looking at this situation from a PESTLE view, which organizations use to understand how external factors can affect their business, sheds light on the situation and makes one thing clear: the pressure is coming from every direction. The good news, however, is that the underlying requirement is the same across all six dimensions: data center operators and enterprise infrastructure leaders need a trusted, near-real-time view of their physical, logical, and virtual infrastructure.

What surprises me, after 25+ years working with data center operators, is how often the conversation still defaults to “we need more capacity” or “we need to lease more power” when the real constraint is data quality. The PESTLE forces described below all converge on the same blind spot, and it isn’t power, water, or workforce talent. It’s that most operators cannot trust what their own documentation tells them.

Component 1: Political

Sovereignty Becomes an Architecture Decision

Data localization rules, cloud sovereignty strategies, and trade tensions are reshaping where workloads, data, and infrastructure documentation are allowed to reside. At the same time, public funding and capacity-allocation programs across the EU, North America, and Asia-Pacific — from EU sovereign-cloud initiatives, to U.S. federal infrastructure investment, to Singapore’s Green Data Centre Roadmap and Japan’s METI cloud and AI-infrastructure subsidies — are creating opportunities for expansion, while attaching new sustainability and resilience conditions to that growth.

Sovereignty is no longer just a contractual topic. It has become an architecture decision.

For data center leaders, sovereignty means knowing not just where workloads are hosted, but where the supporting infrastructure and documentation are managed — and being able to prove it. And here the blind spot shows itself first: most organizations cannot answer “where physically does this workload’s underlying infrastructure reside, and who controls it?” from a single trusted source. Without that, every sovereignty argument is rhetorical.

Component 2: Economic

From Build-Out to Better Utilization

The economics of data center operations are changing quickly. AI workloads are driving new demand for space, power, and cooling. Energy availability is becoming a limiting factor in some regions, while rising electricity costs are putting additional pressure on operating models. At the same time, the workforce talent gap remains a major challenge. Many operators are being asked to run larger, denser, and more distributed estates with teams that are already stretched.

As a result, the focus is shifting from pure build-out to better use of existing infrastructure. CFOs and infrastructure leaders increasingly need answers to practical questions such as: Where do we still have usable capacity? Which sites are constrained? Which assumptions are outdated? Where can we optimize before investing in new capacity? These questions cannot be answered reliably with fragmented spreadsheets or static documentation. In nearly every conversation I have on this, the team suspects they have unused capacity somewhere — but no one trusts the documentation enough to commit to it without a physical walk-through first.

Component 3: Social

Transparency Becomes Part of the License to Operate

Data centers are becoming more visible to communities, regulators, investors, and employees. Local concerns around land use, noise, water consumption, energy demand, and grid impact are now part of the public conversation. Internally, the same visibility challenge affects talent. The industry must attract new professionals while competing with more visible areas of the technology sector. Younger professionals often expect modern tools, transparent processes, and meaningful sustainability commitments – not manual documentation work and disconnected systems.

For operators, this creates a dual challenge. They must communicate more clearly to external stakeholders while also making infrastructure work more manageable and attractive internally. Visibility is no longer only an operational advantage; it is becoming part of the industry’s social license to operate. That social license is only as strong as the data behind it. The first time an outside stakeholder traces a public claim back to its source and finds the documentation can’t support it, the credibility loss is hard to recover from.

Component 4: Technological

Complexity Outpaces Static Documentation

Data center infrastructure is becoming denser, more distributed, and more technically complex. AI clusters are pushing power and cooling requirements beyond traditional assumptions. Liquid cooling, on-site generation, hybrid cloud, edge architectures, and OT convergence are expanding the technical surface area that operators need to understand and control.

The challenge is not only that infrastructure is growing; it’s that physical, logical, and virtual dependencies are becoming harder to trace. The operators I speak with are no longer asking how fast they can build. They are asking which assumptions in their existing estate are still true. Most discover that several of those assumptions quietly stopped being true months ago, and nothing in the documentation flagged the change.

A change in one domain can affect capacity, service availability, compliance, energy consumption, or resilience in another. Without a connected view of infrastructure, teams are forced to make critical decisions based on incomplete or outdated information. In this environment, documentation can no longer be a passive record of what was installed. It must become an operational intelligence layer.

Component 5: Legal

Compliance Becomes Continuous

Regulatory pressure is increasing across the data center and digital infrastructure landscape globally. In the EU, the Data Act, NIS2, DORA, and the Energy Efficiency Directive raise expectations around transparency, resilience, data control, and operational evidence. In the U.S., SEC cybersecurity disclosure rules, the forthcoming CIRCIA incident-reporting regime, and state climate-disclosure laws such as California SB-253 push the same agenda. In Asia-Pacific, Australia’s Security of Critical Infrastructure (SOCI) Act now mandates Critical Infrastructure Risk Management Programs covering data storage systems, Singapore’s Cybersecurity Act extends to critical information infrastructure, and Japan’s Economic Security Promotion Act designates cloud programs as critical products requiring resilient supply. The common direction is unmistakable: operators must shift from periodic documentation to continuous proof.

In practice, that means demonstrating not only that policies exist, but that infrastructure dependencies are understood, risks are visible, and reporting data is reliable. For this reason, energy, water, waste heat, ICT capacity, service dependencies, and asset relationships are all increasingly relevant to compliance and audit processes. Manual evidence collection is too slow and fragile for this new environment where compliance readiness needs to be built on current operational data. Auditors under NIS2 and DORA are increasingly skipping the policy binder and asking a single question first: “show me the live dependency map.” Most teams can’t, and the conversation gets harder from there.

Component 6: Environmental

Sustainability Moves from Reporting to Operational Proof

Energy efficiency, water usage, carbon impact, and waste heat reuse are becoming strategic data center topics. Sustainability expectations are no longer limited to ESG reporting. They increasingly influence permitting, customer requirements, investor confidence, and regulatory obligations.

This creates a practical documentation challenge. Operators need to understand how infrastructure assets consume energy, how capacity is used, where inefficiencies exist, and how sustainability KPIs connect to real infrastructure. High-level metrics are no longer enough. Leaders need infrastructure-level transparency across sites, rooms, racks, assets, services, and dependencies. Sustainability reporting is far more credible when it is based on connected infrastructure data rather than manual consolidation pieced together from disconnected tools.

The inverse is worth keeping in mind: once an auditor or investor traces a published KPI back to its source and finds the underlying data unreliable, the credibility damage takes far longer to repair than the documentation work would have taken in the first place.

The Common Thread: You Cannot Manage What You Cannot See

All these external challenges expose the same underlying weakness: many organizations lack a trusted, connected view of their infrastructure. The good news is that visibility is achievable with a unified foundation of trustworthy, near-real-time infrastructure information. Such a holistic view surfaces hidden realities within the infrastructure to inform decision making and combat PESTLE forces.

• Political pressure requires sovereignty and control. A single trusted source for where infrastructure resides and who controls it turns sovereignty from a contract clause into an architectural fact.
• Economic pressure requires better use of existing capacity. Current data on space, power, cooling, connectivity, and utilization replaces walk-throughs and assumptions with decisions teams can actually commit to.
• Social pressure requires transparency, both inward and outward. Modern, connected tools make infrastructure work attractive to new talent, and make external claims defensible when stakeholders look behind them.
• Technological pressure requires dependency visibility across physical, logical, and virtual layers. Without it, a change in one domain creates surprises in others; with it, “what if?” becomes a planning question rather than a recovery one.
• Legal pressure requires audit-ready evidence. Mapping dependencies from business services down to the infrastructure they rely on lets teams answer “show me the live dependency map” without maintaining parallel documentation.
• Environmental pressure requires reliable sustainability data. Consolidated asset, capacity, energy, and water data make recurring reports a byproduct of operations rather than a quarterly scramble.

Many organizations face a visibility gap because they rely on spreadsheets, isolated DCIM tools, BMS-centric views, and siloed CMDBs. While each of these may reveal part of the picture, they often fail to provide the connected infrastructure intelligence needed to plan, operate, report, and prove resilience across complex hybrid environments.

How Infrastructure Management Software Can Help

This is the gap that Hybrid Digital Infrastructure Management (HDIM) platforms are built to address. Such software consolidates physical, logical, and virtual infrastructure data across sites, domains, and vendors, turning fragmented documentation into the operational digital twin behind capacity, compliance, and sustainability decisions. In practice, operators can use this type of software to:

• Plan capacity decision on actual utilization
• Manage multi-site and edge environments through a single source of truth, regardless of vendor mix
• Overcome skills shortages by replacing manual documentation work with automated reconciliation
• Generate sustainability KPIs from live infrastructure data instead of quarterly consolidation
• Prove resilience by tracing every business service to the physical, logical, and virtual assets it depends on
• Demonstrate sovereignty by design with a defensible record of where infrastructure resides and who controls it

Infrastructure Visibility Is Becoming Strategic

External forces are reshaping the data center landscape. AI demand, regulatory pressure, sustainability expectations, energy constraints, and skills shortages are not temporary challenges. They are structural forces that will define infrastructure strategy over the coming years.

The data centers that navigate the next 24 months successfully will not simply be those with the most capacity. They will be those with infrastructure data reliable enough to guide capacity planning, dependency management, compliance evidence, sustainability reporting, and operational decision-making. In the next phase of data center strategy, space, power, and cooling will only get you as far as the data behind them lets you go.

# # #

About the Author

Oliver Lindner has over 30 years of experience in IT and the management of IT infrastructures with a focus on data centers. He has worked for many years at FNT Software, a leading provider of integrated software solutions for IT management. In his current position as Director of Product Management, he is responsible for the strategic direction and continuous improvement of the software products for data centers. The aim is to support customers in the efficient and transparent design of their IT infrastructure.

Oliver Lindner attaches great importance to customer focus, innovation and quality. His expertise also includes the development and provision of Software as a Service (SaaS) solutions that offer customers maximum flexibility and efficiency. To this end, he works closely with his own team, partners and customers to create sustainable and innovative software solutions.

The post Six Pressures, One Blind Spot: A PESTLE View of the Data Center appeared first on Data Center POST.

TL;DR

• Foresight won the 2026 Datacloud Global Award for Best AI Innovation for its Predictive Project Delivery platform.
• The platform uses predictive AI to identify project risks early, improve schedule certainty, and accelerate time-to-revenue for large-scale infrastructure projects.
• The recognition highlights the growing importance of AI-driven project intelligence as investment in data centers, power infrastructure, and other critical assets continues to rise.
• The award follows strong company momentum, including a $25 million Series A funding round and increasing adoption among leading infrastructure organizations.

# # #

Foresight, the digital Chief Time Officer for major infrastructure programs, has been named the winner of the Best AI Innovation category at the 2026 Datacloud Global Awards, one of the digital infrastructure industry’s most prestigious awards programs. The award was presented during Datacloud Global Congress in Cannes and recognizes organizations delivering measurable impact through the application of artificial intelligence across the digital infrastructure ecosystem.

Foresight received the award for its Predictive Project Delivery platform, which helps owners and operators of large-scale infrastructure programs identify delivery risks earlier, improve schedule predictability, and accelerate time-to-revenue across hyperscale data centers, power infrastructure, advanced manufacturing facilities, transportation programs, and other capital-intensive projects.

The recognition highlights the growing importance of artificial intelligence in addressing one of the infrastructure sector’s most persistent challenges: project delays. As investment in AI infrastructure continues to accelerate globally, organizations are increasingly seeking new ways to improve delivery certainty and bring critical capacity online faster.

Foresight’s platform applies predictive AI to help project teams identify emerging risks before delays become unavoidable. Leveraging one of the world’s largest datasets of planned versus actual project outcomes, the platform provides leaders with greater visibility into schedule performance and the factors most likely to impact successful project delivery.

According to Dr. Atif Ansar, Co-Founder and Executive Chairman of Foresight, the award validates the company’s mission to help organizations manage time with the same rigor traditionally applied to capital.

“Receiving the Datacloud Global Award for Best AI Innovation is a tremendous honour and a validation of a simple idea: time is money,” said Ansar. “Every major organisation has rigorous governance around capital allocation and financial performance. Yet project time, despite being one of the largest drivers of value creation and value destruction, often receives far less visibility and control.”

The award follows a period of significant momentum for Foresight, including the recent completion of its $25 million Series A funding round led by Macquarie Capital Venture Capital and continued adoption of its platform among leading infrastructure owners, operators, and delivery organizations.

To continue reading, read the full press release here.

The post Foresight Earns Best AI Innovation Recognition at Datacloud Global Congress appeared first on Data Center POST.

TL;DR

• The Angelwish WIFFLE Ball Classic demonstrated how industry communities can come together in support of a meaningful cause.
• Approximately 21 teams participated, reflecting strong engagement from organizations across the digital infrastructure and telecommunications sectors.
• More than $25,000 was raised to help Angelwish create memorable experiences for children living with chronic illnesses.
  The event highlighted the impact that collective action, community involvement, and charitable giving can have beyond the workplace.

# # #

On June 4, members of the iMiller Public Relations (iMPR) team joined professionals from across the digital infrastructure, telecommunications, and technology communities for the 2026 Hoboken Angelwish WIFFLE Ball Classic. While the competition on the field was spirited, the focus of the day extended far beyond wins and losses.

Hosted by Angelwish, the annual tournament brings together companies, colleagues, friends, and families to raise funds for children living with chronic illnesses. Founded in 1999, Angelwish helps fulfill wishes for children around the world while also promoting philanthropy and community engagement. The organization has spent more than two decades creating meaningful experiences for children and their families, helping bring moments of joy during some of life’s most difficult circumstances.

At Frank Sinatra Park, set against the backdrop of Hoboken’s waterfront, the Angelwish WIFFLE Ball Classic has become a longstanding tradition that combines fundraising, networking, and a healthy dose of childhood nostalgia. What makes the event unique is its simplicity: a  game that many participants grew up playing becomes a vehicle for something much larger for supporting children who are facing challenges most adults would struggle to navigate.

Over the years, the tournament has attracted participation from organizations across the communications and digital infrastructure sectors, creating an atmosphere where friendly competition  quickly gives way to collaborate and to come together in support of a meaningful cause.

This year’s tournament featured approximately 21 teams representing organizations from across the tech industry, telecommunications, technology, and professional services sectors. Participants included companies such as NJFX, CoreWeave, Ciena, Megaport, 1547, and many others that came together in support of the cause. Throughout the day, participants stepped away from conference rooms and video calls to spend time together outdoors, reconnect with industry peers, and contribute to a mission that impacts children and families around the world.

For the iMPR team, the tournament served as a reminder that some of the most meaningful industry gatherings are not centered on business development or market discussions, they are centered on people. Events like the Angelwish WIFFLE Ball Classic demonstrate how a community can come together in support of something bigger than itself, creating tangible impact while building connections that extend beyond the workplace.

Another successful tournament came to a close, raising over $25,000. The lasting takeaway is not who advanced the furthest in the bracket or who hit the longest home run, but  the collective effort of dozens of companies who dedicated their time, energy, and resources to support children living with chronic illnesses. That shared commitment is what continues to make the Angelwish WIFFLE Ball Classic such a special event year after year.

iMPR is proud to have participated in this meaningful tradition and support the important work being done by Angelwish, and we look forward to returning next year to continue contributing to a cause that makes a meaningful difference in the lives of children and families.

The post More Than a Game: Supporting Angelwish at the 2026 Hoboken Annual WIFFLE Ball Classic appeared first on Data Center POST.

TL;DR

• Power availability continues to influence where and how new data center capacity is developed.
• AI workloads are driving changes in facility design, construction strategies, and infrastructure planning.
• Regional markets are attracting increased investment as operators expand beyond traditional data center hubs.
• Workforce development and risk management remain critical to supporting long-term industry growth.

# # #

AI Demand Reshapes Power, Construction, and Expansion Strategies Across BISNOW’s DICE Event Series

The data center industry entered 2026 facing unprecedented demand for digital infrastructure. To address the opportunities and challenges ahead, industry leaders gathered at three major BISNOW events: National DICE Construction, Design & Development – East, Data Center Investment Conference & Expo (DICE) Southeast, and National Data Center Investment Conference & Expo (DICE) Power Capacity, Energy & Sustainability. Together, the events examined how operators, developers, investors, utilities, and technology providers are adapting to evolving infrastructure requirements driven by artificial intelligence, cloud computing, and continued digital transformation.

Although each event focused on a different segment of the industry, several themes emerged consistently across the discussions. Power availability, site selection, construction innovation, workforce development, and long-term resiliency remain among the most important considerations for organizations seeking to support the next generation of data center growth.

AI Is Accelerating Infrastructure Planning and Development

Artificial intelligence continues to reshape the way data centers are planned, designed, and deployed. As organizations invest in AI infrastructure, operators are being challenged to support higher-density workloads, larger campuses, and increasingly sophisticated technology environments. These changing requirements are forcing the industry to rethink traditional approaches to development and operations.

Discussions throughout the DICE event series highlighted how organizations are adapting to these demands through advanced cooling strategies, modular construction techniques, integrated project delivery models, and more flexible infrastructure planning. Attendees also explored how AI is influencing everything from facility design and procurement decisions to construction schedules and long-term capacity planning. The consensus was that AI is no longer simply creating incremental demand; it is fundamentally changing how infrastructure is developed and operated.

Emerging Markets Continue to Attract Investment

As demand for capacity continues to increase, operators are expanding beyond traditional data center markets in search of new growth opportunities. Regional markets throughout the Southeast and other parts of the United States are attracting attention due to available land, economic development incentives, connectivity assets, and opportunities to support future expansion.

At the same time, site selection has become increasingly complex. Organizations must evaluate a wide range of factors that extend well beyond land acquisition, including power availability, utility partnerships, permitting timelines, transportation infrastructure, workforce availability, and community engagement. These considerations are playing a growing role in determining where projects move forward and how quickly new facilities can be delivered.

Conversations at DICE Southeast reflected the industry’s continued focus on balancing growth with long-term sustainability. As more markets compete for data center investment, stakeholders are increasingly seeking strategies that support both economic development and responsible infrastructure expansion.

Power Availability Remains a Critical Industry Focus

Few topics generated more discussion across the DICE event series than power. As AI workloads continue to increase energy requirements, operators are facing mounting pressure to secure reliable capacity while navigating grid constraints, lengthy utility interconnection timelines, and evolving regulatory requirements.

The National Data Center Investment Conference & Expo (DICE) Power Capacity, Energy & Sustainability focused extensively on how organizations are responding to these challenges. Discussions examined a range of solutions, including utility partnerships, powered land strategies, on-site generation, battery energy storage systems, microgrids, renewable energy integration, and alternative energy technologies.

A recurring theme was the need for greater flexibility in energy planning. Rather than relying solely on traditional utility models, many organizations are evaluating diversified approaches that can help accelerate deployment schedules while improving resiliency. As infrastructure demand continues to grow, power strategy is becoming a key component of long-term business planning rather than simply an operational consideration.

Construction, Workforce Development and Risk Management Are Evolving

The rapid pace of industry growth is also creating new challenges for project delivery. Larger campuses, higher-density environments, and compressed timelines are requiring organizations to adopt more integrated approaches to construction, engineering, procurement, and operations.

Throughout the events, attendees explored how new construction technologies, design methodologies, and delivery models are helping improve efficiency and reduce project risk. Organizations are increasingly emphasizing collaboration across stakeholders to improve planning, streamline execution, and maintain quality throughout the development lifecycle.

Workforce development was another important topic discussed across multiple sessions. The industry continues to face growing demand for skilled professionals across engineering, construction, operations, and technical disciplines. As projects become more complex, building sustainable talent pipelines is becoming essential to supporting future growth and maintaining operational excellence.

Risk management discussions also highlighted the importance of preparing for supply chain disruptions, cybersecurity threats, regulatory changes, and climate-related challenges. Industry leaders emphasized that resiliency must be considered throughout every stage of development, from site selection and design to construction and ongoing operations.

Positioning for the Next Phase of Growth

The conversations held across BISNOW’s DICE event series in the first quarter of 2026 demonstrated that the data center industry is entering a new phase of maturity. Demand remains strong, but success increasingly depends on an organization’s ability to align infrastructure planning, energy strategy, construction execution, and operational readiness.

Organizations that can effectively navigate power constraints, support AI-driven workloads, attract skilled talent, and identify strategic growth markets will be well positioned for long-term success. As the industry continues to evolve, collaboration across the digital infrastructure ecosystem will remain essential to delivering the capacity required to support future innovation. To learn more about upcoming DICE events and register for future conferences, visit BISNOW’s events page at www.bisnow.com/events.

The post Digital Infrastructure Growth Creates New Challenges and Opportunities appeared first on Data Center POST.

TL;DR

• Panhandle expansion continues: Duos Edge AI will host an open house June 18 to showcase its patented modular EDC deployed with Hereford ISD.
• A century of community, now with edge computing: Hereford ISD spans 900 square miles and serves 4,000+ students with infrastructure built for AI, digital access, and workforce readiness.
• Sustainable by design: The Hereford EDC runs on on-grid power and air cooling, reducing environmental impact while supporting digital growth.

# # #

Duos Technologies Group Inc. (Nasdaq: DUOT), through subsidiary Duos Edge AI, Inc., has announced an open house in Hereford, Texas on Thursday, June 18, 2026, from 9:00 AM to 11:00 AM CDT to showcase its patented modular Edge Data Center deployed in partnership with Hereford Independent School District.

Beyond supporting K-12 education, the Hereford deployment creates new opportunities for local businesses to adopt advanced computing and data-driven technologies. The facility operates with a compact footprint, meets SOC compliance standards, and is designed to scale alongside the community’s evolving needs, fostering stronger digital ecosystems and long-term economic development across the Panhandle.

“Bridging the digital divide is core to our edge expansion, particularly in the Texas Panhandle and across the state,” said Doug Recker, CEO of Duos Edge AI and Duos Technologies Group,Inc. “We look forward to connecting with the community at the Hereford open house to share how this facility is already bringing tangible benefits to schools, businesses, and healthcare organizations in the area.”

“We look forward to connecting with the community at the Hereford open house to share how this facility is already bringing tangible benefits to schools, businesses, and healthcare organizations in the area.”

To learn more about Duos Edge AI and register for the open house, visit https://freeevite.com/event.php?e=3wk0cpbdauds1_E5Uyor-A.

The post Duos Edge AI to Host Hereford Edge Data Center Open House appeared first on Data Center POST.

TL;DR

• The Huge Potential of Waste Heat: Liquid-cooled AI data centers generate massive amounts of heat that, instead of being uselessly vented into the atmosphere, can be efficiently captured using established heat exchanger technology and redirected to local district heating networks.
• Massive Efficiency Gains: Properly implemented heat recovery systems could drastically reduce global energy waste, tapping into an estimated 3,100 thermal terawatt-hours of wasted heat annually to potentially save up to €140 billion worldwide.
• Geographic and Contractual Barriers: While the technology is readily available, the main hurdles to widespread adoption are the physical distance between data centers and municipal heating networks, alongside the complex contracts needed to manage fluctuating, seasonal community heat demand.
• Regulatory and Community Incentives: Forward-thinking operators can leverage this opportunity to improve sustainability and benefit from new government incentives, such as European tax exemptions for reusing heat, while establishing themselves as valuable, environmentally responsible community neighbors.

# # #

Data centers, especially those powering AI, generate vast amounts of heat. But that heat doesn’t have to be wasted: using well established technology, it can be recovered and reused in heating and hot water systems. Ulrik Vadstrup, HVACR Segment Manager for ABB asks why, in a sector built for speed, are so many data centers slow to take up this opportunity?

Picture a cruise ship gliding through Arctic waters – on-deck swimming pools steaming in the frigid air. On the surface, this looks incredibly wasteful: how much fuel must the ship need to burn to keep multiple pools hot in such freezing conditions?But in fact, this is an incredibly efficient use of energy. A cruise ship’s engines generate huge amounts of heat as a matter of course. With nowhere to go, that heat would make the engine room and surrounding gangways unbearable for the crew, and could even damage the ship. Swimming pools give the ship somewhere useful to put waste heat, cooling the engine and pleasing the passengers at the same time. It’s a win-win.

The same thinking applies to commercial refrigeration, brewing, food and beverage plant, plastic extrusion, and now especially to data centers: facilities like these also generate waste heat. Without somewhere to go, it ends up heating the roof of the building, then the air outside, which benefits no one.

Both a need and an opportunity for data centers

The latest generations of data centers use liquid cooling. Cold liquid, often water, is piped through the hot servers, absorbing heat before being piped away again.

Liquid cooling is common in other industries as well. And once upon a time, businesses would dispense the hot used coolant into the sewer, and pipe in fresh coolant to keep their processes cooled. But no longer. Today, regulations require businesses to recirculate coolant rather than continuously drawing and venting it. That means they need a way to quickly cool down used coolant, ready for recirculation. This requirement is the norm for new liquid-cooled data centers.

The value in heat recovery is clear. A facility generates unwanted heat in the course of its business; elsewhere, there is demand for heating and hot water. But despite the potential, McKinsey estimates that at least 3,100 thermal terawatt-hours of recoverable heat a year is still going to waste worldwide.

Technology is not the barrier

Waste heat recovery is not a new technology, or an especially complex one. All it takes is a heat exchanger, and often a heat pump. Using the same thermodynamic principle as liquid cooling, the heat exchanger transfers heat from where it’s not wanted into water or another agent, which is then piped to somewhere needing heating.

That could be somewhere in the same facility. Danish cooling compressor specialist Advansor offers combined heating and cooling systems for supermarkets, for example, which recover waste heat from the refrigeration and air conditioning systems and use it for comfort heating and hot water in the same building.

Or it could be in the local community, via a district heating network. This is where heat pumps come in. Waste heat tends to be at around 30-60°C. Older district heating systems operate at 90°C in the winter, and around 60°C in the summer. For those, heat recovery systems use a heat pump – a technology well known and widely used in heating, ventilation, and air conditioning – to lift the water temperature to a suitable level.

Naturally the higher the waste heat source temperature – which equates to how much energy is available – then the better the process efficiency, as measured by the heat pump’s coefficient of performance (COP).

Advancing technology may soon remove the need for even the relatively minor complexity of adding a heat pump. This is because the temperature of the coolant coming from the data centers is increasing due to liquid direct-to-chip cooling, while the latest generation of district heating systems work perfectly well at lower temperatures, so waste heat at 30-60°C can be directly used in those.

What about efficiency?

Any amount of recovered heat is a bonus when the alternative is expending energy to generate heat that just goes to waste.

But it still makes sense for heat recovery systems to be efficient. The point of the system is to reduce wasted energy; if the system uses inefficient motors or drives, it cannot fully realise its waste heat recovery potential.

The more efficient the variable speed drive (VSD) controlling a heat pump motor and the more efficient the motor itself, the more thermal energy the pump can provide for a given amount of electrical energy. A heat pump also needs a drive that doesn’t generate electrical harmonics which can impair power network performance and cause electrical problems.

Distance can be a challenge

In energy efficiency terms, heat recovery is clearly a positive for data centers. But there is still an upfront cost to install the system, which could take a while to pay for itself in saved heating costs.

And what if those savings are being passed on to a district heating network instead?

Often in these cases, the network offers to pay for the heat recovery system. Yet even when the system costs the data center nothing and solves a cooling problem, district heating networks still sometimes fail to convince data centers to donate their waste heat.

Sometimes it comes down to geography. Large operators generally aim to build their data centers in the lowest cost location possible. This often means building them far from the nearest district heating network connection. More distance between the data center and the heating network means longer pipes and more heat lost along the way. Above a certain distance, the connection is no longer worthwhile.

Data centers run 24/7: demand for heating is not constant

Any time a data center’s servers aren’t running, they’re losing the owner’s money. So data centers are always generating heat they need to get rid of.

On the other hand, district heating networks don’t always need heat. On hot summer days, people don’t want to heat their homes, even when they can do it for free.

Data centers need certainty, usually written into a contract, about how much heat their district heating network partner will take from their facility, and what will happen if at any point the network can’t or doesn’t want to take that much. Agreeing these contracts is the biggest barrier to increase waste heat recovery in this fast growing sector.

And even if it doesn’t directly benefit the data center, recovering waste heat is still a good idea. Data centers use a lot of energy. If even a percentage of that massive energy expenditure is going to waste, when the technology exists to recover and reuse it, data centers have a responsibility to cut that waste. European politicians have started to make that responsibility an obligation – but there is still so much more potential in this field.

Good neighbours

In the European Union, the amount of unrecovered waste heat across all industries rivals the total demand for heat and hot water in all residential and service sector buildings. Worldwide, if we recovered and reused all the heat that is currently going to waste, it could save as much as €140 billion.

And the demand, and the potential savings, are still on the rise. When electricity and gas prices can increase unexpectedly, free heat becomes more attractive, even when it calls for some up front investment. Heat pumps also become more economical as heating becomes more expensive.

For once, governments are moving faster than some businesses to recognize the opportunity. Several European governments have recently changed the law so businesses are no longer taxed for reusing waste heat. And when it’s used in district heating, waste heat is officially recognized in Europe as a clean heat source, a climate mitigation measure, and a green investment.

Today, district heating and cooling supplies 13% of the European Union’s demand. If data centers and other businesses take their governments’ hints and recover more of their waste heat, this could increase to 50% by 2050.

For some data center operators, this will mean stepping out of their comfort zone. But those who show leadership have everything to gain: more efficient operations, a more sustainable business, and a valuable role in the lives of their nearest neighbours.

# # #

About the Author

Ulrik Vadstrup is the HVACR Segment Manager for Europe at ABB, bringing over 30 years of experience in industrial automation to the role. With a background spanning system design, software programming, and OEM and direct sales, Ulrik has developed deep expertise across the full project lifecycle, working with clients and partners worldwide.

The post Don’t Waste The Waste Heat Opportunity appeared first on Data Center POST.

TL;DR

• The Nordic Integration Model: Leading data centers in the Nordic region demonstrate that true resilience requires treating the physical environment, energy strategy, and security as a single interconnected system, rather than treating them as isolated, vulnerable functions.
• Connecting Operational Signals: True protection comes from connecting data rather than just collecting it; operators must integrate video analytics, access events, and environmental sensors into a unified platform to detect anomalies before they compound into costly outages.
• Security as a Performance Driver: As facilities scale to handle complex AI workloads, treating security merely as a reactive cost center is a severe liability; if a security system does not actively contribute to facility uptime and operational efficiency, it is already obsolete.

# # #

Sienna Cacan, Global Enterprise Segment Marketing Manager, Axis Communications, explains why the Nordic data center market offers a useful model for treating security as a core part of the operating environment.

The data center has a security problem – and it’s not what most operators think. Data centers excel at what almost amounts to theatrical security: the fences, cameras, access control systems and guards which surround the perimeter. These measures are necessary, but they create a false sense of completion, and the illusion of control. Modern facilities require a shift toward operational intelligence, where security systems actively contribute to uptime, efficiency, and risk mitigation.

Data centers are operationally complex models of critical infrastructure. They carry workloads that entire economies depend upon. AI compute, cloud expansion, and edge deployments are pushing facilities to operate at unparalleled scale and complexity. In this environment, the margin for error is nil. Security cannot, therefore, simply manifest as a layer built around a center’s operations: it must be a core part of those operations, extending from fence to rack. The world is dependent on data centers getting it right.

The Nordic operating model

Across Sweden, Denmark, Norway, and Finland, a different model is emerging. The Nordic market has established itself as a global data center hub. It is an ideal habitat for data centers in general, offering renewable energy, cooler climates and political stability to an industry which needs all three. The key is that Nordic data centers operate with their environment, and not against it.

In Helsinki, for example, North’s FIN02 facility has been designed to feed excess heat into the local district heating network, turning what would once have been treated as a cooling problem into a community energy resource. In Norway, Green Mountain has explored a different version of the same idea, working with seafood producers to use waste heat in land-based aquaculture.

Data centers are becoming active parts of local infrastructure, with responsibilities that extend beyond their own walls. Remote facilities are being used to support sovereign data strategies, with Lefdal Mine Data Center in Norway acting as an extreme but useful example. Built inside a former olivine mine, it uses rock, depth and geography as part of its resilience proposition, alongside cold fjord water for cooling.

Not every facility can be built into a mountain, but the Nordic market is unusually comfortable thinking about the physical environment, energy strategy and security as parts of the same design problem. Every major function must make that system more resilient and form part of a combined whole, because if one part is treated as separate it becomes the weak point. If security is left as a mere visible perimeter rather than treated as an operational function, it will not keep pace with the facility it is supposed to protect.

From the fence line to the rack

The increased dependence on data centers – both internationally and, as centers become more integrated into their environments, locally – means the role of the fence line has been reduced at best. The industry needs to confront the uncomfortable truth that most legacy security systems contribute little to operational performance. They record incidents but don’t prevent them, generate data but don’t produce actionable insights. A camera with analytics which can pick out abnormal movement, spot equipment stress or monitor for environmental changes essentially helps run the site.

There is a place for visible security. It shows that a facility has defences and creates the appearance of control. But the interdependent Nordic approach teaches us that we must build security for the data center environment specifically and acknowledge that an effective security approach is one which considers the intersection between physical incidents, IT, and operational technology (OT). Video analytics and connected sensor platforms enable real-time, remote decision-making across distributed sites, an increasingly important capability as operators scale geographically.

A forced door in a data center can quickly become a cyber incident. A compromised connected device can be a route through the virtual perimeter and into the network. A cooling issue can become an availability event – or a threat to physical safety. Very different categories of incident, but they share a common outcome: disruption.

Security through connected signals

Operators need systems that connect signals rather than simply collect them. Video, access control, audio, environmental sensors and analytics all have value on their own, but their real strength comes when they contribute to a shared view of a facility. A single alert may mean very little. A door event, a record of unusual movement, a temperature change and an equipment alarm in combination may tell a different story.

This is where the region’s interest in digital twins and real-time facility models becomes relevant. In a large or remote Nordic site, the useful view may not be a guard watching a flat wall of feeds, but an operational model based on a trusted sensor platform that brings video, sensors, access events and environmental data into the same frame. A failing door seal, abnormal rack vibration or unexpected movement pattern may each be minor in isolation. Together, they may point to an issue worth acting on before it becomes an outage.

This is what real resilience looks like: not stronger barriers, but visual verification, audit trails, SLA evidence and increased customer trust built through smarter integration and a willingness to rethink what security is actually about. As hyperscale and colocation facilities continue to expand, the industry needs to be honest with itself that security has often not evolved at the same pace as capacity, and scaling conventional security into larger, denser and more automated data centers does not automatically improve protection.

Building true resilience with integrated thinking

In truth, the next wave of data center disruptions is unlikely to result from inadequate perimeter defences. Instead, it will stem from blind spots in operational visibility, delayed responses to emerging risks, and an over-reliance on manual processes in increasingly automated environments. Essentially, it will come from treating security as a cost center rather than a strategic capability.

The lesson is not necessarily to copy the Nordics exactly, of course. Geography, energy markets, and local regulations differ. But copying the key lesson, that resilience comes from integration, is viable everywhere. As data centers become ever more critical to the global economy, the systems that protect them must also enable performance. If your security system doesn’t improve uptime, it is already obsolete.

A data center that looks secure may still be fragile. A data center that understands itself, monitors its operations and connects security intelligence with operational decision-making is far harder to disrupt. Security should not sit around the data center; it should run through it. Anything less is theatre, and that is a poor foundation for critical infrastructure.

# # #

About the Author

Sienna Cacan, Global Enterprise Segment Marketing Manager, Axis Communications

Leads strategic marketing initiatives focused on the Technology & IT and Commercial Real Estate verticals. With more than a decade of experience across both B2C and B2B marketing, she has spent the past six years driving global demand creation and market development at Axis Communications. She works closely with end customers, ecosystem partners, and industry stakeholders to support growth and innovation across key enterprise markets.

About Axis Communications

Axis enables a smarter and safer world by improving security, safety, operational efficiency, and business intelligence. As a network technology company and industry leader, Axis offers video surveillance, access control, intercoms, and audio solutions. These are enhanced by intelligent analytics applications and supported by high-quality training.

Axis has around 5,000 dedicated employees in over 50 countries and collaborates with technology and system integration partners worldwide to deliver customer solutions. Axis was founded in 1984, and the headquarters are in Lund, Sweden.

The post From Theatre To Resilience: Lessons From The Nordic Data Center Rulebook appeared first on Data Center POST.

TL;DR

• DāSTOR has partnered with Myota to enhance its Backup as a Service (BaaS) offering.
• The solution combines DāSTOR’s managed backup expertise with Myota’s Shard and Spread™ technology.
• Customers benefit from improved cyber resiliency, instant recoverability, and reduced storage costs.
• The enhanced offering is available immediately for enterprise customers.

# # #

As organizations face growing threats from ransomware, infrastructure outages, and increasing data volumes, many are reevaluating how they approach backup and recovery. Traditional backup environments can be costly, complex, and difficult to manage, creating new challenges for IT teams focused on resiliency and business continuity.

To help address these challenges, DāSTOR has announced a strategic partnership with Myota to enhance its Backup as a Service (BaaS) offering with advanced data protection and storage optimization capabilities.

The enhanced solution combines DāSTOR’s infrastructure and managed backup expertise with Myota’s patented Shard and Spread™ technology. By encrypting, sharding, and distributing data across multiple storage locations, the solution helps improve cyber resiliency while reducing storage infrastructure requirements.

As ransomware attacks continue to target organizations of all sizes, backup and recovery strategies have become a critical component of cybersecurity planning. Many traditional backup environments rely on multiple copies of data stored across different systems, which can increase storage requirements, management complexity, and overall costs. Organizations are increasingly looking for solutions that can strengthen protection while improving operational efficiency.

Myota’s approach helps address these challenges by securing data at the point of creation and distributing encrypted data fragments across multiple storage locations. Even if attackers gain access to part of the environment, the individual data fragments are computationally impossible to reassemble without authorization. At the same time, authorized users can quickly access and recover data when needed, helping reduce downtime and improve business continuity.

“Organizations need backup solutions that improve security and resiliency without increasing costs,” said Kevin Mulqueen, CEO of DāSTOR. “Our partnership with Myota strengthens our Backup as a Service offering with a more secure and efficient approach to data protection that helps reduce storage costs for customers.”

Beyond strengthening security, the partnership is designed to help organizations better manage growing storage demands. By reducing reliance on traditional redundancy-based approaches, customers can benefit from a more efficient backup environment that lowers storage overhead while maintaining fast recovery capabilities.

The partnership supports DāSTOR’s broader strategy of delivering scalable backup and disaster recovery solutions for modern IT environments, including hybrid cloud, colocation, and high-density infrastructure deployments.

The announcement reflects a broader shift across the industry as organizations seek backup solutions that can support increasing data growth without introducing additional complexity or cost. Security, recoverability, storage efficiency, and operational simplicity are becoming equally important considerations when evaluating modern data protection strategies.

The enhanced Backup as a Service offering is available immediately to enterprise customers across healthcare, legal, financial services, manufacturing, government, and other data-intensive industries.

Read more in the full press release here.

The post DāSTOR Strengthens Backup as a Service with Advanced Cyber Resiliency Through Myota Partnership appeared first on Data Center POST.

• ZincFive was named to TIME’s World’s Top GreenTech Companies 2026 list for the second consecutive year, recognizing its innovation and sustainability leadership.
• The award highlights the growing need for safer, more sustainable power solutions as AI-driven infrastructure increases demands on data center power systems.
• ZincFive’s nickel-zinc battery technology delivers high power density, inherent safety, and sustainable performance for mission-critical applications.

# # #

In an industry where every second of uptime matters, ZincFive^® is once again earning recognition for helping shape the future of mission-critical power. The company has been named to TIME’s World’s Top GreenTech Companies 2026 list, marking its second consecutive year on the global ranking and underscoring the growing relevance of nickel-zinc technology in today’s power landscape.

The recognition arrives at a moment when data centers, AI infrastructure, and other high-demand environments are under pressure to deliver more power with fewer trade-offs. That is exactly where ZincFive has made its mark. Built around patented nickel-zinc (NiZn) battery technology, the company’s solutions are designed for immediate power applications that demand high performance, compact design, and inherent safety.

TIME and Statista evaluated more than 8,300 companies before selecting just 250 for inclusion on the 2026 list, making the recognition especially meaningful. Companies were judged on environmental impact, financial strength, and innovation drive – criteria that reflect not only what a company makes, but how it contributes to advancing the broader GreenTech sector. For ZincFive, the honor highlights the broader shift underway in power infrastructure: Sustainability is no longer a side note, but a core requirement.

As AI workloads continue to drive greater power density inside data centers, operators face increasing pressure to deploy solutions that deliver reliable performance without introducing additional safety risks or environmental concerns. Traditional battery technologies often require trade-offs between footprint, safety, sustainability, and performance.

Tod Higinbotham, CEO of ZincFive, said being named among the World’s Top GreenTech Companies “reinforces our belief that the future of power infrastructure requires solutions that are both high performing and sustainable.” He added that as AI-era infrastructure places unprecedented demands on power systems, the recognition reflects a broader industry shift toward safer, more sustainable energy storage and validates the role nickel-zinc technology is playing in delivering performance without compromise.

What makes ZincFive stand out is not just the chemistry, but the philosophy behind it. The company’s systems are engineered to combine high power density, reliable operation, and a more sustainable footprint in one compact solution. For customers navigating the future of data center power, that combination offers a compelling path forward. Designed for today’s most demanding environments, ZincFive’s nickel-zinc technology delivers reliable operation without the safety and environmental tradeoffs associated with traditional battery chemistries.

As the GreenTech landscape continues to evolve, ZincFive’s place on TIME’s 2026 list reflects more than a single achievement. While the award highlights ZincFive’s continued growth and innovation, it also points to broader changes taking place across the power infrastructure industry.  It signals the company’s continued role in shaping safer, smarter, and more sustainable power solutions for the world’s most demanding environments.

For full details, please read the press release here.

The post TIME Recognizes ZincFive for Advancing Safer, More Sustainable Power appeared first on Data Center POST.

TL;DR

• PowerBridge appointed Melissa Podesto as Vice President of Hyperscale Leasing and Data Center Sales to lead customer engagement and sales strategy.
• Podesto brings more than 20 years of hyperscale and digital infrastructure sales experience, most recently at Aligned Data Centers and previously at Digital Realty.
• The company is advancing its Alpha Digital Campus in Pecos, West Texas, a planned two-gigawatt project anticipated as part of ERCOT’s Batch 0.
• PowerBridge says the appointment supports its integrated strategy of converging power, connectivity and digital infrastructure to serve hyperscale and AI customers.

# # #

As hyperscale and AI infrastructure demand continues accelerating, customers are increasingly prioritizing speed to power, long-term scalability and integrated infrastructure execution when evaluating where to deploy capacity.

That market shift is one reason PowerBridge has appointed Melissa Podesto as Vice President of Hyperscale Leasing and Data Center Sales.

Podesto joins PowerBridge at a moment when hyperscale, cloud and AI customers are prioritizing long-term infrastructure readiness and speed to power. In her new role, she will lead customer engagement and sales strategy as the company advances its growing portfolio of powered digital infrastructure campuses across North America.

Her appointment brings more than 20 years of relationship-driven sales leadership to the team. Podesto most recently served as Senior Director of Sales at Aligned Data Centers and previously spent nearly a decade at Digital Realty as Global Sales Director, where she led hyperscale and global account sales for one of the world’s largest data center platforms. Across both companies, she became known for translating complex hyperscaler and digital native infrastructure requirements into long-term partnerships at scale.

The appointment reflects broader changes happening across the digital infrastructure industry, where hyperscale and AI customers are increasingly seeking partners that can deliver power, connectivity and campus-scale infrastructure as part of a unified strategy rather than through fragmented development models.

For PowerBridge Founder and CEO Alex Hernandez, that combination of commercial experience and customer insight aligns directly with where the company is focusing its growth.

“Melissa is a highly respected commercial leader with customer insight, a long-standing track record and market experience that will complement our energy convergence strategy,” said Hernandez, Founder and Chief Executive Officer of PowerBridge. “As demand for powered digital infrastructure continues to accelerate, Melissa’s long-standing relationships with hyperscale, cloud and AI customers will accelerate our mission to deliver large-scale powered campuses built for speed, certainty and growth.”

That strategy is anchored in an integrated approach to digital infrastructure and connectivity. PowerBridge was formed by Hernandez and the leadership team behind Cumulus Data, in partnership with FivePoint Infrastructure, which announced a $1 billion equity commitment to the company in May 2025. Today, PowerBridge is advancing several multi-gigawatt developments across West Texas, where abundant energy resources, available power infrastructure and fiber conduit connectivity are positioned to support the next phase of large-scale digital infrastructure growth.

Among those developments is the company’s Alpha Digital Campus in Pecos, West Texas, a two-gigawatt project scheduled to deliver first power in the second half of 2027 and into early 2028 as an anticipated ERCOT Batch Zero power generation and data center project.

For hyperscale and AI customers, projects like Alpha Digital Campus represent a growing shift toward infrastructure environments designed around long-term power availability, execution certainty and scalable campus development.

Podesto said the company’s differentiated platform was central to her decision to join.

“I am thrilled to join PowerBridge at such an important moment for the industry,” Podesto said. “Alex and the team were years ahead of our industry in understanding the rapid convergence between power and digital infrastructure. PowerBridge’s assets in West Texas offer hyperscale and AI customers a differentiated and compelling platform built around fundamentals, execution and scale. I look forward to working with the team to expand customer relationships and support the company’s continued growth.”

As hyperscale and AI deployments continue to accelerate, the industry is increasingly moving toward infrastructure models that prioritize integrated execution, scalability and long-term power availability. PowerBridge’s latest leadership appointment reflects how developers are positioning themselves to meet that next phase of growth.

Read the full release here.

The post PowerBridge Adds Hyperscale Sales Leadership as AI Infrastructure Demand Accelerates appeared first on Data Center POST.

Originally posted on CD-Modular.

TL;DR

• The AI Construction Bottleneck: Traditional, labor-intensive data center construction models are sometimes too slow to support the rapid scale and precision required by modern, purpose-built AI deployments.
• Full-Scale Prefabrication: To accelerate timelines, the industry is moving beyond just modularizing power and cooling by prefabricating entire IT white spaces and operational areas in controlled factory settings.
• Engineered for Extreme Density: These customized, factory-built units are specifically designed to handle AI’s heavy structural demands, sophisticated liquid cooling, and extreme power requirements that exceed 4,000 watts per square foot.
• Bypassing Labor Shortages: Moving complex infrastructure assembly off-site allows operators to avoid acute industry labor shortages, transforming months of on-site construction into a competitive advantage where units are fabricated in just weeks.

# # #

The data center industry is facing a critical inflection point as traditional, labor-intensive construction models struggle to keep pace with the demands of purpose-built AI deployments. While pouring concrete and relying on large on-site workforces remains viable for standard colocation facilities, this approach creates severe bottlenecks for modern AI environments that prioritize rapid scalability, speed, and precision. To overcome these hurdles, the industry is moving beyond simply modularizing power and cooling components to prefabricating the entire IT white space and integrated operational areas.

Modern AI workloads demand heavy structural infrastructure, sophisticated liquid cooling, and dense power delivery capable of exceeding 4,000 watts per square foot. By shifting the assembly of these complex IT environments to controlled factory settings, organizations can drastically reduce their reliance on on-site labor while ensuring consistent quality and significantly faster deployment cycles. This turnkey approach allows fully customized modular units to be fabricated in a matter of weeks, offering a competitive advantage over traditional, prolonged construction timelines and actively mitigating the impacts of acute industry-wide labor shortages.

To continue reading, please click here.

The post How Prefabrication is Solving the AI Data Center Bottleneck appeared first on Data Center POST.

TL;DR

• The Dominance of Air Cooling: Despite the growing adoption of liquid cooling, approximately 80% of data centers worldwide still rely on air as their primary cooling method, making precise environmental control essential for managing increasingly complex workloads.
• The Massive Cost of Inaccuracy: A minor temperature deviation of just 0.5°C in a typical 10 MW data center can waste more than $800,000 in cooling energy over ten years, representing a potential $805 million annual loss across the global industry.
• Compounding Operational Risks: When environmental sensors provide inaccurate data, cooling systems either overcompensate, leading to significant energy waste and inflated operating costs, or risk overheating, which threatens equipment reliability and causes costly downtime.

# # #

Air cooling still underpins most data center operations. Even as liquid and hybrid solutions gain traction, roughly 80% of the world’s data centers still rely on air as their main cooling method, underpinning the importance of precise environmental control. With data center workloads growing in complexity and density, maintaining reliable environmental conditions has never been more critical.

As operators strive for higher efficiency and sustainability, small environmental errors can quietly drive significant energy waste and cost. Even minor inaccuracies can magnify in large, high-power environments.

A temperature deviation of just 0.5°C in a typical 10 MW air-cooled data center can result in more than $800,000 in wasted cooling energy over ten years. Across the global installed base of roughly 12,000 data centers, correcting this half-degree error could prevent approximately $805 million in unnecessary energy consumption each year. These figures demonstrate that what seems like a minor measurement difference can translate into substantial financial and energy impacts.

Why Measurement Accuracy Matters

Cooling systems respond to the environmental readings they receive. Precise measurements allow operators to maintain optimal setpoints while ensuring safe conditions for critical IT equipment. When sensors provide inaccurate data, systems may overcompensate, leading to overcooling, increased energy use and higher operating costs. On the opposite end of the spectrum, consistent and accurate readings are essential in preventing overheating, supporting long-term reliability and minimizing the risk of costly downtime.

High-accuracy monitoring is the foundation for operational efficiency. The ideal solution combines precise temperature and humidity sensing with the ability to track multiple parameters, such as dew point and carbon dioxide, on the same platform.

For example, Vaisala Origo, a next-generation modular measurement platform, illustrates how a modular, high-accuracy measurement system can address these challenges. The platform provides ±0.1°C temperature accuracy and ±1 % relative humidity accuracy, with support for multiple environmental parameters through interchangeable probes. Systems like this demonstrate the type of precision and flexibility needed to manage complex environments effectively.

Operational Implications

The consequences of even small errors extend beyond energy costs. Data centers currently account for roughly 1.5 percent of global energy consumption, and demand is expected to reach just under 3% by 2030, with cloud services, AI workloads and expanding digital infrastructure. Small inaccuracies can quietly drive energy waste, reduce efficiency and increase operating expenses. Addressing the half-degree problem is a practical step toward improving operational efficiency and sustainability.

In mission-critical operations, precision matters. Even a half-degree difference in environmental measurement can have cumulative effects on energy use, costs and equipment reliability. Facilities that prioritize accurate monitoring, using modular, high-accuracy systems that track multiple environmental parameters, can realize meaningful efficiency gains while ensuring operational stability. As a result, small improvements in measurement accuracy can translate into large energy savings and more reliable operations.

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About the Author

Kelly King is a Business Development Manager at Vaisala and has 10+ years of experience across technology, security and data center environments. She helps customers apply Vaisala’s industry-leading environmental measurement solutions to modern data centers and combines strong technical understanding with commercial acumen to build strategic customer relationships and deliver practical, scalable solutions.

The post Why A Half-Degree Error is Quietly Costing Data Centers Millions appeared first on Data Center POST.

TL;DR

• The Blind Spot of Standard Monitoring: Traditional infrastructure management relies on temperature and flow rates to confirm circulation, which completely misses the internal chemical health of the fluid until physical damage to cold plates or heat exchangers is already underway.
• The Limits of Periodic Testing: Relying on quarterly or biannual lab testing is insufficient because intense AI workloads can degrade coolant within weeks, and isolated lab snapshots fail to capture rapid degradation trends or brief, damaging contamination events.
• The Shift to Predictive Analytics: By continuously tracking real-time indicators like pH, conductivity, and turbidity, predictive systems can detect the early “fingerprints” of failure, such as active metal dissolution, allowing operators to transition from reactive emergencies to condition-based planning.
• Protecting Hardware and Warranties: Implementing predictive coolant health monitoring prevents costly GPU downtime, extends hardware lifespan, and serves as a vital warranty shield by providing OEMs with continuous proof that fluid chemistry remained within required specifications.

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Why liquid-cooled AI infrastructure needs predictive analysis of fluid condition, not just temperature and flow monitoring.

As direct-to-chip liquid cooling becomes standard for GPU clusters that are pushing rack densities far beyond traditional air-cooling limits, one critical reliability layer remains underdeveloped: the health of the coolant itself. Operators need to move from periodic coolant checks to predictive fluid health monitoring that detects early degradation before it becomes corrosion, clogging, thermal throttling, or unplanned downtime.

Coolant Failure Is Usually Gradual, Not Sudden

In liquid-cooled environments, catastrophic failures rarely begin as thermal events. They begin as chemistry problems that eventually become thermal problems. Performance is lost gradually through small, compounding inefficiencies. Whether the fluid is a water-glycol mix with corrosion inhibitors or a treated water loop, degradation follows a predictable pattern. Early chemical shifts, such as pH drift, rising conductivity, or inhibitor depletion, appear long before physical symptoms like scale formation, galvanic corrosion, or biofouling become visible.

In high-density AI clusters, where cold plate channels can be extremely narrow, even minor fluid chemistry changes invite microscopic scaling, biofilm, and particulate shedding. These forces accelerate flow restrictions and create hot spots. The difficulty is that these early indicators are invisible to standard data center infrastructure management tools. Most monitoring stops at supply and return temperatures, flow rate, and pressure differential. Those parameters confirm that coolant is circulating, but they say nothing about the fluid’s internal condition. An operator can have perfect thermal readings while the coolant inside the loop slowly becomes corrosive. By the time temperature anomalies appear, physical damage to cold plates or heat exchangers may already be underway.

Why Periodic Lab Testing Falls Short

Many facilities operate their cooling loops like driving a high-performance vehicle with no dashboard gauges, relying only on a red warning light that illuminates after the engine has seized. By the time Building Management System (BMS) alarms fire for supply temperature or pump failure, the damage to the GPUs is already done.

Today, many operators rely on pulling coolant samples and sending them to a lab once or twice a year. This is better than no testing at all, but it carries significant blind spots. AI training workloads can stress coolant thermally and chemically within weeks. A six-month gap between lab reports can easily miss the entire degradation curve of a fluid that turns problematic in under three months.

Lab analysis also provides only a single snapshot. It cannot track the rate of change, detect brief contamination events, or correlate chemical shifts with specific GPU workloads. A short pH excursion caused by a mismatched top-up fluid might self-correct, but the momentary corrosive window can still etch cold plate surfaces. Without trended data, operators cannot link cause to effect, so root causes remain hidden and recurrence is likely.

The Shift to Continuous, Predictive Monitoring

To combat this gradual performance drift, the next reliability layer is continuous coolant health monitoring paired with predictive maintenance for liquid cooling. Instead of waiting for a quarterly lab report, operators can track key parameters, such as pH, conductivity, and inhibitor levels, in near real time. More advanced monitoring adds particle counting, turbidity sensing, and early corrosion indicators to catch problems at their very start.

When this sensor data feeds into predictive models, the system learns to recognize the fingerprints of failure from the data stream. For example, a slow, steady rise in conductivity coupled with a slow drop in pH over 72 hours is not random noise – it is the active signature of metal dissolving into the fluid. A spike in turbidity without a corresponding pressure change may point to biological activity, particulate buildup, or another fluid condition that requires investigation. By recognizing these deterministic signals, the system extrapolates the trajectory and calculates the moment of impact, shifting the maintenance strategy from reactive fire drills to condition-based planning.

What Predictive Coolant Health Means for Reliability

For AI data centers, where a single GPU node failure can idle many others and delay

large-scale training runs, the cost of coolant-related failure is severe. Corroded cold plates must be replaced. Clogged micro-channels require aggressive flushing or component swap-out. Unplanned downtime cascades through service level agreements. Predictive coolant health directly targets these risks at the source.

It also extends hardware lifespan and acts as a critical warranty shield. OEMs increasingly require proof that coolant chemistry stayed within specification throughout the hardware’s life; continuous monitoring provides a stronger operating record. Keeping the fluid clean keeps the cooling system efficient and focuses the power bill on compute.

Predictive Coolant Health: An Emerging Reliability Layer

Predictive coolant health is not just another maintenance task. It is an emerging reliability layer for liquid-cooled AI infrastructure. As GPU clusters become denser and cooling loops become more complex, operators will need systems that can analyze fluid condition over time, identify early degradation patterns, and forecast when coolant health is moving outside safe operating limits. This shift from reactive sampling to continuous, predictive analysis of liquid health represents the next maturity curve for data center cooling reliability.

The Future Is Predictive Liquid Health

As liquid cooling matures from a niche high-performance computing solution to standard AI infrastructure, the supporting practices must grow more sophisticated. Thermal management came first. Leak prevention came second. Now, predictive coolant health must become the third pillar of liquid cooling reliability.

This does not require replacing existing coolant distribution units or loops. It requires adding a layer of chemical and electrochemical awareness, connected to analytics, that can catch gradual degradation before it becomes catastrophic. For operators planning the next wave of AI deployment, establishing essential maintenance practices for direct-to-chip cooling systems and building coolant health monitoring into liquid-cooled infrastructure from day one is a practical step toward more predictable operations and longer asset life. Coolant is not just a consumable. It is an operating condition that directly affects AI infrastructure reliability.

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About the Author

Rupesh Mainali is a Senior Member of Technical Staff at Reliability Engine, where he focuses on predictive analysis of liquid health for liquid-cooled AI data centers. His work spans coolant health monitoring, loop behavior, and early degradation signals in direct-to-chip cooling infrastructure. To learn more, follow Reliability Engine on X and LinkedIn.

The post Predictive Coolant Health: The Missing Reliability Layer in AI Data Centers appeared first on Data Center POST.

TL;DR

• Subsea infrastructure resilience, cable security, and operational readiness remained key priorities as operators evaluate how to protect critical communications infrastructure and support growing global connectivity demands.
• Investment in new cable systems, network expansion, and long-term infrastructure planning continues to accelerate as AI workloads, cloud adoption, and international data traffic drive bandwidth growth.
• Governments, operators, and infrastructure providers are placing greater emphasis on policy coordination, resilience planning, and public-private collaboration as submarine networks become increasingly strategic assets.
• The subsea, cloud, fiber, and data center ecosystems are becoming more interconnected, creating new opportunities for collaboration across the global digital infrastructure landscape.

# # #

Submarine Networks EMEA 2026, held May 27–28 in London, brought together leaders from across the subsea, telecommunications, cloud, and digital infrastructure sectors. Throughout the event, operators, policymakers, infrastructure providers, and technology companies examined how rising bandwidth demand, artificial intelligence, and evolving geopolitical considerations are shaping the future of global connectivity.

Subsea infrastructure resilience emerged as a major theme throughout the conference. Tansy McCluskie, Deputy Director for Maritime Security at the UK Department for Transport, discussed the growing importance of protecting submarine cable systems as governments and operators respond to rising geopolitical concerns, physical infrastructure risks, and increasing dependence on global digital connectivity. Conversations throughout the session focused on strengthening resilience strategies, improving monitoring capabilities, and supporting the long-term security of critical communications infrastructure. Conversations examined how governments and industry stakeholders are strengthening resilience strategies, improving monitoring capabilities, and preparing for increasing geopolitical and operational risks.

As global bandwidth demand continues to increase, long-term infrastructure investment remains a priority across the subsea sector. Steve Holden, Chairman of ESCA and Network Operations Engineer Infrastructure (Subsea) at Meta, discussed the future of submarine cable systems and the planning required to support continued network growth. The session highlighted the importance of maintenance readiness, route diversity, and industry coordination as operators prepare for rising traffic demands driven by cloud adoption and AI workloads.

Policy and regulatory considerations also played an important role throughout the event. Grace Koh, Vice President, Government Relations, Legal at Ciena, examined how policymakers and industry leaders are working together to address regulatory challenges and strengthen collaboration around critical communications infrastructure. Discussions focused on the increasing strategic importance of submarine cable systems and the need for coordinated approaches to support future network expansion.

Regional connectivity growth and international infrastructure development remained important topics. Maja Summers, Director, Strategic Accounts and Network Solutions at WIOCC Group, explained how operators are expanding connectivity opportunities across emerging and established markets. Conversations explored infrastructure investment priorities, regional interconnection strategies, and the role submarine networks play in supporting broader digital transformation initiatives.

Beyond the conference program, Submarine Networks EMEA continued to serve as a meeting point for cable operators, investors, infrastructure providers, technology companies, and policymakers exploring partnerships and future growth opportunities across the subsea ecosystem. Assured Communications participated as a sponsor and exhibitor, reinforcing its continued engagement in subsea communications, infrastructure strategy, and mission-critical connectivity initiatives.

Submarine Networks EMEA is expected to remain an important forum for conversations around cable deployment, infrastructure resilience, network security, and the long-term future of global connectivity. As AI adoption accelerates and international bandwidth demand continues to increase, operators, policymakers, and infrastructure providers face growing pressure to strengthen communications networks while planning for future scalability. Submarine Networks EMEA will return to London, June 15–16, 2027. Additional information on the 2027 event can be found on the official Submarine Networks EMEA website.

The post Submarine Networks EMEA 2026 Examines the Next Phase of Global Connectivity and Subsea Infrastructure Growth appeared first on Data Center POST.

TL;DR

• Critical Cybersecurity Vulnerability: A new report reveals that 27% of the top 100 U.S. data centers fail to enforce basic email authentication (DMARC), leaving this vital infrastructure highly exposed to domain spoofing and phishing attacks.
• Systemic Infrastructure Risk: These widespread security gaps present a major systemic threat given the immense scale of the sector, which currently encompasses over 4,500 active U.S. facilities and more than 700 additional sites under construction.

# # #

As cyber threats increasingly target critical infrastructure, a new analysis from cybersecurity firm Red Sift exposes major email security weaknesses across the nation’s largest data center operators. Despite powering the U.S. digital economy, more than a quarter (27%) of the top 100 data centers fail to enforce basic email authentication, leaving the door wide open to domain spoofing and phishing.

The review assessed the top 100 U.S. data centers’ use of core protections like DMARC (Domain-based Message Authentication, Reporting, and Conformance), the frontline defense against email impersonation. The findings signal systemic risk:

Key findings:

• 27% lack enforcement: Policies set to “none” or left unconfigured, creating widespread spoofing exposure across critical infrastructure.
• 10% have no DMARC record at all: The highest-risk category, with zero protection against impersonation attacks.
• Just 6% use the key brand standard BIMI: Meaning 94% of data center brands lack visual inbox verification, making it far easier for attackers to mimic trusted senders.

The gaps are especially alarming given the sector’s scale and strategic importance. The U.S. now hosts more than 4,500 active data centers consuming roughly 176 TWh annually, roughly 4.4% of total U.S. electricity with more than 700 additional facilities under construction nationwide. Virginia alone accounts for over 665 sites, underscoring how concentrated and exposed this critical infrastructure backbone has become.

# # #

About the Author

Brian Westnedge leads alliances for Red Sift, an integrated cloud email and brand protection platform that automates BIMI and DMARC processes, making it easy to identify and stop business email compromise, and securing domains from impersonation to prevent attacks. He has worked in the DMARC space since its inception, has 20 years of experience in email deliverability, security and authentication.

The post New Report: Over One Quarter of Top U.S. Data Centers Lack Email Security Protections to Block Spoofing Attacks appeared first on Data Center POST.

TL;DR

• Explosive Market Growth: Driven by the rapid expansion of AI, cloud platforms, and high-density computing, the global data center refrigerant market is projected to reach $1.62 billion by 2035.
• The Push for Sustainability: Stringent environmental policies and global climate agreements are forcing operators to abandon traditional high-global-warming-potential (GWP) refrigerants in favor of low-emission, energy-efficient alternatives.
• Hyperscale and U.S. Dominance: Accounting for 40% of the market, hyperscale data centers are fueling the most rapid growth, particularly in the U.S., as major tech providers invest heavily in advanced thermal management to handle unprecedented AI workloads.

# # #

The global data center refrigerant market, valued at USD 633 million in 2025, is projected to experience robust growth, reaching an estimated USD 1.62 billion by 2035. According to newly released industry data, the market is set to expand at a compound annual growth rate (CAGR) of 9.6% over the forecast period of 2]026 to 2035.

This significant market transformation is being driven by the rapid expansion of global digital infrastructure, including cloud platforms and hyperscale facilities. As artificial intelligence (AI), big data analytics, and high-density computing continue to scale, the computational workloads are generating unprecedented thermal management requirements. Data center operators are increasingly turning to advanced refrigerants to ensure optimal energy performance, operational stability, and efficient heat control.

Sustainability and Regulatory Shifts Fuel Innovation

The industry is undergoing a major structural shift, moving away from traditional high-global-warming-potential (GWP) refrigerants toward low-emission, energy-efficient alternatives. Spurred by global climate agreements and stringent regional environmental policies, data center operators are prioritizing emission reductions, enhanced leak detection, and advanced lifecycle management to meet rigorous sustainability mandates while simultaneously lowering operating costs.

Market Segmentation Highlights: HFOs and Hyperscale Lead the Way

• HFO Refrigerants: Hydrofluoroolefins (HFOs) dominated the market in 2025 with a 67.7% share and are expected to grow at a CAGR of 10.2% through 2035. Their significantly lower global warming potential and high cooling efficiency make them the preferred choice for next-generation facilities amid the global phase-out of high-GWP options.
• Hyperscale Data Centers: Accounting for a 40% market share in 2025, the hyperscale segment is projected to grow at a rapid 10.4% CAGR from 2026 to 2035. Operated by major cloud and technology providers, these massive facilities require highly efficient cooling systems to manage the substantial heat loads generated by advanced AI and digital services.

U.S. Market Remains a Powerhouse

In 2025, the U.S. Data Center Refrigerant Market generated USD 176.3 million, holding a commanding 79% share of its regional landscape. U.S. growth is heavily supported by continuous investments in hyperscale expansions by leading tech firms, a surge in AI applications, and strict energy efficiency regulations driving the transition toward modern, low-GWP thermal management technologies.

Competitive Landscape and Strategic Initiatives

Key global players driving innovation in the market include Daikin Industries, Linde plc, Honeywell, Chemours, AGC, Dongyue, Zhejiang Juhua, Arkea, and Sinochem. These industry leaders are significantly increasing investments in research and development to enhance refrigerant efficiency, thermal stability, and high-density computing compatibility. Furthermore, market players are actively expanding production capabilities in high-demand regions and forming strategic partnerships with cooling system manufacturers to integrate next-generation, compliance-driven refrigerant solutions.

# # #

About the Author

Kanthamsetty Sri Lakshmi is a journalism graduate who turned her passion for writing into a thriving profession by curating insightful and well-researched articles across multiple sectors. She has established herself as a versatile content creator, focusing on the latest technologies, industry trends, and emerging business landscapes. Sri Lakshmi produces highly engaging and informative pieces. She continues to explore thought leadership topics and looks forward to publishing articles that provide readers with deep insights, actionable knowledge, and a forward-looking understanding of evolving markets and innovation.

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TL;DR

• Open house announced: Duos Edge AI will host a Dumas open house on June 16 to showcase its newly operational Edge Data Center.
• Infrastructure in action: The facility delivers critical IT load capacity supporting high-performance compute, AI workloads, network infrastructure, and disaster recovery solutions.
• Regional connectivity boost: The project strengthens digital infrastructure in the Texas Panhandle and expands Duos Edge AI’s modular edge footprint.

# # #

Duos Technologies Group Inc. (Nasdaq: DUOT), through subsidiary Duos Edge AI, Inc., has announced the deployment of a newly operational Edge Data Center in Dumas, Texas, bringing advanced data center capabilities to an underserved Panhandle market with a compact footprint and zero operational water consumption.

The deployment serves as a regional hub for real-time data processing, enabling advanced educational tools, improved connectivity, and dependable infrastructure for Dumas ISD’s 4,300 students, as well as healthcare providers, carriers, enterprises, and the broader regional economy. Built to scale alongside community needs, the EDC supports long-term digital growth and economic development across the Panhandle.

“The Panhandle region has been crucial to Duos Edge AI’s journey as we deploy facilities across Texas with a specific focus on rural areas,” said Doug Recker, CEO of Duos Edge AI and Duos Technologies Group,Inc. “Our Dumas facility is already playing a key role in expanding access to advanced computing resources and driving growth throughout the region.”

Community leaders, education stakeholders, and industry partners are invited to tour the site at the open house on Tuesday, June 16, 2026, from 9:00 AM to 11:00 AM CDT at 421 W. 4th St, Dumas, TX 79029.

To learn more about Duos Edge AI and register for the open house, visit freeevite.com/event.php?e=QNAiq7mZalRfd87nV8tMOw.

The post Duos Edge AI to Host Dumas Edge Data Center Open House appeared first on Data Center POST.

Integrating IMS, DCMA Diagnostics, OFCI Visibility, TIA Governance, and Executive Risk Analytics

TL;DR

• The Shift to Predictive Governance: Traditional, reactive scheduling is inadequate for the complexity of multi-billion-dollar hyperscale AI data centers; operators must adopt a system of predictive, portfolio-level schedule governance.

• Managing Critical Constraints: Major project bottlenecks, specifically long-lead Owner Furnished Contractor Installed (OFCI) equipment and commissioning capacity, must be integrated into the schedule early to prevent late-stage conflicts and supply chain misalignments.

• Proactive Diagnostics and Delay Tracking: Instead of merely reporting past issues, operators should utilize DCMA 14-point diagnostics to continuously measure schedule health and enforce standardized Time Impact Analysis (TIA) for the consistent evaluation of delays and claims.

# # #

The rapid expansion of artificial intelligence infrastructure has transformed data center construction from a traditional capital project environment into a mission-critical delivery ecosystem. Hyperscale AI data centers are no longer isolated construction programs; they are capacity-enabling infrastructure platforms supporting cloud computing, machine learning workloads, enterprise applications, and national digital competitiveness.

As project portfolios grow in size and complexity, traditional schedule management practices are no longer sufficient. Data center delivery teams must manage overlapping construction sequences, long-lead OFCI equipment, commissioning readiness, power availability, contractor performance, claims risk, and executive reporting requirements across multiple campuses and regions.

In this environment, schedule governance must evolve from reactive reporting into predictive portfolio-level decision support.

The Challenge: Traditional Scheduling Is Too Reactive

Many large infrastructure programs still rely heavily on periodic schedule updates, milestone reports, and contractor narratives. While these tools remain necessary, they often identify risk after the schedule has already deteriorated.

Common issues include:

• Open-ended activities that weaken logic integrity
• Excessive hard constraints that distort the critical path
• Long-duration construction activities that reduce progress visibility
• Inconsistent General Contractor schedule integration into the Integrated Master Schedule
• Misalignment between OFCI supplier dates, need-by dates, and required-on-jobsite milestones
• Inconsistent Time Impact Analysis submissions
• Lack of standardized reason codes for delay tracking
• Limited portfolio-level visibility into schedule health trends

For a single project, these issues may appear manageable. Across a multi-billion-dollar hyperscale portfolio, they can create systemic delivery risk.

The solution is not simply “better scheduling.” The solution is integrated schedule governance.

1. Integrated Master Schedule Governance Must Be Standardized

The Integrated Master Schedule should serve as the single source of truth for executive milestone visibility, contractor coordination, supply chain alignment, commissioning readiness, and risk escalation.

However, IMS governance often breaks down when General Contractor schedules are not integrated consistently. Common problems include:

• Data dates that do not align between GC schedules and owner IMS schedules
• Activity IDs that do not follow Division 01 requirements
• Milestone logic that is linked incorrectly or not linked at all
• Inconsistent calendars and coding structures
• Missing relationships between procurement, construction, and commissioning activities

A strong IMS governance framework should include:

• Standard Activity ID requirements
• Required WBS structure
• Data date alignment rules
• Schedule coding standards
• Calendar governance
• Milestone integration requirements
• Baseline review checklists
• Contractor update expectations
• Portfolio-level reporting requirements

When the IMS is standardized, leadership can compare schedules across projects, identify recurring bottlenecks, and make better portfolio decisions.

2. DCMA 14-Point Diagnostics Should Be Used as a Governance Tool

DCMA 14-point analysis is often treated as a compliance exercise. In reality, it should be used as a scheduled health governance system.

Key metrics such as missing logic, open-ended activities, high lag, hard constraints, excessive duration, invalid dates, and logic density provide early signals of schedule reliability.

For example:

• A high percentage of open-ended activities may indicate weak schedule logic.
• Excessive hard constraints may artificially control milestone dates.
• High lag usage may hide true activity dependencies.
• Excessive durations may reduce the ability to measure progress accurately.
• Poor logic density may indicate insufficient schedule sequencing.

When these metrics are tracked consistently across a portfolio, leadership can identify which projects have reliable schedules and which schedules require corrective action before milestone risk escalates.

The goal is not to produce a perfect DCMA score. The goal is to improve confidence in the schedule as a decision-making tool.

3. OFCI Equipment Must Be Integrated Into the Schedule Earlier

Owner Furnished Contractor Installed equipment is one of the most critical schedule drivers in data center construction. Generators, switchgear, UPS systems, chillers, CRAH units, and other long-lead equipment can determine whether construction, commissioning, and turnover milestones remain achievable.

A common scheduling gap occurs when teams track either:

• supplier confirmed delivery dates, or
• required-on-jobsite dates,

but not both.

This creates limited visibility into whether equipment will arrive too early, too late, or at the wrong point in the construction sequence.

A stronger approach is to integrate three key milestones:

By comparing these dates, project teams can identify:

• early delivery storage risk,
• late delivery schedule risk,
• commissioning readiness exposure,
• installation sequence conflict,
• and procurement escalation needs.

This approach allows supply chain risk to become visible inside the schedule instead of being managed separately from project controls.

4. Time Impact Analysis Requires Standardization

Time Impact Analysis is one of the most important tools for evaluating delay events, yet it is often inconsistently applied.

Common issues include:

• contractors using different TIA formats,
• incomplete fragnet logic,
• unclear delay narratives,
• missing contemporaneous documentation,
• inconsistent reason codes,
• delayed submissions beyond contract timelines,
• and weak alignment between TIA findings and schedule updates.

A standardized TIA process should define:

• required submission timeline,
• fragnet requirements,
• narrative expectations,
• baseline schedule reference,
• impacted activity logic,
• reason code categories,
• contract review workflow,
• and approval or rejection criteria.

When standardized across projects, TIA governance improves claims evaluation, contractor accountability, and consistency in delay analysis.

5. KPI Dashboards Must Translate Schedule Data Into Executive Decisions

Project controls teams often produce large volumes of schedule data, but executive leaders need decision-ready information.

Effective dashboards should answer practical questions:

• Which milestones are slipping?
• Which projects have poor schedule health?
• Which contractors are repeatedly submitting weak schedules?
• Which OFCI equipment presents the highest risk?
• Which delays are weather-related, procurement-related, design-related, or contractor-caused?
• Which projects require recovery planning?
• Which risks require executive escalation?

Useful executive schedule dashboards may include:

• Schedule Performance Index
• Planned vs. Actual progress curves
• Milestone variance trends
• DCMA schedule health scores
• Risk log summaries
• TIA log with reason codes
• OFCI supplier date vs. ROJ variance
• commissioning readiness indicators
• recovery plan status

The value of a dashboard is not its appearance. Its value is whether leadership can make faster, better decisions from it.

6. Commissioning Must Be Treated as a Portfolio Constraint

In hyperscale data center delivery, commissioning is not simply a late-stage project activity. It is a portfolio-level capacity constraint.

Commissioning schedules depend on:

• construction completion,
• system turnover,
• equipment readiness,
• utility availability,
• testing resources,
• vendor support,
• integrated systems testing,
• and operational acceptance.

When commissioning is not integrated early into the IMS, project teams may discover conflicts too late.

Portfolio-level commissioning governance should include:

• commissioning milestone integration,
• system turnover sequencing,
• commissioning resource planning,
• cross-project team utilization analysis,
• readiness dashboards,
• and early warning indicators.

In large portfolios, optimizing commissioning resources across multiple projects can improve schedule performance and reduce idle time, bottlenecks, and turnover delays.

7. Division 01 Specifications Are the Foundation of Schedule Governance

Division 01 scheduling specifications define the rules of schedule management. If they are vague or inconsistent, each General Contractor may interpret requirements differently.

Strong Division 01 schedule language should clearly define:

• project naming conventions,
• Activity ID structure,
• WBS requirements,
• required calendars,
• data date rules,
• retained logic settings,
• allowable constraints,
• activity code requirements,
• weather day usage,
• TIA procedures,
• recovery schedule requirements,
• baseline review requirements,
• and weekly reporting expectations.

Standardized Division 01 requirements create consistency across campuses, improve contractor accountability, and reduce ambiguity in delay discussions.

8. Predictive Governance Creates Measurable Value

The greatest value of schedule governance is not reporting what happened. It is identifying what is likely to happen next.

A predictive schedule governance framework combines:

• IMS integration,
• DCMA diagnostics,
• OFCI variance tracking,
• TIA trend analysis,
• EVM KPIs,
• risk logs,
• commissioning readiness indicators,
• and executive escalation protocols.

When implemented effectively, this framework can:

• reduce milestone slippage,
• improve schedule health,
• reduce storage costs,
• improve contractor accountability,
• reduce claims exposure,
• improve commissioning readiness,
• and support faster executive decision-making.

For hyperscale AI data center portfolios, this is no longer optional. It is essential.

Conclusion

AI infrastructure delivery requires a new level of schedule governance maturity. Traditional project-level schedule tracking is not enough for multi-billion-dollar hyperscale portfolios where construction delays can affect capacity availability, operational readiness, and digital infrastructure growth.

The future of data center project controls will be defined by integrated, predictive, and portfolio-level scheduling systems.

The most effective organizations will be those that can connect construction schedules, supply chain data, commissioning readiness, contract requirements, and executive risk analytics into one coherent governance framework.

In hyperscale AI infrastructure delivery, the schedule is not just a project control tool.

It is a strategic operating system for mission-critical delivery.

# # #

About the Author

Pradeep Juturu is a PMI-certified Project Controls and Scheduling leader with 15+ years of experience delivering complex capital programs across hyperscale Data Centers, AI infrastructure, smart grid modernization, utility technology deployment, transportation infrastructure, and healthcare construction. He has a proven record leading Integrated Master Scheduling, Primavera P6 governance, DCMA 14-point diagnostics, Time Impact Analysis, Earned Value Management, OFCI supply chain integration, executive dashboards, risk logs, and portfolio-level schedule optimization. At Microsoft, He led regional schedule governance for an approximately $4B Data Center portfolio.

The post Predictive Schedule Governance for Hyperscale AI Data Center Delivery appeared first on Data Center POST.

By Andre Azevedo, Founder & CEO, Hype Telecom LLC

TL;DR

• The True AI Bottleneck: While capital and power receive the most attention, the defining constraint for the massive data center buildout is a projected shortfall of 340,000 qualified technicians by the end of 2026.
• The Limits of Traditional Hiring: The industry cannot simply recruit its way out of this gap; traditional apprenticeships take years, and the existing pool of fully qualified talent is vastly insufficient to staff multiple parallel megaprojects.
• A Scalable Training Solution: To rapidly qualify workers without sacrificing quality, operators must deploy centralized standard operating procedures, rely on local teams rather than labor arbitrage, and accelerate learning through structured knowledge transfer that pairs new hires with seasoned experts on live deployments.

# # #

Most coverage of the AI infrastructure buildout concentrates on the wrong constraints. Capital is not the binding factor: the hyperscaler capex cycle now driving this expansion is supporting a data center buildout valued at approximately $700 billion in 2026. Power has received considerable attention, and justifiably so; BloombergNEF projects U.S. data center demand could reach 106 gigawatts by 2035, a 36% upward revision in only seven months. Chips and permitting have likewise been thoroughly examined.

The constraint that will, in practice, determine which 2026 commissioning dates hold and which slip is none of those. It is the availability of qualified personnel, the technicians who pull cable, splice fiber, terminate copper, dress racks, commission equipment, and remain on site through the night when something fails. By the end of 2026, the U.S. data center industry is projected to be short approximately 340,000 of them, even as the broader buildout opens an estimated 650,000 positions across construction and operations.

The CEO of Randstad,  the world’s largest recruitment firm, stated the matter directly on CNBC earlier this year: the real constraint on global technology growth is not chips, energy, or capital, but the severe scarcity of the specialized talent required to build it. The most recent Uptime Institute survey reflects this directly. Fifty-three percent of operators report difficulty finding qualified candidates, up from 38% in 2018. A separate Uptime construction survey found 52% of firms reporting staffing-driven disruptions, against 43% the prior year. Forty-five percent of contractors experienced at least one project delay in the past year attributable to staffing constraints.

This is not a forecasting exercise; it is a structural gap, and it widens with every quarter. The question that matters is not where to find 340,000 people who already have the skills. It is how to qualify them faster than the traditional pipeline allows, and how to do so without sacrificing the consistency that hyperscale work demands.

Why hiring alone will not close the gap

The reflex response to a labor shortage is to recruit harder. In this sector, that reflex meets a hard ceiling. A journeyman electrician requires four to five years of training. A commissioning engineer with hyperscale experience requires longer. Approximately one in four tradespeople globally is at or near retirement age. The pool of fully qualified, immediately deployable technicians is not large enough, and it cannot be enlarged on the timeline the buildout requires.

The shift in scale makes this concrete. A decade ago, peak crews at major data center facilities were typically capped at around 750 workers. DataBank’s Red Oak campus is expected to reach a peak between 4,000 and 5,000 workers in early 2026. The arithmetic does not hold when the industry must staff dozens of such megaprojects in parallel, drawing from a finished-talent pool that simply does not contain those numbers.

If the qualified workforce cannot be hired into existence quickly enough, it has to be trained into existence quickly enough. That reframes the problem. The constraint is not a recruiting problem; it is a training-throughput problem. And training throughput is something an operator can actually engineer.

The hidden problem: inconsistency across geographies

There is a second constraint that receives even less attention than the first. As field-services work spreads across regions — Northern Virginia, Dallas-Fort Worth, Greater Phoenix, and increasingly across borders into Latin America and Europe — the standard to which the work is executed begins to drift. A splice performed in one metro is documented one way; the same task in another metro is documented differently. Acceptance criteria are interpreted locally. Photo evidence varies. Labeling conventions diverge.

For a hyperscale customer, that drift is unacceptable. A hyperscaler enforces the same build standard in every facility it operates, and it expects its partners to do the same. An operator that cannot guarantee identical execution in every geography it serves is not a scalable partner; it is a collection of local teams that happen to share a name.

So the real objective is twofold: qualify new technicians faster, and qualify them to a single global standard. Those two goals are usually treated as a trade-off: move fast or maintain consistency. They do not have to be.

Centralized standards, local teams, structured knowledge transfer

The model that resolves the trade-off has three components, and none of them involves moving labor across borders.

• Centralized standards. SOPs, acceptance criteria, labeling conventions, safety procedures, and photo-evidence requirements are defined once, centrally, and applied everywhere. The standard does not belong to a region; it belongs to the company. A technician in São Paulo and a technician in Phoenix execute against the identical specification.
• Local teams. The work in each geography is performed by technicians based in that geography: recruited, employed, and developed locally, under local labor and licensing frameworks. This is not labor arbitrage. It is local capacity, held to a global standard.
• Structured knowledge transfer. This is the component that actually accelerates qualification. New technicians are paired directly with experienced ones on live work, rather than being trained in isolation and released. That pairing is supported by a documented body of procedure, written SOPs and instructional video covering how each activity is performed the company’s way. The senior technician carries the company’s standard; the documentation makes that standard explicit and repeatable; the junior technician absorbs both at once, on real deployments.

The effect is that a new technician does not enter the field as an unknown quantity. They enter alongside someone who already embodies the standard, with reference material that removes ambiguity about how the work should be done. The ramp from hired to genuinely productive shortens, because the new technician is never learning the standard and the job separately — they learn them together. Operators that run this model also tend to see stronger retention, because technicians developed inside a clear system, with visible support, are less likely to leave it.

Why this is a competitive question, not an HR question

Treating workforce development as an HR line item is the most common and most expensive mistake in this segment. A multi-trillion-dollar global data center spending cycle through 2030 will not be delivered by organizations that regard training as overhead. It will be delivered by organizations that treat training throughput as core operational capacity and as deliberately engineered as their supply chain or their project controls.

For operators and developers selecting field-services partners for the 2026–2027 wave of activations, three questions are worth posing before the next site goes vertical:

1. Does the partner execute to a single documented standard across every geography, or does quality depend on which local team happens to be assigned?
2. How does the partner qualify new technicians? Is it through structured pairing with experienced staff and documented procedure, or by hiring finished talent that the market cannot actually supply?
3. Is workforce development treated as a board-level capability, or as an administrative function? The answer predicts whether the partner can scale with the buildout or will become a bottleneck within it.

A global industry needs a global standard

The AI infrastructure buildout is often described as a race for power, chips, and capital. Underneath those, it is a race to qualify a workforce: fast enough to meet demand, and consistently enough to meet the standard. Those two requirements are not in tension when training is engineered properly: centralized standards make consistency portable, local teams keep the work lawful and grounded in each market, and structured knowledge transfer compresses the time from hired to capable.

The operators who treat the qualification of their workforce as a core engineering discipline will be those whose commissioning dates hold. For the remainder, the consequences will be measured not in apologies but in delayed activations, contractual exposure, and the compounding cost of every missed milestone.

# # #

About the Author

Andre Azevedo is the founder and CEO of Hype Telecom LLC, a U.S.-headquartered telecommunications infrastructure and field-services company based in Winter Park, Florida. The company supports rack-and-stack, structured cabling, fiber installation, FLM/Smart Hands, and network deployment work across more than 20 U.S. states, with affiliated operations across Brazil and Latin America and operations expanding into Europe in 2026. With more than 15 years of entrepreneurial experience and an LL.M. in International Business Law from Queen Mary University of London, Andre leads Hype Telecom’s North American expansion and its workforce-development model. Learn more at www.hypetelecom.net.

The post The 340,000-Worker Question: Why the AI Buildout Will Be Won or Lost on Training appeared first on Data Center POST.

TL;DR

• AI infrastructure planning is shifting from future strategy to immediate execution, with discussions focused on compute demand, interoperability, edge deployment, and the network requirements needed to support increasingly data-intensive workloads.
• Energy access, power availability, and long-term infrastructure resiliency emerged as critical priorities as operators, policymakers, and investors evaluate how to support rapid digital infrastructure growth while maintaining operational stability.
• Public trust, permitting, and digital infrastructure policy are becoming increasingly important to project development, reinforcing the need for stronger communication, community engagement, and collaboration between public and private stakeholders.

# # #

ITW 2026, held May 18-21 at the Gaylord National Resort & Convention Center in National Harbor, Maryland, brought together  global leaders from across the telecom, cloud, digital infrastructure, subsea network, and investment sectors.  Across keynotes, panels and networking sessions, industry stakeholders explored how artificial intelligence, infrastructure investment, energy availability and policy considerations are reshaping the future of global connectivity. Throughout the week, operators, hyperscalers, policymakers, and investors discussed strategies for adapting communications networks and digital infrastructure to support rising AI demand, increasing capacity requirements, and the continued evolution of the global digital ecosystem.

Artificial intelligence and infrastructure readiness emerged as a major focus throughout the conference. During the keynote panel “Unleashing the 3 Pillars of AI,” Arno van Huyssteen, VP Global Telecom & AI Service Provider at Nscale, examined how AI is reshaping infrastructure strategies, accelerating demand for compute and connectivity, and influencing investment decisions across telecom and digital infrastructure ecosystems. Discussions explored how operators and infrastructure providers are preparing networks to support increasingly data-intensive workloads as enterprise expectations continue to evolve.

Policy and international coordination also shaped conversations across the Digital Infrastructure Policy & Investment Summit. Anjana Modi, Acting Principal Deputy Assistant Secretary, Bureau of Cyberspace and Digital Policy at the U.S. Department of State, discussed the strategic importance of AI innovation and the role digital infrastructure plays in supporting economic competitiveness, national priorities, and long-term resiliency. Broader discussions throughout the summit focused on how governments and industry stakeholders are navigating geopolitical shifts while planning for future infrastructure growth.

Energy supply and infrastructure scaling remained important themes as demand for AI capacity continues to grow. During the panel “Investing in Energy to Power Digital Growth,” Tate Cantrell, Chief Technology Officer at VERNE, highlighted the growing need for reliable energy strategies, grid resiliency, and infrastructure planning to support increasing digital demand. Conversations throughout the session explored how operators are balancing performance expectations with long-term infrastructure readiness as AI workloads continue to expand.

Public perception and permitting challenges surrounding infrastructure deployment also became a major topic of discussion. Ilissa Miller, Founder and Chief Executive Officer of iMiller Public Relations, participated in the panel “Debunking the Data Center Misinformation Dilemma,” where she addressed the role communication, transparency, and community engagement play in navigating permitting processes and addressing misconceptions around digital infrastructure development. The session explored how public trust, land use concerns, and local engagement increasingly shape infrastructure planning and project execution.

Artificial intelligence infrastructure deployment and operational readiness were also explored during the “ITW Meetup: AI & Data Infrastructure” session. Doug Recker, CEO of Duos Edge AI, led discussions around designing fit-for-purpose AI-ready data centers and the infrastructure requirements needed to support growing enterprise demand for low-latency AI workloads. Conversations focused on deployment flexibility, infrastructure readiness, and how operators are preparing environments capable of supporting increasingly distributed AI applications.

Sustainability, operational efficiency, and responsible infrastructure planning also shaped broader agenda discussions. During the panel “Building Responsible Data Centers: Delivering Sustainable Operations at Scale,” Sriram Natarajan, Chief Technology Officer at Hypertec, examined how operators are adapting infrastructure strategies and operational models to improve efficiency while supporting continued digital growth. Discussions explored long-term sustainability planning, infrastructure resilience, and the operational considerations tied to rising compute density requirements across data center environments.

ITW is set to return on May 10-13, 2027 at the Gaylord National Resort & Convention Center in National Harbor, Maryland. Information on future events is available through the official ITW website: www.internationaltelecomsweek.com

The post ITW 2026 Highlights AI Growth, Infrastructure Strategy, and the Evolving Connectivity Ecosystem appeared first on Data Center POST.

TL;DR

• The Modern Economy’s “Oil Fields”: Data centers are the foundational engines of 21st-century prosperity; regions that embrace them will secure vital talent and investment, while those that resist risk falling behind.
• Accelerating Medical Breakthroughs: In healthcare hubs like Greater St. Louis, immense computing power is essential for processing massive biological datasets, which speeds up drug discovery and precision oncology.
• Responsible Community Development: To build public trust, data center projects must prioritize transparency and offer direct local benefits, such as investments in grid modernization and innovative utility-sharing agreements.

# # #

When oil was first discovered in Texas in the early 1900s, many people saw it as dirty, disruptive, and uncertain.  Texans were rightfully concerned about land use, industrialization, and whether the economic promises promoting the black gold breakthrough would ever materialize. Yet history proved that oil would become one of the foundational drivers of America’s global leadership.

Today, data centers occupy a similar position in our economy.

The debate surrounding the proposed Festus data center in Jefferson County, MO has revealed understandable concerns from residents about transparency, environmental impact, and energy consumption. Those concerns deserve to be heard and addressed seriously. But we must also recognize the larger reality: data infrastructure is becoming as essential to the 21st-century economy as oil fields were to the 20th.

If America intends to remain a global leader in artificial intelligence, healthcare innovation, cybersecurity, and advanced research, we can’t afford to reject the infrastructure that powers those industries.

Data centers are no longer simply warehouses full of computers. They’re the engines behind nearly every major technological breakthrough happening today. They support artificial intelligence models, advanced manufacturing, logistics systems, financial networks, and medical research. Increasingly, they will determine which sections of the country prosper economically and which are left behind.

For the greater St. Louis metropolitan area, this conversation is especially important.

For over 130 years, Greater St. Louis has positioned itself as a center for healthcare, medicine, and academic research. We’re home to world-class hospitals, universities, bioscience companies, and research institutions. The next generation of medicine, from protein synthesis and precision oncology to AI-assisted diagnostics and designer pharmaceuticals, will be facilitated by immense computing power.

Modern drug discovery requires researchers to process massive biological datasets, model protein interactions, and train increasingly sophisticated artificial intelligence systems. These breakthroughs are computationally intensive. Faster access to computing infrastructure directly accelerates the pace of discovery.

In practical terms, that means data centers can help shorten the timeline for developing new therapies, improving patient outcomes, and strengthening America’s global medical competitiveness.

Regions of America that embrace this infrastructure will attract investment, talent, and exciting transformation. Regions that reject it risk watching opportunity move elsewhere.

That doesn’t mean citizens should simply accept any data center construction project without safeguards. Responsible development matters. In fact, if Missouri wants to lead in this space, we should demand that these projects become models for how modern infrastructure can coexist with community and environmental interests.

There are reasonable solutions available.

First, large-scale data centers should be required to incorporate renewable energy offsets or long-term investments in clean energy generation. If these facilities consume significant power, they should also help expand and modernize their local energy grids.

Second, the locales that host these projects should directly benefit from them. One innovative approach would be to require utility-sharing agreements that reduce energy costs for area residents and businesses. If a data center becomes a major economic engine for a community, the people living there should share in the upside.

Third, transparency must improve. Public trust is essential. Companies and municipal governments should communicate openly about environmental impact, water use, energy demand, and long-term economic benefits before projects are approved.

The United States is entering a global competition centered around artificial intelligence, biotechnology, and advanced computing. China, Europe, and other states across America are investing heavily in digital infrastructure. Missouri has an opportunity to become part of that future rather than watching it happen elsewhere.

The truth is simple: data centers are poised to be the oil fields of the modern economy.  The cities and states that understand this reality will help shape and contribute to the next century of American prosperity.

# # #

About the Author

Dr. David Lenihan, Ph.D., J.D., MBA is the Past President and CEO of Ponce Health Sciences University in St. Louis.  He’s also the CEO/Co-Founder of Tiber Health.  His POVs on innovation, management, and entrepreneurship have been featured in Fast Company, Startups Magazine, Management Today, Forbes, Ticker News, and many more.

The post To Boost Crucial Developments in Medical Research, Here’s How Missouri’s Data Center Infrastructure Can Lead, Not Lag appeared first on Data Center POST.

Data Center Post had the opportunity to connect with Nadya Melic, Vice President Product & Marketing at FLAG, where she focuses on how global connectivity infrastructure is designed, packaged and delivered to support the way customers actually build and run digital platforms today.

Melic spent over 20 years across the telecommunications and technology sector, working across product leadership, commercial strategy and customer-facing roles. Her career has taken her through Microsoft, BT, Telstra and Vodafone Business, where she worked closely with enterprise customers, carriers and hyperscalers as their architectures evolved from early international connectivity through to today’s distributed, cloud-led environments.

She led the transition from Global Cloud Xchange to FLAG when she joined the company in 2024, and since then, her focus has been on aligning our portfolio more closely with how customers consume global infrastructure today, integrating subsea, terrestrial and data centre assets into solutions that prioritise resilience, flexibility and scale.

How did you come to your current position with FLAG?

I entered the industry at a time when engineering and network roles were still very male-dominated, and that shaped how I think about visibility, representation and long-term career progression. Early on, it became clear that success in this sector isn’t just about technical expertise but instead about understanding customers, building credibility, and learning how complex systems behave in the real world.

Across my roles at BT, Telstra and Vodafone, I worked closely with customers as their needs shifted from relatively static, hub-based networks to far more distributed, latency-sensitive environments. That experience has heavily influenced how I approach product and market strategy today. I don’t see infrastructure as a set of assets. It is something that has to adapt continuously as customer architectures evolve.

At FLAG, that perspective has been central to how we think about portfolio development and positioning, ensuring what we build is genuinely usable, scalable and aligned with where demand is actually moving.

What is FLAG’s core mission?

At FLAG, we believe connectivity is a fundamental human right, and our mission is to build the infrastructure that makes that a reality.

As demand for AI, cloud and IoT accelerates, many organisations are still constrained with fragmented networks, limited route choice and architectures that were designed around a small number of global hubs. That creates risk, limits scalability and makes it harder for customers to adapt when conditions change.

Our role is to solve this by providing carrier-neutral infrastructure with built-in path diversity and resiliency, ensuring critical data continues to flow even when the unexpected happens.

We do this by integrating subsea cable systems with terrestrial networks, connecting to edge data centres and intelligent routing, creating a more flexible network layer that supports global scale.

Ultimately, our goal is to enable customers to scale, move traffic intelligently and maintain performance even when routes, regulations or demand patterns shift.

How would you describe the current state of the global digital infrastructure market in terms of challenges and opportunities for your business?

One of the biggest challenges is that traditional connectivity models, built around fixed routes and a small number of global hubs, no longer reflect how data is created, consumed and transferred

AI-driven workloads, hyperscale data centre expansion and regional cloud growth are dramatically increasing traffic volumes, placing strain on infrastructure that wasn’t designed for this level of scale or complexity.

At the same time, geopolitical and regulatory dynamics are playing a much bigger role in network planning. Route diversity, data sovereignty and permitting constraints now directly influence where customers place capacity and how they design resiliency

From our perspective, this is also where the opportunity sits. Customers are moving away from thinking about individual assets and towards infrastructure as a platform that delivers outcomes, whether that’s predictable latency, the ability to scale quickly, or the confidence that traffic can be rerouted when conditions change.

That shift is driving demand for carrier-neutral, route-rich networks and has directly informed investments such as our dedicated fibre pair on the ECHO subsea cable, connecting this with our investments from India to Singapore creating a high-capacity route between South Asia and the US in response to customer demand for scale and resilience across that corridor.

Who do you see as your primary customer base today, and how has that evolved over the past few years?

Our customer base is primarily made up of hyperscalers, telecom carriers, as well as large enterprises and financial services companies that rely on high-performance global connectivity to operate at scale.

These organisations depend on resilient, low-latency infrastructure to support everything from cloud services to real-time data exchange across regions, including Asia, the Middle East, Europe and the USA.

What’s changed in recent years is less about who those customers are and more about how they consume connectivity. Traditionally, demand was driven by relatively linear, point-to-point traffic between major hubs. Today, customers are operating in far more distributed environments, with workloads spread across multiple regions.

As a result, we’re seeing a shift towards integrated, carrier-neutral solutions that deliver outcomes, whether that’s scalability or flexibility, rather than simply access to capacity.

There’s also growing demand from emerging markets, where improved route diversity is enabling greater participation in the global economy beyond traditional centres.

What are the top priorities or concerns you hear from your customers, and how is FLAG addressing them?

The main priorities we’re hearing from customers today centre on scale and performance. As data demand continues to surge, organisations need infrastructure that can deliver high-capacity, low-latency connectivity across increasingly complex global environments.

Many are also looking to reduce reliance on single routes or legacy hubs. Outages, congestion and geopolitical disruption are no longer hypothetical risks – they’re things customers actively plan around.

In response, we’re investing heavily in expanding and diversifying our network across high-growth corridors such as the US, India, Southeast Asia and the Middle East – while strengthening links back into Europe. This is helping us build more globally integrated connectivity options, aligned with evolving data centre footprints and changing customer expectations.

Customers don’t want to stitch together subsea, terrestrial and data centre connectivity themselves. They expect those layers to work together as one and be provided by trusted providers.

Are there emerging customer segments or industries that you see as growth areas for your business?

Demand based on hyperscale AI connectivity remains a core growth area, particularly as they expand regional availability zones and invest in new data centre hubs outside of traditional markets.

We’re also seeing strong growth from data centre operators, carriers as well as enterprises running increasingly latency-sensitive applications. These organisations are looking for predictable performance and direct, resilient connectivity between regions to support workloads such as AI, real-time services and large-scale data replication.

From a geographic perspective, markets like India are becoming critical digital hubs, driven by both local demand and their role as aggregation points within global networks. This is creating opportunities to support a broader mix of regional players, as well as global organisations expanding into high-growth markets.

How are you aligning FLAG’s strategy to address sustainability and regulatory requirements in the coming years?

At FLAG, sustainability and regulatory alignment are key as we scale to meet growing global digital demand.

From an environmental perspective, we’re driving measurable reductions in emissions through high-efficiency optical platforms that reduce energy consumption per transmitted bit, alongside optimised network architecture that minimises failover inefficiencies.

This has already helped reduce emissions from 19,656 tCO₂e to 17,768 tCO₂e. We also lower embedded carbon by focusing on reductions on our fully owned and newly invested route-diverse subsea network, avoiding the duplication often seen in fragmented models.

Transparency and accountability are equally important. We provide full GHG Protocol-aligned reporting across Scope 1-3 emissions, enabling customers to better understand and manage their own connectivity footprint.

How is FLAG fostering partnerships to create value for customers and enhance your competitive position?

Partnerships are central to how we create value for customers and strengthen our position in an increasingly complex global landscape. We recognise that the traditional model of building own infrastructure end-to-end is neither realistic nor desirable.

Instead, we work within multi-partner ecosystems that combine our subsea assets with partners’ terrestrial networks and subsea investments to deliver seamless, end-to-end connectivity.

This allows us to extend reach into new markets, navigate regulatory complexity more effectively, and give customers greater reliability through diversified routing.

We also work closely with customers and industry partners as anchor tenants on new routes, helping align infrastructure investment with real demand and accelerate deployment in a way that benefits the wider ecosystem.

What long-term goals or initiatives are you most excited about, and how do you envision the industry evolving over the next decade?

What I’m most excited about is how our Vision 2030 strategy translates into very practical changes in how customers design and consume global connectivity.

At its core, Vision 2030 is about aligning our network and product mix with where demand is genuinely shifting, not where the industry has historically been anchored. Customers are moving away from centralised architectures and single-route dependencies, and they’re looking for infrastructure that can flex as workloads, regulations and traffic patterns evolve.

A key focus for us is making connectivity easier to deploy and scale. That means bringing subsea, terrestrial networks, landing stations and data centres together into coherent, end-to-end architectural environments, rather than forcing customers to manage those layers separately. When those pieces work as one, customers can expand capacity, add regions or reroute traffic without having to constantly redesign their network.

Over the next decade, I expect the industry to become far more distributed and demand-led. Growth in AI, cloud and digital services will continue to drive data volumes, but success will depend less on sheer scale and more on adaptability and optionality and how quickly networks can respond to new centres of activity, regulatory constraints and resilience requirements. Vision 2030 is really about positioning FLAG to support that shift in a way that’s usable, resilient and commercially relevant for customers.

What are FLAG’s core products or services?

Our core offering is end-to-end digital infrastructure and connectivity services designed to support global data flows at scale.

At the heart of this is our subsea and terrestrial network, through which we deliver high-capacity bandwidth and connectivity solutions, including leased capacity, dark fibre, and Layer 2 and 3 services for carriers, hyperscalers and enterprises.

Alongside this, we offer IP services such as IP transit, Ethernet and remote peering, enabling customers to connect securely and efficiently across global networks.

We also provide modular edge data centre solutions and cable landing station solutions, giving customers the space, power and infrastructure to deploy compute and storage closer to where data is created and consumed.

What ties these together is the way they’re integrated. Customers aren’t looking for standalone products. They want infrastructure that works across layers, reduces operational complexity and supports long-term scalability.

What markets do you offer FLAG’s solutions to?

Our network spans the US, Asia, the Middle East, and Europe – regions that form the backbone of today’s digital economy. These corridors support high-volume data flows and remain critical for hyperscalers, carriers and enterprises operating at an international scale.

We’re seeing particularly strong growth in Asia and the Middle East, where rising demand for cloud, AI and digital services is driving the need for high-capacity connectivity. At the same time, our presence in Europe and the US enables us to support customers with truly end-to-end, intercontinental infrastructure.

Our strength lies in solving some of the toughest connectivity challenges. By focusing on markets where demand for digital infrastructure is growing fastest, we’re able to expand access where it’s needed most

What upcoming industry events will you be attending?

We are speaking at Submarine Networks World in Singapore in September. The panel is called location, location, location, the next hot spot for submarine investments. We will also be attending Capacity Europe, ITW Asia, PTC’27, and Capacity Middle East.

Is there anything else you want to highlight?

• FLAG’s 2025 Rebrand
• FLAG’s Fiber Links Around the Globe
• 2025: A Year of Momentum at FLAG

# # #

About FLAG

FLAG is one of the largest privately owned subsea cable operators globally. With a network spanning 180+ countries, the company delivers high-speed digital connectivity via seven subsea and six terrestrial cables. Serving hyperscalers and enterprises, FLAG offers flexible capacity solutions across key routes in Asia, the Middle East, Europe, and the USA ensuring reliable, neutral connectivity for mission-critical data. Additionally, the company provides scalable modular data centres for high-performance computing and storage at edge locations and cable landing stations.

Learn more at flagtel.com or reach out directly to flag@theflywheelers.com.

The post Executive Profile: A Conversation with Nadya Melic, Vice President Product & Marketing at FLAG appeared first on Data Center POST.

By Matt Merbach, Vice President, National Solution Services (NS2) at Faith Technologies Incorporated (FTI)

TL;DR

• While public attention focuses heavily on constructing data centers, the real overlooked challenge is keeping these mission-critical facilities operational amid skilled labor shortages and complex environmental demands.
• To ensure constant uptime, operators must adopt a comprehensive, lifecycle-based “end-to-end” support system that integrates specialized professionals across engineering, mechanical systems, fiber networks, and cybersecurity.
• Technology alone is insufficient; success relies on aligning with dedicated service partners who prioritize continuous internal workforce training, offer 24/7 emergency support, and utilize modular manufacturing for safer, more consistent deployments.

# # #

What makes headlines when it comes to data centers? The large number currently under construction across the country. Their locations and the reaction of local communities. Their perceived power and water usage.

So much attention is paid to building data centers. What’s often overlooked ─ the story behind the headline ─ is the task of keeping data centers on once they’re up and running. What plans or service agreements can ensure mission-critical data center infrastructure operates efficiently and constantly?

No doubt, the data center world has service needs. And there’s a revolutionary solution. Yet, before exploring that, let’s quickly review three vital things that influenced the creation of this solution.

First, let’s consider all the demands within the data center space: skilled labor shortages, tight schedules, communication challenges, safety concerns, project complexity, public perception issues and more. As previously mentioned, other priorities overshadow data center service, and that’s a mental hurdle to overcome.

Second, not every data center has the same goal. A world-class service solutions strategy is flexible enough to adjust to solve different challenges. Having integration expertise not only supports modern state-of-the-art systems; it allows for adjustments tailored to the needs of the data center that ensure it achieves that company’s goals.

Third, compared to other commercial buildings or industrial construction jobsites, data centers require more. More communication. More planning. More oversight. More emphasis on safety. Contractors with operating experience within these strictly controlled environments often bring a mindset that prioritizes productivity, operational efficiency and superior service.

Let’s now dive into a revolutionary solution to meet data centers’ growing service needs. When the demands are many, goals are changing, the pressure is on and the mission is critical, it’s still possible to keep data centers on and achieve true peace of mind.

How is “End-to-End” the Answer?

Ideally, efforts to keep a data center up and running are part of an overall, comprehensive lifecycle-based support system. A system that may include an engineering team, integration experts, a real estate team, a design team, construction and safety professionals—all who know the equipment and the systems inside and out.

Why are there so many people with such a variety of skills? Because data center service scopes of work include electrical systems, mechanical systems, control systems, fiber optic networks, UPS and battery health/maintenance, equipment lifecycle analysis, energy and power quality audits, on-demand cybersecurity and more.

That is what’s required to provide service designed to keep modern, mission-critical data center infrastructure running efficiently throughout its lifecycle.

That is an end-to-end solution.

Teams Must Complement the Technology

The right data center service solutions strategy can help prevent downtime, predict performance by using monitoring and analytics, and address issues before they occur. The technology is comprehensive and impressive.

However, wise use of tech alone isn’t a strategy, it’s simply using a tool. Multi-disciplined technical experts embedded in the field are needed to monitor systems, provide proactive maintenance, resolve challenging issues, handle complex upgrades, coordinate warranties and fully support data centers.

The best field service representative teams aren’t contractors; they’re partners who understand and complement the strengths of the projects, they’re dedicated to onsite service, they reply promptly, and they offer around-the-clock emergency support.

When Core Values Align

Partnership becomes “culture fit” when field and support teams are aligned with the core values of data center projects. Some contractors are extremely selective, only working with end users that align with their philosophy. Culture fit is an underrated aspect of data center development and service that’s just as important as capabilities.

Want to further streamline a data center service solutions strategy? Look for two things: a partner that prioritizes education, and a partner that designs and manufactures modular products. Here’s why:

1. From apprenticeships to mentoring to continuing education courses, internal training programs create skilled workers and successful careers. For example, the field service representative teams I work with are trained through an internal program for licensed electricians (journeyman and master level), BICSI-certified technicians, and master technicians.
2. Moving labor off construction sites increases safety and consistency while allowing for rapid deployment to hyperscale data centers and other mission-critical facilities nationwide. Search for an Original Equipment Manufacturer that specializes in manufacturing electrical and modular solutions.

In my position at FTI’s National Solution Services, we care for assets at every step of the lifecycle. Plus, we service the switchboards and power distribution modules we manufacture at the highest possible level. Of course, maintenance is easier when the products are better.

Our newest offering, FTI ON, is a value-added service that provides comprehensive support specifically for data centers. We deliver what the name promises: we keep data centers on, tailoring support for each one along the way.

AI continues to boom, and more data center infrastructure is needed. The investment is huge. The stakes couldn’t be higher. And everything must be kept up and running at peak efficiency. A true end-to-end solution may sound complex and revolutionary, but it’s the smart way ─ perhaps even the only way ─ to achieve what the industry now demands.

# # #

About the Author

Matt Merbach, Vice President, National Solution Services at Faith Technologies Incorporated (FTI), has extensive expertise in holistically managing service for data centers and other emerging technology. He creates comprehensive strategies and approaches tailored to support each data center resulting in optimized uptime and efficiency. Matt’s strategic leadership in asset management and preventative/reactive maintenance ensures seamless data center operations.

The post End-to-End: A Revolutionary Solution to Meet Data Center Service Demand appeared first on Data Center POST.

TL;DR

• Data Centre LIVE: The London Summit 2026 explored how artificial intelligence, sustainability and increasing compute demand are reshaping digital infrastructure strategy, operations and long-term investment priorities.
• Speakers from organizations including NTT Global Data Centers, Equinix, STACK Infrastructure, DXC Technology and GEICO discussed topics ranging from global expansion planning and hyperscale growth to AI readiness, cybersecurity, and emerging technologies.
• The event brought together data center operators, enterprise leaders, infrastructure providers, and technology companies to examine how the industry is adapting to rising demand for resilient, scalable, and energy-conscious digital infrastructure.

# # #

Data Centre LIVE: The London Summit 2026 brought together more than 1,000 senior executives across the digital infrastructure ecosystem in London on May 20–21 for discussions focused on AI, sustainability, resilience, and the future of data center growth. Through keynote sessions, fireside chats, and executive panels, the summit explored how operators, enterprises, and infrastructure providers are adapting to rising compute demand, evolving operational requirements, and increasingly complex digital infrastructure strategies.

The intersection of artificial intelligence and digital infrastructure strategy emerged as a major focus throughout the summit. Alex Bennett, Global Strategy Realisation & Transformation Director at NTT Global Data Centers, discussed how operators are approaching long-term growth planning, balancing resilience and scalability while adapting infrastructure strategies to support changing enterprise and hyperscale requirements. Discussions explored how global portfolios are evolving to meet increasing digital demand without sacrificing operational efficiency.

The growing role of emerging technologies in shaping infrastructure requirements was also explored across multiple sessions. Petrina Steele, Global Lead – Emerging Technologies at Equinix, examined how technologies such as AI and quantum computing are influencing infrastructure planning, connectivity requirements, and long-term digital ecosystem development. Speakers explored how operators are preparing for more data-intensive workloads while supporting increasingly distributed environments.

AI’s growing impact on infrastructure design, performance, and operations also shaped broader agenda discussions. Amy Daniell, Senior Vice President, Strategy & Development at STACK Infrastructure, contributed perspectives around how operators are preparing for rapid growth in compute demand, addressing infrastructure scalability challenges and evaluating the long-term implications of AI on data center strategy, capacity planning and operational models.

Security and operational resilience remained important themes as digital infrastructure becomes increasingly interconnected. Richard Wilkinson, Chief Technologist – Europe GIS at DXC Technology, examined cybersecurity preparedness, evolving infrastructure risks, and the technologies organizations are deploying to secure increasingly complex environments supporting AI-driven operations.

To learn more about Data Centre LIVE and to stay updated on future events, visit the events page here.

The post Data Centre LIVE: The London Summit 2026 Explores AI, Scale and the Future of Digital Infrastructure appeared first on Data Center POST.

Originally published on Medium.

Ilissa Miller, the Founder and CEO of iMiller Public Relations, brings a unique perspective to strategic communications that spans from her early training as an opera singer to her tenure as a local elected official. These diverse experiences taught her that messaging alone is insufficient for driving meaningful change; true progress requires understanding complex systems, taking proactive ownership, and aligning differing perspectives across business, policy, and community lines.

When addressing innovation within large organizations, Miller observes that businesses rarely suffer from a lack of ideas. Instead, innovation is frequently stifled by internal friction, unclear priorities, and bureaucratic misalignment. To overcome these hurdles, she emphasizes the importance of balancing structure with creative freedom, requiring teams to thoroughly understand existing processes before attempting to improve them. Furthermore, she distinguishes between the role of management in maintaining stable systems and the role of leadership in creating the alignment and permission needed to move new concepts forward.

To actively foster a culture of innovation, Miller relies on five core strategies: establishing clear goals, identifying decision-makers, defining responsibilities, creating a safe space for challenges, and aligning new initiatives with overall business priorities. Looking toward the broader industry, she advocates for a movement that treats digital infrastructure as modern civic infrastructure. By engaging communities early, demystifying technology, and highlighting new economic pathways, she believes the industry can replace public fear and misinformation with shared participation and trust.

To continue reading, please click here.

The post Ilissa Miller Of iMiller Public Relations On Strategies for Fostering Innovation Inside Big Business appeared first on Data Center POST.

TL;DR

• Capital discipline is reshaping investment strategies. Investors are reassessing valuation models, underwriting standards, and financing structures as risk is repriced across digital infrastructure.
• Power has become a primary investment consideration. Energy availability, water access, and permitting timelines are increasingly determining where AI infrastructure can be developed and scaled.
• Execution certainty now drives value creation. Developers and investors are prioritizing projects with realistic delivery timelines, secured power resources, and clear paths to deployment.
• Regional differences are influencing capital allocation. Variations in energy availability, regulatory environments, and market maturity continue to shape investment decisions across EMEA, APAC, and the Americas.

# # #

The Tech Capital’s International Finance Forum (IFF) 2026, held May 11-12, 2026, in London, provided a platform for senior leaders from the global digital infrastructure, investment, energy, and technology sectors to examine how risk is being reassessed across the market. Held under the theme Risk, Repriced, the fifth annual forum explored the changing assumptions surrounding valuation, underwriting, capital deployment, and infrastructure execution as AI-driven demand continues to accelerate. With participants representing more than 40 countries and organizations spanning data centers, connectivity, finance, and energy, the event focused on the realities shaping the next phase of infrastructure investment.

Rather than concentrating on future possibilities, the agenda focused on the practical challenges affecting infrastructure deployment today. Topics ranging from capital formation and valuation discipline to energy availability and project delivery reflected a market increasingly focused on fundamentals, execution, and long-term sustainability.

Capital Markets Enter a More Disciplined Era

One of the strongest themes emerging from the forum was the shift toward greater investment discipline. As financing conditions evolve and infrastructure requirements become more complex, investors are reassessing how risk should be measured and rewarded.

Marc Ganzi, CEO of DigitalBridge Group, opened the event with a discussion centered on capital allocation and market confidence. His remarks explored how investors are balancing the tremendous growth opportunity created by AI with concerns surrounding energy access, geopolitical uncertainty, and project execution. The message resonated across multiple sessions, where speakers examined the growing role of private credit, structured finance, and alternative funding models as organizations seek greater flexibility while maintaining prudent risk management.

Several panels also explored whether current valuation assumptions remain appropriate in a market where timelines are extending, costs are increasing, and infrastructure projects face greater operational complexity than in previous development cycles.

Valuation Models Face a Reality Check

As AI infrastructure expands, many of the assumptions that have traditionally supported digital infrastructure valuations are being tested. Speakers examined how leasing expectations, discount rates, utilization forecasts, and long-term growth projections are changing as investors place greater emphasis on execution certainty and operational performance.

Andrew Schaap, CEO of Aligned Data Centers, and Krupal Raval, Chief Strategy Officer of CyrusOne, participated in discussions examining supply, demand, and valuation trends across the sector. Their perspectives reflected a growing recognition that successful infrastructure development depends on more than projected demand. Access to power, realistic construction timelines, and the ability to deliver capacity when customers need it have become equally important considerations when assessing project value.

The result is a market that is placing greater weight on demonstrated execution capabilities and less emphasis on assumptions that may have been acceptable during periods of lower capital costs and fewer infrastructure constraints.

Energy Availability Is Reshaping Infrastructure Strategy

Power emerged as one of the defining topics of the event, appearing throughout discussions on  finance, development, policy, and risk. As AI workloads continue to increase power requirements, energy availability is becoming a critical factor in determining where infrastructure can be developed and how quickly projects can move forward.

Ayotunde Coker, CEO of Open Access Data Centres (OADC), joined discussions examining the physical limitations facing AI infrastructure growth. Conversations explored how power generation, water availability, grid access, and permitting timelines are influencing both investment decisions and project economics.

Many participants noted that energy is no longer simply an operational consideration. In many markets, access to reliable power has become one of the primary determinants of infrastructure value, influencing site selection, underwriting decisions, and long-term growth strategies.

Development Economics Continue to Evolve

The relationship between land, power, pricing, and project timelines was another recurring topic. As development conditions become more challenging, investors and operators are reevaluating how and where capital should be deployed.

Doug Recker, CEO of Duos Technologies Group, participated in the session “Build, Buy or Wait: When Land, Power and Price Stop Aligning,” which examined the changing economics of infrastructure development. Alongside fellow panelists, Recker explored how rising land costs, constrained power availability, permitting requirements, and community considerations are affecting investment decisions.

The discussion highlighted a growing shift away from assumptions that development automatically delivers superior returns. In some cases, acquisition opportunities may offer greater certainty, while in others, delaying investment until market conditions improve may become a viable strategic option. These decisions are becoming increasingly nuanced as infrastructure projects face more variables than ever before.

Regional Markets Continue to Follow Different Paths

While AI demand is global, the conditions supporting infrastructure investment vary considerably by region. Sessions focused on regional capital dynamics and diverging risk profiles examined how investors are evaluating opportunities across Europe, North America, Latin America, and Asia-Pacific.

Energy availability, regulatory frameworks, political stability, and market maturity all emerged as factors influencing where capital is flowing. Rather than pursuing uniform global expansion strategies, many organizations are tailoring investment decisions to regional realities, recognizing that the risks and opportunities associated with infrastructure development differ significantly from market to market.

These regional distinctions are expected to play an increasingly important role as investors seek opportunities that offer both growth potential and greater certainty of execution.

The Next Phase of Infrastructure Investment

A central conclusion from IFF 2026 was that digital infrastructure remains one of the most attractive sectors for long-term investment, but the criteria for success are changing. Demand continues to grow, particularly as AI adoption expands, yet investors are paying closer attention to the factors that determine whether projects can actually be delivered.

Power availability, permitting timelines, workforce capacity, financing structures, and operational execution are now influencing investment decisions as much as market demand itself. The organizations best positioned for success will be those capable of navigating these constraints while maintaining the flexibility required to adapt to a rapidly evolving infrastructure landscape.

To learn more about The Tech Capital and upcoming events, visit events.thetechcapital.com.

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By Mike Hodge, AI Solutions Lead, Keysight Technologies

TL;DR

• The Shift to Inference: The AI industry is rapidly transitioning from episodic model training to continuous, 24/7 inference operations, which are projected to soon account for two-thirds of all AI computational workloads.
• Compounding Financial Risks: Because inference runs constantly, even minor network inefficiencies or latency issues compound over billions of runs, directly eroding operating margins and inflating the cost per token.
• The Danger of Late Validation: Waiting to test inference infrastructure until after it is physically installed is a massive financial risk; discovering bottlenecks late leads to expensive remediation, extends deployment timelines, and delays revenue.

# # #

Over the past few years, AI has dominated boardroom strategy and discourse. Executives have debated LLM deployments, approved record-breaking infrastructure investments, and reorganized day-to-day operations around axioms like “AI transformation.” For much of that timeframe, discussions have centered around deploying infrastructure and using proprietary datasets to train AI models.

But there’s a big shift on the horizon and it’s poised to change everything.

This year, Deloitte projects that only a mere third of computational workloads for AI will be used for model training. The other two thirds will be utilized for answering user prompts and queries, a process known as inference.

The signal is clear. AI is moving from experimentation to large-scale production. And along the way, organizations are discovering that the real bottleneck isn’t building models: it’s running them efficiently at scale.

Inference is the beating heart of the AI engine. It shapes customer experiences, protects (or erodes) operating margins, and generates revenue. But it’s also the source of a new and expensive form of friction: waiting.

In some ways, waiting has become the new normal for AI. Organizations must wait for hardware to arrive in supply-constrained markets. They need to endure lengthy validation cycles to confirm that systems behave as expected. It takes time to discover whether infrastructure performs under real workload conditions; but waiting compounds cost, delays revenue realization, and causes economic drag.

The Economic Shift from Training to Inference

The early days of generative AI focused on scale. The majority of infrastructure spending focused on training models. After all, larger clusters meant faster experimentation and stronger competitive positioning.

But the world has changed. Inference dominates infrastructure spending, and that means network architects have a new set of considerations.

Training workloads are episodic; inference workloads run 24 hours a day, seven days a week. Prompts consume compute cycles, memory bandwidth, networking capacity, storage I/O, and power, and every generated token carries incremental cost. However, this means any network inefficiency will have a compound impact; as runs can repeat millions, or even billions, of times a day.

Even modest issues can snowball at scale. For example, a mere five percent drop in sustained token throughput in a large deployment can cost millions of dollars in annual operating expenses. Slight instabilities in latency distributions can force network operations to provision excess headroom to maintain service-level agreements, inflating total cost of ownership.

Performance issues here aren’t limited to the network. When it comes to inference, inefficiency erodes margins.

The Real Cost of Waiting

The most underestimated financial risk in AI inference is late validation. In many environments, full inference testing occurs only after physical infrastructure is installed and configured.

However, at this stage, capital has already been committed. If bottlenecks emerge in networking fabrics, memory hierarchies, storage systems, or inline security enforcement layers, remediation becomes expensive and time-consuming. Architectural redesigns might require additional procurement or reconfiguration. That means deployment timelines extend and revenue realization windows slip.

To meet this moment, a new competitive variable is emerging: Time-to-AI.

Simply put, Time-to-AI means that waiting isn’t measured by schedule, it’s measured by cost. Organizations that identify and resolve issues earlier can move from capital expenditure to revenue faster. By contrast, those that discover inefficiencies after deployment often compensate by provisioning excess capacity to protect performance guarantees. While that approach preserves service levels, it also inflates cost per token and reduces overall return.

Inference Is Harder Than Training from a Structural Standpoint

Many organizations still treat inference as a scaled-down version of training. That assumption isn’t just wrong. It’s also expensive.

Training workloads are relatively uniform and compute intensive. Inference workloads couldn’t be more different. They’re diverse, use case-specific, and highly sensitive to latency, memory behavior, and concurrency patterns.

For example, a legal AI system may push massive context windows that strain memory subsystems. Financial AI assistants may prioritize microsecond-level determinism. Inference applications in the healthcare industry might need to combine large imaging datasets with sustained throughput demands.

Inference performance is multi-dimensional and not solely defined by peak accelerator throughput. This reality explains the industry’s move toward workload-specific accelerators and domain-optimized designs.

But hardware specialization on its own does not guarantee peak performance, or a good rate of return. If infrastructure isn’t validated against realistic inference workloads before deployment, organizations risk misallocating capital. They may scale GPUs when memory bandwidth is the true constraint; or expand clusters to compensate for networking variability that could have been resolved via architecture. In each case, spending increases faster than sustained value.

Shifting Left: From Expansion to Efficiency

The first phase of AI adoption rewarded expansion. The next phase will reward efficiency and discipline.

Boards are shifting focus from how much infrastructure has been deployed to how effectively that infrastructure converts capital into sustained business output. The more relevant executive questions are no longer about peak tokens per second; they’re focused on sustained cost per token under realistic demands. These are not just engineering concerns, they’re capital allocation decisions as well.

In response, networking teams need to embrace a shift-left mentality. Embracing workload-specific benchmarking, especially in the early stages of procurement, enables organizations to evaluate inference architectures before hardware ever hits the rack. Emulating real-world inference prompts and architectures helps identify potential imbalances across compute, memory, networking, and storage layers before additional capital is deployed. Some platforms even make it possible to recreate industry-specific prompts and LLM architectures, which can go a step further towards reducing iteration cycles and reactive overprovisioning.

In power-constrained data center environments, where energy availability increasingly limits growth, even incremental improvements in sustained tokens per watt can materially affect long-term ROI. Scale still matters, but efficiency now determines competitive advantage.

Certainty Isn’t a Mere Strategy, It’s the Way Forward

If the training era of AI was defined by scale, the inference era will be defined by certainty. Certainty that infrastructure can sustain real workload diversity. Confidence that latency distributions align with enterprise commitments. Proof that deployment timelines are predictable, and capital investments translate into measurable, sustained output.

The winners of the inference era will be the organizations that treat inference validation as a strategic capability, instead of a late-stage technical exercise. They won’t just move from reactive scaling to deliberate optimization. They will deploy faster, allocate capital more precisely, and protect margins more effectively.

Those that do not will continue to wait. And in an inference economy defined by Time-to-AI, time is money.

# # #

About the Author

Mike Hodge is AI Solutions Lead at Keysight, where he drives global strategy and go-to-market execution across the company’s AI, network test, and security portfolios. He specializes in connecting innovation with real-world applications, helping organizations harness AI for smarter, more secure systems.

The post The Inference Reckoning: AI’s New Bottleneck Isn’t Strategy, It’s Time appeared first on Data Center POST.

By Laurent Segneri, R&D executive director at Apx Data Centre Solutions

TL;DR

• The AI “Thermal Wall”: As AI-driven demands push rack densities to 100kW, traditional air-cooling methods have reached their physical limits, rendering standard, transactional cooling procurement obsolete.
• From Vendor to Collaborative Partner: Because every data centre now faces unique physical constraints and staffing shortages, operators must shift from buying cooling equipment as a commodity to treating providers as integrated engineering partners.
• Precision Engineering for Sustainability: Collaborative cooling strategies prevent wasteful “over-cooling” by tailoring compressors and closed-loop systems to specific thermal loads, helping operators optimize critical green metrics like pPUE and WUE.

# # #

As we move through 2026, we aren’t just seeing a slight uptick in data demand; we’re in the middle of a full-scale industrial revolution, powered by AI. While this is good news for the sector, we’re now in the era of the 100kW rack, with power consumption pushed to its limit by the new generation of chips and their successors.

This isn’t just an anecdotal shift. A January 2024 International Energy Agency (IEA) report forecasted that the global data centre industry’s energy consumption would hit a record high 1,000 TWh annually by 2026 —roughly equivalent to the electricity consumption of Japan. With these updated racks, it’s a prediction set to become reality.

While this innovation drives the industry forward, it’s also created a massive hurdle for those of us on the ground. Traditional air-cooling methods, which have served us well for decades, have officially hit a physical ceiling. It is pushing us towards a thermal wall, where blowing more cold air at a server isn’t just inefficient, it’s physically impossible. Operators need reliable and efficient solutions that are tailored to real-world challenges. In this new era, success in data centre cooling goes beyond simply providing equipment.

The commodity trap

As we’ve reached a physical limit, we can no longer treat cooling as a commodity. For too long, procuring the equipment has been a transactional, box-ticking exercise. In the past, operators asked for a set amount of kilowatts for cooling their data centres and the supplier sent them over the correct amount. No questions asked.

In 2026 though, cooling is taking a front seat, and this approach might just be a recipe for operational disaster. At Apx, we’re seeing first-hand that ‘standard’ data centres no longer exist. Every site, whether a hyperscale, enterprise or colocation has its own challenges.

Some operators find that their sites have structural load limits that can’t handle the weight of new liquid-cooling infrastructure. Others are facing a staffing crisis. According to recent Uptime Institute data, 53% of operators are reporting difficulties with finding qualified staff to manage increasingly complex systems.

A true collaborative partner fills the technical void that a mere equipment provider cannot. Being able to trust the person that you are working with and knowing they can rely on you is really important. It goes beyond providing the product– it’s being focused on customer needs and delivering them as best you can, right until the end.

We can’t solve today’s problems with an outdated approach. It’s time to treat cooling providers as partners rather than vendors. It doesn’t matter if the equipment used is modern, it’ll underperform if it hasn’t been designed with the people who have to maintain and install it.

I’ve worked in the HVAC industry for years and understand its intricacies as well as the importance of mechanical engineering. In both sectors, I’ve seen first-hand why working together is critical for infrastructure like this. Focusing on an ‘engineering in partnership’ mindset and collaborating to share our experience creates far better systems; not just built for the now, but the future. And, in doing so, the future’s problems.

Engineering for the boots on the ground

Mechanical engineering backgrounds mean we understand the fundamentals of what it takes to design products that actually work for specific environments. This means we’re not just building hardware; we’re designing around real-world challenges. As part of the LFB Group, we have over 60 years of HVAC experience with state-of-the-art testing facilities that enable us to put the solutions through rigorous, real-life tests first.

Integrating engineering expertise at the start of the process means that logistical issues can be solved or ‘designed out’ before they become expensive problems further down the line.

The industry is littered with cautionary tales of high specification cooling units that arrived on site, but didn’t fit through the door. Focusing on the ‘boots on the ground’ approach prevents logistical problems like this and makes installing a cooling unit a simpler process, reducing the risk of projects from running over on time and budget.

We also have to think about longevity. Although these highly specialised units are projected to have a lifespan of 15 years, they won’t last unless we future-proof them. We need to swap parts for these systems without them shutting down, and they must be easily maintained and have critical components that can be reached by maintenance engineers.

Without collaboration with specialist engineers, operators risk deploying units that are technically brilliant but logistically catastrophic.

Metrics with meaning

Crucially, collaboration doesn’t just mean making life easier for engineers; it also means hitting important sustainability targets. Over 100 of Europe’s data centres are now part of the Climate Neutral Data Centre Pact, striving to be carbon neutral by 2030.

Cooling, and the industry as a whole, often gets a really bad rep, primarily because there’s still a lack of understanding around the world about what data centres do, and where they draw their energy from. However, data centres actually use no more water than a typical golf course.

For us, it’s about flipping the script and working as closely with operators and suppliers as we can to ensure that we are delivering solutions tailored to operators’ specific needs and priorities so that we are providing effective solutions. We are part of an effort to change the narrative through our precision engineering mindset.

The success of cooling units in data centres isn’t just measured by its design, it’s also validated by green metrics such as pPUE (partial Power Usage Effectiveness) and WUE (Water Usage Effectiveness).

Tailoring fans and compressors to the specific thermal load of an AI cluster prevents the ‘over-cooling’ waste that’s less cost-effective. Collaboration with cooling specialists will allow them to implement closed-loop systems that keep units at an optimum temperature without draining the local water supply.

Precision engineering is far more important than updating systems at an unsustainable speed. It’s about being right, not just being fast.

A change in mindset

Three to five years ago, cooling sat in the shadows. But now, thanks to the demand for AI, we’ve gone from the proverbial ‘Fred Flintstone’ era, where they’re powering their car with their legs, to a Formula One car. And because of that, cooling can no longer sit quietly in the background or be seen as a ‘box-ticking’ exercise. Instead, it’s a vital and collaborative engineering discipline which determines whether a data centre thrives or fails.

Future success relies on listening to customers, understanding their physical constraints and addressing operational realities—crucially, ahead of time. Viewing cooling providers as partners rather than vendors enables the construction of solutions that not only fit the space, but operate effectively in real-world scenarios, ensuring that the 100kW racks of today keep running efficiently in 2040.

# # #

About the Author

Laurent Segneri is an experienced leader with a strong focus in R&D Management and transformation, portfolio management and end-to-end project execution in cross-cultural matrix environment while keeping a lean and pragmatic approach to all things.

The post Data Centre Cooling: How Collaboration Drives Performance And Long-Term Reliability appeared first on Data Center POST.

Originally posted on Telecom Newsroom.

Mission-critical Local Area Networks (LANs) in facilities like airports, hospitals, and industrial plants now support far more than traditional IT, handling essential 24/7 traffic such as security video, clinical systems, and building automation. Because these environments are typically saturated with high electromagnetic noise from sources like heavy machinery, elevator systems, and medical imaging equipment, the underlying cabling infrastructure must be able to maintain consistent performance in electrically harsh conditions.

To meet these rigorous demands, Shielded Twisted Pair (STP) cabling provides a distinct advantage over Unshielded Twisted Pair (UTP) by ensuring more predictable performance as data rates and Power over Ethernet (PoE) requirements increase. As modern edge devices demand higher bandwidths and power, shielding preserves the vital signal-to-noise ratio and aligns with strict industrial design standards. In zones with severe electromagnetic interference, STP allows for routing closer to power pathways than UTP, reducing conduit congestion while maintaining network reliability.

Ultimately, for electrically noisy and high-availability environments, STP offers a critical reliability buffer. Provided that grounding and installation are executed correctly, organizations benefit from stronger electromagnetic interference (EMI) immunity, lower signal emissions, and superior headroom to accommodate future speed and PoE upgrades. 

To continue reading, please click here.

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TL;DR

• Data center uptime and infrastructure strategy are now board-level commercial imperatives, driven by the increasing demands and density of AI workloads.
• Relying on fragmented, multi-vendor delivery models splits accountability and significantly amplifies the risk of service continuity issues.
• Adopting a unified delivery model for Mechanical & Electrical (M&E) engineering, connectivity, and electronic security minimizes integration risks and prevents costly rework.
• Integrated systems ensure long-term lifecycle resilience, providing simplified maintenance, predictable performance, and a stronger foundation for scalable growth

Originally posted on Datalec Precision Installations

Data centers have evolved from backend technical environments into critical strategic assets directly tied to revenue, compliance, and customer experience. As artificial intelligence workloads increase density and place higher demands on power, cooling, and security, the cost and complexity of ensuring resilience have surged significantly. Consequently, infrastructure strategy and uptime are no longer solely technical concerns but commercial imperatives that require board-level oversight. Even minor technical failures can escalate into broad service continuity issues, a risk that is heavily amplified when accountability is split across multiple vendors in fragmented delivery models.

To address these challenges, operators are increasingly shifting toward integrated delivery models that coordinate M&E engineering, connectivity, and electronic security from the outset. Consolidating these disciplines under a single partner reduces integration risks, clarifies accountability, and prevents the delays and costly rework frequently seen at the interfaces of disconnected systems. When power, cooling, safety, and monitoring systems are designed as a unified architecture, organizations benefit from enhanced visibility, simplified maintenance, and a stronger foundation for the site’s long-term operation.

Ultimately, the true value of infrastructure investment is realized over its full lifecycle, extending far beyond initial project completion. Integrated environments allow for faster diagnostics, efficient upgrades, and consistent uptime under real-world conditions, minimizing the operational burden of managing overlapping service level agreements across multiple suppliers. By treating system integration as a strategic priority rather than a secondary consideration, resilient operators can establish a future-ready ecosystem that sustains business continuity today and supports scalable growth tomorrow.

To read the full article please click here.

The post Beyond Fit-Out: Why Integrated M&E, Connectivity, and Security Are Now Board-Level Issues appeared first on Data Center POST.

TL;DR

• Atlanta Technical College officially opened one of Georgia’s first datacenter technical training academies through Microsoft’s Datacenter Academy program.
• The facility features a hands-on simulation lab designed to prepare students for careers in datacenter operations, cybersecurity, networking and energy management.
• Backed by more than $800,000 in funding and support from Microsoft, TA Realty and TA Digital Group, the academy creates direct pathways into Georgia’s rapidly expanding digital infrastructure sector.
• The launch reflects growing efforts to align workforce development with Georgia’s emergence as a major data center hub.

As Georgia continues to attract significant digital infrastructure investment, the need for a skilled workforce to support that growth is becoming increasingly urgent.

Atlanta Technical College is addressing that demand with the official opening of its new Microsoft Datacenter Academy lab facility, one of Georgia’s first dedicated datacenter technical training academies.

The ribbon-cutting ceremony, held May 20 on Atlanta Technical College’s campus, brought together leaders from Microsoft, TA Realty, TA Digital Group and regional stakeholders to celebrate a milestone that connects education directly to Georgia’s growing digital economy.

Part of Microsoft’s global Datacenter Academy network, the new facility is designed to create pathways into technical careers through curriculum alignment, scholarships, mentorship, simulation labs and hands-on learning opportunities. Students will gain practical experience in datacenter operations, networking, cybersecurity and energy management, all skill sets with a growing demand as hyperscale and cloud infrastructure continue expanding nationwide.

For Atlanta Technical College President Dr. Victoria Seals, the academy represents a major investment in both students and Georgia’s technology future.

“The future of digital infrastructure does not begin in a server room. It begins in a classroom,” said Dr. Seals. “Behind every advancement in A.I. is the power of H.I., human intelligence. I believe this transformational moment will be shaped by the people who are trained, skilled, and wise enough to guide this innovation. We believe technology will drive the future, but it is important to prepare the people who shape it. This academy represents our commitment to ensuring students gain the skills, access and opportunities needed to lead in one of the fastest-growing industries in the world.”

The initiative is backed by more than $800,000 in funding through the Atlanta Technical College Foundation, with support from Microsoft and industry collaborators including TA Realty and TA Digital Group.

Microsoft says the academy reflects its broader commitment to building local technical talent pipelines in communities where digital infrastructure investment is accelerating.

“Microsoft is proud to support the Microsoft Datacenter Academy at Atlanta Technical College and invest in students pursuing careers in the datacenter and IT industry,” said Bowen Wallace, corporate vice president, Americas, Microsoft. “This new simulation lab gives students hands-on access to equipment and servers, reflecting our shared commitment to strengthening the local talent pipeline and preparing learners for high-demand careers in cloud infrastructure.”

For TA Realty and TA Digital Group, the academy represents a critical link between infrastructure development and long-term workforce readiness.

“What we celebrate here is the result of alignment. Alignment between education and industry, between vision and execution, between opportunity and access,” said Tim Shaheen, partner at TA Realty and chief development officer for TA Digital Group. “At TA Realty and TA Digital Group, we believe workforce development must be intentional, practical and aligned with where the world is today and where it is going tomorrow. That means creating environments where students are not simply talking about the future but actively building it together.”

As Georgia continues to emerge as a major data center market, initiatives like this reflect a broader industry shift: workforce development is becoming a foundational component of digital infrastructure growth.

The post Atlanta Technical College Launches One of Georgia’s First Datacenter Academy Lab Facilities to Strengthen Regional Workforce Pipeline appeared first on Data Center POST.

TL;DR

• Victor expansion continues: Empire Fiber Internet is growing its 100% fiber network in Victor, NY.
• 2,000+ locations served: More homes and businesses across Ontario County now have access to high-speed internet.
• Regional investment underway: The buildout reflects Empire’s broader commitment to the Finger Lakes region and local economic growth.

Empire Fiber Internet, a leading fiber optic internet service provider serving communities across New York and Pennsylvania, is continuing the expansion of its 100% fiber-optic network in Victor, NY, bringing high-speed internet access to more than 2,000 homes and businesses. Additional neighborhoods are also coming online across Ontario County as the company continues construction throughout 2026.

Founded in the Finger Lakes region, Empire Fiber Internet has been serving communities across New York and Pennsylvania since 1896 and continues to grow its local fiber footprint. That regional foundation gives the announcement added significance because it shows the company expanding in an area where it already has deep roots and long-term presence.

The expansion is part of Empire Fiber Internet’s broader investment in Ontario County and the Finger Lakes region. Residents and businesses that previously lacked access to fiber may now be eligible for service, giving more of the community access to the speed and reliability needed for modern life and work.

“Victor and Ontario County deserve internet that works as hard as the people who live and work here,” said Kevin Dickens, CEO of Empire Fiber Internet. “From families relying on connectivity for school and work to businesses that depend on our internet to serve customers, fiber delivers the speed and consistency that modern life requires. And just as important, our customers can count on responsive, local support when they need it.”

As communities across the country demand stronger broadband infrastructure, fiber providers are under increasing pressure to deliver not just faster speeds, but long-term reliability and local service. Empire Fiber Internet’s continued growth in Ontario County reflects that trend, while also highlighting how regional providers can play a major role in strengthening connectivity and supporting local economies.

“We’re thrilled to have Empire Fiber Internet as a valued chamber member,” said Miranda Odell, President of the Finger Lakes Area Chamber of Commerce. “Their commitment to delivering high-speed internet services aligns perfectly with our mission to support local businesses. We love working with them and are overjoyed to hear about their recent expansion in Ontario County. This growth represents a significant boost to our community, enabling more businesses and residents to thrive with reliable connectivity. Congratulations to Empire Fiber Internet on this exciting achievement!”

To learn more about Empire Fiber Internet, visit empirefiber.com.

The post Empire Fiber Internet Continues Local Expansion in Victor, NY appeared first on Data Center POST.

TL;DR

• PowerBridge appointed Scott Hanna as Chief Revenue Officer to lead revenue strategy and hyperscale customer engagement.
• Hanna previously held leadership roles at Cumulus Data and CyrusOne, bringing experience in hyperscale and powered campus development.
• The company is advancing several multi-gigawatt powered digital infrastructure campuses across West Texas, including its planned Alpha Digital Powered Campus near Pecos, Texas.
• PowerBridge says the appointment supports its strategy of combining power, connectivity and digital infrastructure to meet growing AI and hyperscale demand.

The growth of AI infrastructure is forcing the digital infrastructure industry to rethink how large-scale campuses are developed, powered and delivered. Speed to deployment still matters, but increasingly, so does the ability to align power, connectivity and infrastructure execution from the beginning.

That evolving market dynamic is part of the reason PowerBridge recently appointed Scott Hanna as Chief Revenue Officer.

Hanna joins PowerBridge at a time when hyperscale and AI customers are placing greater focus on long-term infrastructure readiness. In his new role, he will lead the company’s revenue strategy, customer development and hyperscale engagement efforts as PowerBridge advances several powered digital infrastructure campuses across West Texas.

The appointment also reunites a leadership team that previously worked together on the development of the Cumulus Data campus in Pennsylvania. Hanna formerly served as Chief Revenue Officer for Cumulus Data, where he helped lead the development and sale of the Susquehanna campus to Amazon Web Services.

Before that, Hanna spent more than a decade at CyrusOne, including serving as Vice President of Hyperscale Sales during a period of major enterprise and cloud growth for the company.

For PowerBridge Founder and CEO Alex Hernandez, that combination of hyperscale relationships and execution experience aligns closely with where the company is focusing its growth.

“Scott brings proven hyperscale relationships, deep commercial experience and a strong track record of execution that aligns directly with our strategy,” Hernandez said.

That strategy centers on developing integrated powered campuses designed to support large-scale hyperscale and AI deployments. Rather than focusing solely on traditional data center construction, PowerBridge is building campuses that combine power infrastructure, connectivity and digital infrastructure development into a unified platform.

The company’s current roadmap includes several multi-gigawatt developments across West Texas, including the planned 2 Gigawatt Alpha Digital Powered Campus near Pecos. PowerBridge believes the region’s energy resources, available land and growing connectivity infrastructure position it to support the next generation of large-scale digital infrastructure growth.

Hanna said the opportunity to help expand that platform was a major factor in joining the company.

“I’m excited to rejoin Alex and our management team in this new chapter focused on building and deploying the powered-campus infrastructure required to support the next era of hyperscale and AI growth,” Hanna said.

As AI demand continues accelerating, the broader industry is increasingly moving toward infrastructure models that prioritize execution, scalability and long-term power availability. PowerBridge’s latest leadership appointment reflects how companies are positioning themselves to meet that next phase of growth.

Read the full release here: https://www.imillerpr.com/news/powerbridge-appoints-scott-hanna-to-drive-revenue-strategy-for-gigawatt-scale-powered-ai-data-center-campuses/

The post PowerBridge Strengthens Leadership Team as AI Infrastructure Demand Accelerates appeared first on Data Center POST.

TL;DR

• Direct Engagement is Essential: Data center developers must proactively communicate with local communities rather than relying on local governments to manage public concerns about resource usage, pollution, and grid strain.
• The Cost of Silence: Failing to address community worries transparently creates a narrative vacuum that invites misinformation, resentment, and severe political backlash, as seen in recent local elections where pro-data center officials were ousted.
• Proactive Problem Solving: By openly discussing practical engineering solutions, tax benefits, and past operational lessons, tech companies can build necessary trust, identify potential issues early, and secure the vital infrastructure needed for ongoing AI expansion.

# # #

Originally posted on The Kansas City Star.

The rapid expansion of artificial intelligence requires significant data center infrastructure, which is crucial for maintaining long-term global and economic leadership. However, this growth frequently faces pushback from local communities that are rightly concerned about environmental and civic impacts, such as excessive water usage, noise pollution, unfair tax treatment, and the strain placed on local electrical grids. When these valid worries are ignored by developers or solely delegated to local governments, they can quickly escalate into widespread skepticism and organized opposition that is easily fueled by misinformation and propaganda.

Relying on underfunded local municipalities to manage public sentiment has proven to be a flawed and short-sighted strategy for the tech industry. Because local officials may prioritize the potential for new tax revenues over community concerns, especially in areas facing financial distress or population decline, citizens often feel their questions are being evaded. Recent elections in Missouri illustrate this growing backlash, with voters actively ousting politicians who supported massive data center tax breaks without providing sufficient transparency to the public.

To secure the infrastructure necessary for future technological advancements, developers must take a proactive approach to community outreach. By directly participating in civic dialogues, operators can clarify their engineering solutions for noise abatement and resource efficiency, explain the logic behind tax incentives, and address community challenges before they derail projects. Ultimately, direct and transparent engagement is essential for data center operators to build trust and establish themselves as responsible neighbors.

To continue reading, please click here.

The post Engaging the Public on the Realities of Digital Infrastructure appeared first on Data Center POST.

TL;DR

• As edge AI increasingly automates industrial infrastructure monitoring, a critical reliability problem has emerged: these AI systems are only as accurate as the observations feeding them.
• Facilities face a dangerous “ground truth gap” because isolated sensors and static deployments often fail to capture true environmental conditions, missing localized issues like thermal layering or airflow disruptions.
• Faster analytics cannot solve this blind spot; increased processing speed only accelerates responses to observed events and completely fails to compensate for anomalies the sensing layer misses.

# # #

Modern edge infrastructure monitoring environment showing real-time telemetry dashboards, connected industrial systems, and AI-driven operational analytics inside a data center or industrial operations facility.

The rapid growth of edge AI is changing how industrial infrastructure is monitored and managed.

Across data centers, logistics environments, connected facilities, and industrial operations, organizations are increasingly deploying AI-driven systems capable of analyzing telemetry in real time, detecting anomalies, optimizing cooling, automating alerts, and improving operational responsiveness without direct human intervention.

But underneath this accelerating layer of intelligence is a reliability problem many organizations still underestimate:

AI systems are only as reliable as the observations feeding them.

In many industrial and edge environments, that observational layer remains incomplete.

The Operational Visibility Assumption

Modern monitoring platforms are highly effective at processing telemetry streams. However, there is an important difference between processing data efficiently and accurately representing real-world conditions.

In practice, many operational systems still rely on isolated sensing points, periodic logging intervals, and static deployment strategies that cannot fully capture environmental variability across physical infrastructure.

This creates what many engineers increasingly describe as a “ground truth gap” — the difference between actual operating conditions and the subset of conditions sensors are capable of observing.

The issue becomes especially visible inside temperature-sensitive environments.

Within data centers and industrial infrastructure, airflow disruption, rack density, cooling inefficiencies, thermal layering, and equipment cycling can create highly localized environmental deviations. Yet monitoring dashboards may continue displaying stable conditions simply because the sensing layer never directly observed the anomaly.

The monitoring system itself may remain fully functional.

The environment may not be.

Why Faster Analytics Does Not Solve the Problem

 Thermal visualization showing localized hot spots and airflow inconsistencies inside a data center or industrial environment.

One of the most common assumptions surrounding edge AI is that reducing latency automatically improves operational awareness.

It does not.

Faster analytics only improve response speed to observed events. They cannot compensate for events the sensing layer failed to capture in the first place.

This distinction becomes increasingly important as AI systems move closer to autonomous infrastructure operations.

Today’s edge environments increasingly depend on AI-driven operational logic to manage cooling efficiency, environmental controls, predictive maintenance, workload optimization, and infrastructure resiliency. As organizations continue automating these decisions, incomplete telemetry becomes more operationally significant.

Three recurring factors continue to distort real-time operational visibility:

• Sensor Placement Bias – Sensors are frequently positioned in locations that are operationally convenient or compliance-oriented rather than areas with the highest environmental variability.
• Temporal Gaps – Many monitoring architectures still rely on fixed logging intervals. Short-duration environmental fluctuations occurring between measurements may never appear inside recorded telemetry.
• Spatial Variability  – Physical environments are rarely uniform. Airflow dynamics, infrastructure density, thermal layering, and operational movement continuously create localized variability across facilities.

Single-point sensing cannot fully represent these conditions.

The Risk of Confidently Incomplete Systems

One of the least discussed challenges in operational AI is amplification.

AI systems do not independently validate reality. They operationalize observations at scale.

When telemetry contains blind spots, automated systems inherit those same limitations while continuing to generate highly confident operational outputs.

This creates a growing disconnect between perceived operational visibility and actual environmental awareness.

In many edge environments, organizations believe they have achieved real-time visibility when they have only achieved real-time reporting from limited observation points.

Those are not the same thing.

As enterprises continue investing in edge intelligence, predictive operations, and AI-driven infrastructure automation, improving sensing fidelity may become just as important as improving analytics sophistication.

The long-term reliability of operational AI systems will increasingly depend on whether organizations can improve the representational accuracy of the telemetry entering those systems.

Because in edge AI environments, intelligence is only as reliable as the observations behind it.

 # # #

About the Author

Aity Ritesh Raj is an intern at Mindlabs Cloud focused on industrial IoT, edge monitoring systems, and operational intelligence across connected infrastructure environments. His work explores how telemetry integrity, sensing reliability, and environmental variability impact AI-driven operational decision-making in modern industrial systems.

The post The Hidden Reliability Problem Behind Edge AI and Industrial IoT appeared first on Data Center POST.

TL;DR

• Data Center Cooling Expansion: Driven by the rising thermal loads of high-performance computing and expanding digital infrastructure, the global data center chillers market is projected to reach $6.4 billion by 2035.
• Scalable and Sustainable Thermal Management: Hyperscale data centers and water-cooled systems are experiencing significant growth as operators prioritize energy-efficient, scalable, and automated cooling technologies to maintain system stability under environmental constraints.
• High-Density Fiber for AI Workloads: To support bandwidth-heavy applications like GPU clusters and migrations to 400G/800G fabrics, data centers are maximizing rack capacity using multifiber interfaces and very small form factor (VSFF) connectors

# # #

The global data center chillers market was valued at USD 2.6 billion in 2025 and is estimated to grow at a CAGR of 9.6% to reach USD 6.4 billion by 2035, according to a recent report by Global Market Insights Inc.

Increasing reliance on digital infrastructure is driving demand for advanced cooling systems capable of handling rising computing loads across modern data centers. As power consumption continues to increase, cooling requirements scale proportionally, creating strong demand for efficient thermal management solutions. The growing density of high-performance computing systems is reshaping chiller design, requiring more compact, energy-efficient, and high-capacity systems. Innovations in cooling technologies are addressing operational constraints while improving performance in space-constrained environments.

Geographic variations in infrastructure development and environmental conditions are also influencing deployment strategies. Resource availability is becoming an important consideration, particularly in regions facing environmental constraints, which is shaping the adoption of sustainable cooling technologies. Overall, the increasing need for reliable and efficient cooling across evolving digital ecosystems is expected to drive sustained growth in the market.

The data center chillers market is also benefiting from the rising complexity of IT infrastructure and the need for advanced thermal management systems. Increasing computing intensity is pushing operators to adopt more efficient cooling solutions that ensure system stability and performance. Continuous technological advancements are enabling improved energy efficiency and operational optimization, further strengthening market growth.

The water-cooled systems segment is projected to grow at a CAGR of 10% between 2026 and 2035. This growth is supported by their superior heat transfer capabilities, scalability, and ability to deliver high efficiency in large-scale operations. These systems are increasingly preferred in facilities requiring consistent and high-capacity cooling performance.

The hyperscale data centers segment is anticipated to grow at a CAGR of 10.8% during 2026 to 2035. Growth in this segment is driven by the increasing demand for large-scale computing capabilities, which require advanced cooling solutions to manage rising thermal loads. The expansion of high-capacity data infrastructure is creating a strong need for robust and efficient chiller systems.

U.S. data center chillers market reached USD 1.2 billion in 2025 and is expected to grow at a CAGR of 9.3% from 2026 to 2035. Market growth in the country is supported by the rapid expansion of advanced computing infrastructure and increasing energy requirements. Rising demand for efficient cooling solutions is encouraging the adoption of next-generation technologies designed to handle high-performance workloads while improving energy efficiency.

Key players operating in the data center chillers market include Carrier Global, Trane Technologies, Johnson Controls, Daikin, Mitsubishi Electric, LG Electronics, Vertiv, Schneider Electric, STULZ, and Rittal. Companies in the market are focusing on innovation, efficiency, and scalability to strengthen their competitive position. They are investing in advanced cooling technologies that enhance performance while reducing energy consumption.

Many players are integrating smart monitoring and automation capabilities to improve system management and reliability. Strategic partnerships and collaborations help companies expand their global footprint and address evolving customer requirements. Additionally, manufacturers are prioritizing sustainable solutions, including energy-efficient designs and environmentally friendly refrigerants, to align with regulatory standards. Continuous research and development, along with capacity expansion and product diversification, are enabling companies to meet the growing demand for high-performance cooling systems in modern data center environments.

The post Data Center Chillers Market to Surpass USD 6.4 billion by 2035 appeared first on Data Center POST.

TL;DR

• Bridging the Power Gap: As AI and high-performance computing accelerate hyperscale growth beyond the immediate capacity of permanent grids, operators are increasingly relying on flexible, deployable energy solutions like mobile compressed natural gas (CNG) to launch projects faster.
• Mobile Energy Expansion: Highlighting this shift, Certarus is expanding its portable CNG operations, including a new Utah supply hub, to provide turnkey, interim power for major developments, such as a recent 60 MW hyperscale data center.
• Scaling High-Density Fiber: Inside the data center, soaring bandwidth demands from 400G/800G networks and GPU clusters are driving the adoption of high-density fiber platforms that maximize rack space using multifiber interfaces and very small form factor (VSFF) connectors.

# # #

Hyperscale data center development, driven by artificial intelligence and high-performance computing, is accelerating across North America, increasing demand for reliable power that can be deployed ahead of permanent grid and pipeline infrastructure.

At the same time, industrial customers across the region are increasingly seeking flexible, reliable natural gas supply to support operations, manage peak demand, and ensure continuity in environments where infrastructure is constrained or evolving.

Together, these trends are driving demand for fast, flexible energy solutions that can be deployed quickly and scaled as projects grow.

This is creating demand for delivered energy solutions, such as over-the-road compressed natural gas (CNG). Certarus, the leader in mobile CNG solutions in North America, provides an integrated, scalable solution to help customers access reliable energy and move critical projects forward.

Certarus’ mobile CNG platform, anchored by the industry’s largest portable compression fleet, is purpose-built for these needs, providing scalable, turnkey natural gas delivery from early-stage project deployment through long-term operations. The recently announced Utah hub and gas supply award are the latest in a series of data center and industrial wins that reflect Certarus’ ability to accelerate access to energy across a range of applications.

In April, Certarus announced multiple contract awards, including a two-and-a-half-year gas supply agreement for a hyperscale data center project with more than $300 million of expected revenue over the life of the contract. Operations for that project are expected to begin in mid-2027.

Building on this momentum, the company is commissioning a new CNG supply hub southeast of Salt Lake City, Utah, and has been selected as the primary natural gas supplier for a 60 MW hyperscale data center project in the region.

Operations at the Utah facility – and gas supply to the data center – are expected to commence this month. The agreement will support the data center through commissioning and early operations until permanent infrastructure is in place, highlighting the role of mobile energy in bridging infrastructure gaps.

“Across both data center and industrial markets, customers are increasingly limited by infrastructure that cannot keep pace with energy demand,” said Dale Winger, President, Certarus. “Certarus provides an integrated, scalable solution to help customers access reliable energy to move valuable projects forward. The new Utah hub strengthens our growing network of strategically positioned supply points that allow us to serve customers quickly and efficiently across multiple end markets.”

Certarus brings a differentiated set of capabilities to both data center and industrial customers, including:

• The largest portable compression fleet in the industry, paired with the largest CNG transport trailer fleet in North America, enabling unmatched scale and deployment flexibility
• Proprietary high-flow pressure-reduction systems engineered for prime power and industrial applications
• An integrated gas supply and logistics platform that delivers turnkey energy solutions without reliance on fixed infrastructure
• An experienced field operations team with a proven track record of executing complex, large-scale projects safely

This combination positions Certarus as a trusted partner for customers who need to move quickly, scale efficiently, and operate reliably, whether as a primary energy source in early project stages or as a complementary solution alongside future pipeline infrastructure.

For more information, visit www.certarus.com.

The post Certarus Expands Energy Access for Data Centers and Industrial Customers with New Utah Hub and Major Data Center Award appeared first on Data Center POST.

TL;DR

• Student support: Aureon awards $12,000 in scholarships to Iowa students pursuing STEM and technology paths.

• Local impact: Focus on rural and statewide access to education opportunities.

• Industry relevance: Programs contribute to building the next generation of digital infrastructure talent.

# # #

As digital infrastructure expands, so does the need for skilled talent to support it across engineering, operations, and emerging technology fields.

That demand is becoming more visible across the industry, particularly as AI workloads, cloud adoption, and network expansion increase. Roles tied to cybersecurity, data analysis, and field operations are evolving quickly, requiring a workforce that can keep pace with more complex infrastructure environments.

In Iowa, Aureon is contributing to that effort through its annual STEM scholarship programs, awarding a total of $12,000 to nine high school students preparing to enter technology-focused fields. Rather than a single initiative, the scholarships are structured to reach students across different communities and educational paths. One program supports students from areas served by independent telecommunications providers, while another is designed for those pursuing broader technology education across colleges, universities, and trade schools within the state.

This reflects a growing recognition that workforce development needs to start early and extend beyond major metro areas. Rural communities are becoming increasingly important to the digital infrastructure ecosystem, both as locations for network expansion and as sources of future talent.

The students selected for this year’s scholarships plan to pursue disciplines that closely align with current industry needs, including computer engineering, cybersecurity, software development, and data-driven business fields. Many will remain in-state for their education, reinforcing a local pipeline between Iowa’s education system and its evolving technology landscape.

“Every year, we see Iowa students whose talent and drive will power the state’s technology future,” said George O’Neal, CEO of Aureon. “By investing in their STEM education today, we’re strengthening the communities and businesses we serve across Iowa.”

Investments in education like this are becoming an important way to support both workforce development and local communities. As networks grow and new technologies place greater demands on performance and security, companies are recognizing that long-term success depends as much on people as it does on platforms.

Aureon plans to continue the program, with the next round of applications expected to open later this year. Additional details are available in the full announcement: https://www.imillerpr.com/news/aureon-awards-12000-in-stem-scholarships-to-nine-iowa-high-school-students/

The post Aureon Invests in Future Tech Talent with STEM Scholarships Across Iowa appeared first on Data Center POST.

TL:DR

• Beyond Simple Job Counts: Communities often evaluate digital infrastructure projects based solely on the number of permanent jobs created within the facility, which causes them to overlook the massive chain reaction of economic opportunity these developments generate.
• Immediate Economic Activation: The financial impact of a facility begins long before construction starts; early planning and design phases immediately drive demand for local services, consultants, legal teams, and hospitality sectors.
• High Value, Low Community Strain: Data centers act as central nodes that stimulate massive supply chains and professional services across the region, while bringing the added benefit of placing little to no long-term stress on local resources like schools, housing, and traffic.
• A Holistic Economic Catalyst: To fully leverage the next generation of technology investment, communities must adopt greater economic literacy to see beyond narrow employment metrics and recognize digital infrastructure as a comprehensive catalyst for regional growth.

# # #

Understanding infrastructure architecture is critical, but so is recognizing how economic value actually materializes. Much of the public conversation still evaluates digital infrastructure through narrow employment metrics, overlooking the broader chain reaction of opportunity these developments activate. To plan effectively, communities need greater economic literacy around how infrastructure investment shapes regional growth over time. This is the final article in my eight-part series exploring the convergence of industry and governance to solve the digital infrastructure build-out dilemma.  You can read the previous posts in my series here, to learn more.

When communities evaluate digital infrastructure projects, the conversation often centers on a single question: How many permanent jobs will this facility create?

It is an understandable question. Local leaders are accountable for economic development outcomes, and employment metrics are familiar, tangible indicators of value. But when digital infrastructure is assessed primarily through job-count comparisons, an enormous portion of its economic impact can be overlooked.

Because the economic story begins long before a facility is built.

Economic activity begins the moment a digital infrastructure project is conceived. Local vendors are engaged, consultants are hired, impact studies are commissioned, and hospitality and service sectors immediately feel the benefit. A data center doesn’t just create jobs inside the facility; it activates an entire ecosystem of opportunity across industries.

From the earliest stages of planning, projects generate demand for a wide range of local services. Developers engage research firms to assess feasibility. Environmental consultants evaluate land and resource considerations. Architects and engineers begin design work. Legal teams structure transactions. Lobbyists and policy advisors navigate regulatory environments. Activists raise funds and the ecosystem designed to bring us technology becomes an interchange of dollars, even to those who don’t want them there.

Even basic logistical needs create ripple effects. Before a project even goes in front of a planning board, developers are already hiring local printers, using local hotels and restaurants, bringing in consultants, commissioning impact studies: economic activity starts the moment a project is conceived.

As development progresses, the ecosystem expands further. Skilled trades such as electricians, plumbers, construction specialists, become essential. Security providers, transportation firms, and equipment suppliers play critical roles. Connectivity providers, chip supply chains, and energy innovation partners contribute to the broader infrastructure landscape.

Yet many traditional impact assessments remain narrowly focused. Impact studies are often too narrow. They focus on permanent jobs, maybe 100 or 150 roles for a large data center, but during construction there can be thousands, and even that still misses the broader economic activity.

This gap between perceived and actual impact can shape public sentiment. When residents see a large facility but hear relatively modest employment figures, questions naturally arise about whether development aligns with community priorities.

And remember, the inverse is also happening. The stress on schools, housing, traffic for a long-haul large-scale development is low to no impact locally. When structured effectively, these large facilities provide incredible economic benefits to communities without the long-term strain on resources.

What is often less visible is the multiplier effect. People look only at the building, they don’t understand that digital infrastructure development builds entire local economies.

A data centers function as a node within a complex network of industries. A data center sits at the center of an entire ecosystem where computer chips, networks, professional services sit. Expanding off of that there are many more layers of economic opportunity. These economic opportunities span the country or world.

For example, consider that professional services firms expand. Hospitality businesses experience increased demand. New suppliers enter regional markets. Workforce development programs evolve. Adjacent technology investments may follow. Think of all of the consultants,  lawyers, lobbyists, and the associations that benefit from these businesses. The direct, indirect and tertiary benefits of these large scale deployments can reach well beyond a community’s immediate needs for local jobs.

Understanding this broader economic landscape is increasingly important as communities navigate infrastructure decisions in a rapidly digitizing world. Evaluating projects through holistic economic literacy, rather than isolated metrics , can help align development outcomes with long-term strategic goals.

This is one of the central objectives of iMPR’s proprietary Groundswell™ engagement  approach.

By helping communities identify where value is created across the full lifecycle of infrastructure development, stakeholders can move beyond transactional debates toward more informed planning conversations. The focus shifts from whether development creates jobs in a single facility to how it contributes to regional competitiveness, business attraction, and ecosystem growth.

Digital infrastructure is not simply a building. It is an economic catalyst.

Communities that understand this dynamic are better positioned to participate in the opportunities emerging from the next generation of technology investment.

Those that do not may underestimate the scale, and timing, of its impact.

Learn more about what we are doing at iMiller Public Relations to bridge the gap between industry and community for the digital infrastructure sector, go to www.imillerpr.com.

For information about the OIX DIFC, visit www.oix.org/standards-and-certifications/oix-dif-standard.

The post The Hidden Economy of Digital Infrastructure appeared first on Data Center POST.

TL;DR

• Quantica Infrastructure filed interconnection applications with NorthWestern Energy tied to future power generation capacity for its Big Sky Digital Infrastructure Campus in Montana.
• The filing begins a formal review process that takes place years before construction and is intended to support potential long-term customer demand.
• The proposal includes renewable generation, firming generation, and battery storage.
• Quantica says it would fund the additional power infrastructure rather than passing costs to local ratepayers.

Quantica Infrastructure has taken another step in the development of its Big Sky Digital Infrastructure Campus in Montana by filing interconnection applications with NorthWestern Energy tied to future power generation capacity for the project.

The filing supports Quantica’s 1,100 MW Big Sky Campus in Yellowstone County and is intended to help meet potential long-term customer demand while supporting regional grid reliability. According to the company, additional capacity would be delivered in multiple phases over several years and would remain aligned with customer commitments and regulatory approvals.

The filing also marks the beginning of NorthWestern Energy’s formal interconnection review process, which occurs years in advance of construction for projects of this scale.

As proposed, the applications cover a mix of renewable generation, firming generation, and battery storage representing up to 7,235 MW of maximum additional capacity. Quantica noted that renewable generation output would be materially lower than maximum nameplate capacity and that generation proposals of this scale undergo extensive review processes intended to maintain system reliability.

A central component of the announcement is Quantica’s position that the company would be responsible for the cost and construction of the proposed additional generation infrastructure.

“Quantica will pay for the additional power capacity for the Big Sky Digital Infrastructure Campus in Montana. NorthWestern Energy’s ratepayers will not be responsible for the cost of the power. As a Billings resident, I appreciate this approach and it’s important to me that my neighbors don’t foot the bill for our project,” says Charlie Baker, Chief Accounting Officer of Quantica Infrastructure.

“Developed by Montanans and grounded in local priorities, this project is designed to advance statewide economic opportunity while responsibly safeguarding communities and minimizing negative impacts to Montana’s citizens.”

Quantica also stated that Big Sky Digital Infrastructure has engaged in preliminary discussions with the Montana Department of Environmental Quality regarding permitting requirements for the campus and associated generation infrastructure, including firming power options such as natural gas, geothermal, and other potential sources.

The company framed the filing as part of broader planning for long-term infrastructure needs.

“Data center companies are looking for places that can deliver power, connectivity, and building capacity at scale. By investing in additional capacity now, we plan to address what we’re seeing in terms of power demand from data center companies. This expansion significantly increases our total investment in Montana, and the additional power capacity would result in even more economic opportunity, construction jobs over several years, and strengthen the State’s power grid,” says John Chesser, CEO of Quantica Infrastructure.

The Big Sky Campus spans 5,100 acres approximately 30 miles north of Billings and is positioned adjacent to major infrastructure including a substation, highways, and rail access. Quantica says the site is designed to support multiple data center buildings and accommodate the proposed increase in power capacity without expanding the campus footprint.

The company expects the first building to become operational in 2029. Quantica also plans to connect the campus through hundreds of miles of new fiber-ready underground conduit intended to link the site with additional U.S. markets and support regional connectivity.

Read the full release here: https://www.imillerpr.com/news/quantica-files-interconnection-applications-to-expand-power-generation-for-its-big-sky-digital-infrastructure-campus/

The post Inside Quantica’s Plan to Prepare Big Sky Campus for Future Power Demand appeared first on Data Center POST.

TL;DR

• New high density inventory at 60 Hudson: Hudson InterXchange (Hudson IX) plans to bring a second 1 MW data hall online in July 2026, creating additional deployment opportunities inside one of New York City’s most interconnected carrier hotel environments.
• Supporting AI and next generation workloads: The new space is designed for high density cabinet deployments capable of supporting air cooled loads of 45kW and beyond, enabling organizations to accommodate AI, cloud, HPC, and compute intensive applications.
• Long term growth underway: Following the successful launch of its first 1 MW data hall, Hudson IX continues progressing toward a larger vision of delivering more than 10 MW of total capacity at 60 Hudson Street.

As artificial intelligence workloads, cloud ecosystems, and high performance computing environments continue reshaping digital infrastructure requirements, operators in major metropolitan markets are encountering a growing challenge: securing available power and deployable space in highly connected locations. In New York City where both remain at a premium, the ability to bring new inventory online has become increasingly valuable.

Hudson IX is continuing its growth at 60 Hudson Street with plans to bring a second 1 MW data hall online in July 2026. The expansion follows the successful launch of the company’s first 1 MW data hall, which is already supporting customer deployments and represents another step toward Hudson IX’s broader roadmap to exceed 10 MW of total capacity at the site. As AI, hyperscale platforms, and cloud environments continue driving demand, operators in mature urban markets are increasingly facing space and power constraints. 

Hudson IX remains among a limited number of providers able to deliver new contiguous space and surplus power within a highly connected New York City facility, an increasingly rare advantage in today’s constrained market. 

Connectivity remains a defining advantage at 60 Hudson Street which provides access to more than 300 carriers, cloud providers, exchanges, and service providers. As one of the world’s most network dense facilities, the ecosystem offers organizations meaningful benefits for latency sensitive and heavy interconnection environments. 

By making additional resources available inside this ecosystem, Hudson IX is offering more than physical deployment space. Customers gain entry into a deeply established connectivity environment that supports growth, performance, and operational efficiency at scale.

Atul Roy of Hudson IX emphasized the company’s ongoing commitment to serving customer requirements and strengthening its presence at 60 Hudson Street. He noted that Hudson IX continues investing aggressively to meet market demand while providing customers with rare access to scalable power resources, flexible deployment models, and dense interconnection opportunities.

Beyond this deployment, Hudson IX continues advancing a roadmap designed to expand its footprint beyond 10 MW at 60 Hudson Street, reinforcing a long term commitment to scalable growth in one of New York City’s most connected facilities. 

As digital transformation initiatives continue accelerating and demand for compute resources grows, developments like these underscore a larger reality: unlocking new opportunities within established infrastructure ecosystems may become one of the most important differentiators in constrained metro markets.

For organizations evaluating options in New York City, the continued buildout at 60 Hudson Street represents more than another facility enhancement. It creates access to one of the market’s most significant digital crossroads.

The post Hudson IX Continues 60 Hudson Growth with Second 1 MW Data Hall and Roadmap Beyond 10 MW appeared first on Data Center POST.

TL;DR

• Kasi Cloud commissioned West Africa’s first hyperscale-ready, AI-capable, carrier-neutral data center campus in Lagos, Nigeria.
• The Lekki campus is strategically located near major subsea cable landing stations and is expected to scale to approximately 100MW of IT capacity.
• LOS1 gives Nigerian enterprises, financial institutions, and government agencies a sovereign, in-country cloud and AI infrastructure alternative aligned with Nigeria’s National Cloud Policy 2025.
• Leaders across Lagos State, the Federal Government, and NSIA say the project positions Nigeria and Lagos as a major digital and AI gateway for Africa’s future growth.

# # #

Kasi Cloud Datacenters has officially commissioned West Africa’s first hyperscale-ready, AI-capable, carrier-neutral data centre campus in Lagos, marking an important step in Nigeria’s shift from digital consumer to digital owner. The recent flag-off ceremony for its Lekki campus signals the move of Kasi LOS1 from construction into operational readiness, opening up a sovereign, world-class cloud and AI infrastructure option for Nigerian enterprises, financial institutions, and government agencies.

Located across roughly four hectares in the Maiyegun area of Lekki, the campus sits next to six subsea cable landing stations, including Equiano and 2Africa. This strategic positioning strengthens Lagos’s role as a digital gateway for the continent. Once completed, the campus is expected to scale to around 100MW of critical IT capacity. LOS1 is built to support high-density AI and accelerated computing environments, alongside enterprise cloud and connectivity services, with sub-50ms latency for in-country workloads.

Keeping Nigeria’s data and value at home

Nigerian enterprises currently spend an estimated $850 million each year on foreign cloud infrastructure, sending significant capital offshore and placing data under foreign legal jurisdictions. With LOS1, Kasi is introducing the country’s first institutional-grade, AI-ready alternative built on Nigerian soil. This also aligns with Nigeria’s National Cloud Policy 2025 (NCP2025), which requires in-country hosting for sensitive government and financial data.

By providing a sovereign, enterprise-grade cloud and AI platform locally, Kasi ensures that data and the value it generates remain within Nigeria and under Nigerian jurisdiction. In practical terms, this allows enterprises, financial institutions, and government agencies to run critical workloads locally while meeting stricter compliance, data residency, and regulatory requirements.

Built for the AI era

The commissioning of LOS1 represents both a milestone in infrastructure and the delivery of a long-held mission.

“Kasi was founded on the belief that Africa deserves world-class sovereign digital infrastructure built for the AI era,” said Johnson Agogbua, Founder and CEO of Kasi Cloud Datacenters. “For too long, Africa’s data has powered someone else’s economy. Today, that changes. This flag-off marks the transition from development into commissioning and operational readiness — as we deliver world-class sovereign cloud and AI infrastructure, built in Lagos, for Africa’s digital future.”

Agogbua noted that the milestone reflects close collaboration with leaders at both state and federal levels. “We are honoured to celebrate this milestone with His Excellency Governor Babajide Sanwo-Olu of Lagos State, the Honourable Minister of Finance and Coordinating Minister of the Economy Taiwo Oyedele, and Dr. Segun Ogunsanya, Chairman of NSIA — partners and champions whose belief in Nigeria’s digital future made this moment possible” said Agogbua.

Lagos State’s long-term digital vision

The commissioning of LOS1 also reflects Lagos State’s ongoing commitment to building its economic future on strong digital infrastructure. Governor Babajide Sanwo-Olu, Executive Governor of Lagos State, returned to the Kasi Lekki Campus as Special Guest of Honour to officiate the flag-off ceremony for West Africa’s first hyperscale-ready, AI-capable data centre campus, having also presided over its groundbreaking in 2022.

His presence at both milestones reflects a continued partnership between Lagos State and Kasi Cloud, grounded in a shared belief that sovereign digital infrastructure is essential to the city’s future. He has consistently emphasized the importance of infrastructure in sustaining Lagos’s growth, stating: “If Lagos is to sustain its Centre of Excellence status in Nigeria, vital infrastructural development is critical to achieving human capital development. The economic impact that infrastructure improvement has on nation-building cannot be overemphasized.”

In December 2024, the state government publicly committed to hosting world-class data centres in Lagos. With LOS1 now commissioned, that commitment is beginning to take physical form and signals Lagos’s intention to lead Nigeria’s digital transformation.

Federal government’s Renewed Hope Agenda

At the federal level, the Honourable Minister of Finance and Coordinating Minister of the Economy, Taiwo Oyedele, also attended the flag-off ceremony, reinforcing the Federal Government’s recognition of digital infrastructure as a key pillar of Nigeria’s economic diversification strategy. The commissioning of Kasi LOS1 aligns with the Renewed Hope Agenda, which places technology and digital infrastructure at the center of growth, innovation, and job creation.

By enabling an AI-ready, sovereign platform in Lagos, Kasi supports national goals around economic resilience, innovation, and employment, helping ensure that investment in cloud and AI infrastructure translates into local value creation.

NSIA: backing sovereign digital infrastructure

The Nigerian Sovereign Investment Authority (NSIA) has played a foundational role in supporting Kasi’s vision. Also present at the flag-off was Mr. Aminu Umar-Sadiq, Managing Director and Chief Executive Officer of NSIA, one of Kasi Cloud’s foundational investors and a long-standing advocate for digital infrastructure as a driver of long-term economic transformation.

NSIA has described Kasi Cloud as a strategic asset, noting in its 2025 Annual Report that the platform is “advancing Nigeria’s digital infrastructure” as an indigenous hyperscale data centre. “We target high-impact projects that transform critical sectors of economic growth — including initiatives like Kasi Data Center. We congratulate Kasi on this momentous milestone. NSIA believes in the potential of digital infrastructure to serve as an enabler and accelerator for innovation,” Mr. Umar-Sadiq said. “We expect that the transformative impact of this infrastructure on the domestic tech space will reposition Nigeria. The Board and Management of the Authority is proud to be associated with this development.”

With LOS1 now AI-ready and open for business, that shift is already underway.

Africa’s next digital gateway

From an investor perspective, the Lekki campus is about much more than a single facility.

“Africa represents one of the most compelling long-term digital infrastructure growth markets globally,” said Mark Adams, Co-Founder of Kasi Cloud Datacenters. “As global cloud, AI, and content platforms continue expanding into emerging markets, Nigeria — and Lagos specifically — is uniquely positioned to become the strategic digital gateway for the continent. Kasi LOS1 is the infrastructure that makes that possible.”

The campus is designed to support that future, serving both global platforms expanding into Africa and regional enterprises seeking access to world-class infrastructure.

Read the full press release here.

The post Kasi Cloud Commissions West Africa’s First Hyperscale-Ready, AI-Capable Campus in Lagos appeared first on Data Center POST.

TL;DR

• DC BLOX expanded its green financing facility to $850 million, more than tripling its original October 2024 loan.
• The funding will accelerate hyperscale-ready data center and digital infrastructure growth across the Southeast.
• DC BLOX continues to strengthen regional connectivity through cable landing stations, dark fiber networks, and new hyperscale campuses.
• Company leadership says the investment supports long-term economic growth and rising cloud and AI demand throughout the region.

# # #

DC BLOX is taking another major step in its mission to build the digital backbone of the Southeast with a significant expansion of its green financing. The company has increased its Senior Secured Credit Facilities loan to $850 million, more than tripling the original $265 million facility secured in October 2024. This infusion of capital will accelerate the development of hyperscale-ready digital infrastructure across one of the fastest-growing data center regions in the United States.

The expanded green loan provides DC BLOX with greater flexibility to fund both current projects and a robust pipeline of new hyperscale data center developments. These include multiple investment-grade, preleased hyperscale facilities across the broader Southeast, where cloud and AI demand continue to rise. The financing reflects confidence in DC BLOX’s ability to consistently deliver complex, large-scale projects for hyperscale customers on time and to specification.

“Our best-of-breed financing terms and execution with our finance partners speaks volumes of our track record of execution and our strong customer composition,” said Melih Ileri, Chief Investment Officer of DC BLOX. “We were able to further develop our finance relationships with this loan and set ourselves up for accelerated growth. This financing also validates our development and operational capabilities, such as our ability to secure powered land, deliver projects on time, and meet the requirements of hyperscale customers.”

DC BLOX has focused on building the foundational digital infrastructure that enables sustained economic growth in the Southeast. The company’s cable landing stations in Myrtle Beach, South Carolina, and Palm Coast, Florida, bring global connectivity to the region, while its dark fiber network across South Carolina and Georgia provides a high-capacity backbone for regional hyperscale data centers. In parallel, DC BLOX continues to expand its footprint of edge and hyperscale campuses in markets including Alabama, Georgia, South Carolina, Tennessee, and Florida.

Leadership at DC BLOX views this financing as a catalyst not only for the company, but for the communities it serves. “DC BLOX is proud of our role in positioning the Southeast for future growth,” said Jeff Uphues, CEO of DC BLOX. “Data centers and the networks that connect them are vital for economic growth and we are thankful to our financing partners, local government leaders, customers, development partners, communities, and employees for sharing the vision and for the tremendous, sustained effort it takes to realize it.” The facility is backed by funds managed by Future Standard, a global alternative asset manager with $93 billion in assets under management and a long track record of investing in transformative infrastructure.

To learn more about DC BLOX’s expanding digital infrastructure platform across the Southeast, read the full press release here.

The post DC BLOX Secures $850 Million Green Financing to Accelerate Hyperscale Infrastructure Growth in the Southeast appeared first on Data Center POST.

TL;DR

• Driven by AI and High-Speed Fabrics: Data centers are increasingly adopting high-density fiber platforms to meet surging bandwidth demands from AI, distributed storage, and migrations to 400G/800G networks without expanding their physical footprint.
• Maximizing Rack Capacity: These platforms boost port density by utilizing very small form factor (VSFF) connectors, multifiber interfaces, and pre-terminated trunks, which simplify deployments and provide the massive connectivity required by modern GPU clusters.
• The Crucial Role of Cable Management: While high density saves space, it introduces operational risks like congested pathways and bend radius violations; successful deployments require meticulous horizontal and vertical cable management to ensure safe and efficient routine changes.
• Strategic Density Placement: The absolute highest density is not always the smartest choice. Operators should right-size their approach by deploying ultra-dense modules in stable cross-connect zones while preserving more working room in high-change areas to prevent accidental disconnects and simplify maintenance.

# # #

U.S. data centers are being pushed to deliver more bandwidth (cloud, streaming, enterprise SaaS, and support for AI) while holding the line on space, cost, and uptime. High-density fiber platforms (modular patch panels, optical distribution frames (ODFs), and pre-terminated trunk/harness ecosystems) help by packing more fiber terminations into less rack space. However: cable management and day-to-day serviceability determine whether density is an advantage or a liability, and the densest build is not always the best build.

Why port density matters now

Traffic patterns have shifted toward east–west flows inside the data center, driven by distributed storage, microservices, and GPU clusters. At the same time, fabrics are migrating from 100G/200G toward 400G and 800G, and guidance on these transitions often calls out higher port density and the rise of GPU-accelerated clusters as key design pressures. In the U.S. colocation market—where cabinets and cross-connects are billable units—packing more connectivity into fewer racks can materially impact cost and deployment speed.

High-density platforms typically increase capacity in three ways:

• More adapters per rack unit: ultra-dense 1U fields can land very large numbers of ports. High port density supports up to 120 ports per unit.
• More fibers per connector: multifiber interfaces (MPO/MTP and newer Base-16 variants) carry parallel lanes efficiently, simplifying 400G/800G breakouts and reducing the number of individual jumpers required.
• Smaller connector formats (VSFF): very small form factor connectors such as SN and CS shrink the interface itself. Use of VSFF connectors can increase fiber count to as much as 3456 in a 1U space.

The net effect is clear: significantly higher bandwidth per cabinet, and fewer racks dedicated purely to patching and distribution.

How high density supports the practical needs of deployments. 

Faster migration cycles are available at higher speeds. Modular panels and cassette-based systems make it easier to reconfigure a fiber field when switching generations (e.g., LC to MPO breakouts, Base-8/12/16 changes, single-mode expansion), without rebuilding entire rows. This matters as 400G/800G becomes common in new pods and expansions.

You get far more links per “hot” rack. AI racks can require many high-speed connections per rack position. There’s a clear link between rising connector density and GPU growth, with VSFF connectors playing a significant role in providing connectivity for increasing numbers of GPUs.

Easier labor and repeatability make execution fast and simple. Pre-terminated trunks and harnesses can reduce on-site termination work and improve consistency—valuable when schedules are tight and change windows are limited. Pre-assembled trunks and harnesses reduce installation time and labor costs while minimizing errors associated with manual termination and splicing.

Cable management: the hidden cost of maximum density

The tighter the fiber field, the easier it is to create congested pathways, exceed bend radius, or make routine MACs (moves, adds, changes) risky. Horizontal and vertical cable management is critical for maintaining bend radius and strain relief, and exceeding bend radius or placing strain can degrade performance or cause failures. A commonly cited bend-radius rule of thumb in fiber standards guidance is ~20× cable diameter while under pulling tension and ~10× when unloaded.

So “high density” must include the management ecosystem: adequate horizontal/vertical managers, front-access routing, slack storage that doesn’t crush fibers, clean labeling, and clear overhead/underfloor pathways. Dense panels often succeed or fail based on whether technicians can safely trace and dress cords without obstructing airflow or bending cords around sharp edges.

Why “not the absolute highest” can be the smartest choice

Chasing the maximum ports-per-U can increase operational risk if the environment changes frequently. A practical rule is to choose the highest density that still allows technicians to patch, trace, and dress cords without violating bend radius, blocking airflow, or turning every change into a high-risk task. Many operators right-size density based on how the area will be used:

• High-change zones where frequent repatching takes place often benefit from more working room—even if that means fewer ports per U—because it reduces accidental disconnects and speeds work orders.
• Stable zones (structured cross-connect fields) can justify ultra-dense modules because cabling changes less often and can be governed by strict procedures.
• If multiple teams touch the same cabinets, slightly lower density can improve MTTR by making circuits easier to identify and service.

Bottom line

High-density fiber platforms can be a major advantage: they compress the physical layer, support 400G/800G migrations, and keep high-bandwidth fabrics scalable as AI drives up per-rack connectivity. The payoff, however, depends on disciplined cable management— high port counts only yield optimal benefits when daily operations are aligned!

# # #

About the Author

Paul Campos is the President of R&M USA Inc.

The post High-Density Fiber: Enabling The Port Density Gains That Power Applications Of Today And Tomorrow appeared first on Data Center POST.

TL;DR

• Lubbock goes live: Duos Edge AI is opening its newest operational Edge Data Center in West Texas.
• Built for local demand: The site adds capacity for compute, AI, network, and recovery workloads across the region.
• Another step forward: The deployment expands Duos Edge AI’s edge footprint and supports long-term growth in Lubbock.

# # #

Duos Technologies Group Inc. (Nasdaq: DUOT), through Duos Edge AI, Inc., has announced a newly operational Edge Data Center in Lubbock, Texas. The facility supports the local market with scalable, low-latency infrastructure designed to serve carriers, enterprises, education, healthcare, and the broader regional economy closer to where data is created and consumed.

The Lubbock Edge Data Center serves as a central communications hub for carriers and network providers delivering services to mobile operators and other local users. The deployment marks another step in Duos Edge AI’s continued rollout of modular edge data centers built to bring high-performance computing, resilient infrastructure, and AI readiness to underserved and high-growth markets.

“Bringing this edge data center online in Lubbock delivers low-latency, high-performance computing where it’s needed most,” said Doug Recker, CEO of Duos Edge AI and Duos Technologies Group,Inc. “This deployment also reinforces our commitment to supporting local businesses and enabling long-term digital growth across the region.”

Duos Edge AI will host a Lubbock open house on Thursday, May 28, 2026, from 11:00 AM to 1:00 PM CT at 1634 18th Street, Lubbock, TX 79401. Community leaders, partners, and industry stakeholders will have an opportunity to tour the facility and learn more about the company’s edge infrastructure approach.

To learn more about Duos Edge AI and register for the open house, visit freeevite.com/event.php?e=R7tSexY4S22Yvnzuwn2S_Q.

The post Duos Edge AI to Host Lubbock Edge Data Center Open House appeared first on Data Center POST.

TL;DR

• AI infrastructure growth is significantly increasing global data center energy consumption and operational capacity requirements.
• Renewable and carbon-free energy adoption continues to accelerate across hyperscale data centers and colocation environments.
• AI-driven liquid cooling deployments in data centers are increasing industry focus on water consumption, closed-loop cooling systems, and water efficiency strategies.
• Data center operators are making measurable progress in operational efficiency and emissions reduction despite rising AI workloads.

# # #

The rapid expansion of AI infrastructure is reshaping the global data center industry and bringing renewed focus to sustainability, energy consumption, water usage, and operational efficiency. A newly released report from Structure Research takes a closer look at how hyperscalers and data center providers are responding to these growing environmental pressures while continuing to scale infrastructure to support AI-driven demand.

The 2026 State of Environmental Impact Report analyzes environmental data from 38 data center providers and nine hyperscale cloud platforms between 2020 and 2025. The report highlights how AI deployments and high-density compute workloads are accelerating infrastructure growth while also driving new investments in renewable energy, liquid cooling, and operational efficiency.

According to the report, data centers accounted for an estimated 1.23% of global energy consumption in 2025, up from 0.81% in 2020. Total data center energy consumption increased from 198.7 TWh in 2020 to 361.6 TWh in 2025 as hyperscalers and operators expanded capacity to support AI and cloud services.

The report also found that total operational IT capacity within the data center industry reached an estimated 80,242 MW in 2025, compared to 44,046 MW in 2020. Hyperscale self-build capacity grew at a five-year CAGR of 17.6%, reflecting the ongoing global expansion of AI infrastructure campuses and large-scale cloud deployments.

Despite rising resource demands, the report points to measurable progress in sustainability initiatives across the industry. Renewable energy usage among ESG Leaders grew at a five-year CAGR of 26.2%, significantly outpacing overall energy consumption growth. Hyperscalers sourced approximately 92% of their energy usage from carbon-free energy in 2025, while data center providers reached 69%.

As power constraints continue to impact major data center markets, the report notes that operators are increasingly exploring nuclear energy agreements, natural gas partnerships, and direct power procurement strategies to secure long-term energy availability.

Operational efficiency improvements also remain a key focus area. Average Power Usage Effectiveness (PUE) for data center providers improved from 1.44 in 2020 to 1.38 in 2025, while hyperscalers maintained industry-leading average PUEs near 1.21. Emissions intensity also declined during the same period, with average emissions per GWh of energy consumption decreasing from 328.3 mtCO2e/GWh in 2020 to 229.3 mtCO2e/GWh in 2025.

Water consumption emerged as another major theme throughout the report as AI-related liquid cooling deployments continue to expand. Total water consumption among ESG Leaders increased from 55.8 million cubic meters in 2020 to 114.9 million cubic meters in 2025. In response, operators are increasingly adopting closed-loop liquid cooling systems, hybrid cooling designs, and non-potable water strategies to improve water efficiency and reduce environmental impact.

The report also includes the updated Structure Research Sustainability Quadrant (SRSQ), a benchmarking framework designed to evaluate ESG Leaders based on transparency, renewable energy usage, and operational efficiency. The initiative aims to encourage greater consistency and transparency in ESG reporting across the digital infrastructure sector.

As AI infrastructure demand continues to accelerate, the report provides insight into how hyperscalers, colocation providers, enterprises, investors, and policymakers are navigating the environmental realities tied to next-generation digital infrastructure growth.

Read more in the press release and download the report here.

The post Structure Research Examines the Environmental Impact of AI Infrastructure Growth in New ESG Report appeared first on Data Center POST.

TL;DR

• Lightpath is expanding its NYC metro fiber infrastructure to support more than 2,400 macro cell tower locations across the Northeast.
• The deployment includes 265 new route miles of fiber construction across CT, MA, NY, and NJ.
• The expansion strengthens wireless backhaul capacity and network densification while supporting multi-tenant commercialization opportunities.
• Customers in expansion markets gain access to Lightpath’s full portfolio of AI-grade connectivity solutions, including optical transport, dark fiber, Ethernet, and dedicated internet access.

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As demand for mobile data, AI-enabled applications, and high-capacity connectivity continues to accelerate, wireless service providers are placing increasing pressure on the fiber infrastructure supporting macro cell tower deployments. Scalable, resilient backhaul networks have become essential to maintaining performance, supporting densification, and enabling future wireless growth.

To help meet these evolving infrastructure demands, Lightpath has announced a major expansion of its NYC metropolitan fiber network to support deployments for leading national wireless service providers across more than 2,400 macro cell tower locations throughout Connecticut, Massachusetts, New York, and New Jersey.

The deployment includes 265 new route miles of fiber construction, extending and densifying Lightpath’s expansive 12,100 route mile network footprint. The infrastructure leverages Lightpath’s existing high-capacity backbone to deliver scalable 100 Gbps and 400 Gbps aggregation connectivity to multiple customer endpoints.

The expansion reflects Lightpath’s broader strategy of investing alongside strategic customers while building scalable infrastructure capable of supporting additional tenants and future growth opportunities. More than half of the deployed endpoints are served using existing fiber infrastructure, demonstrating the long-term value and commercialization potential of owned network assets through multi-customer adoption.

“This expansion demonstrates our ability to invest deeply in dense fiber infrastructure, in this case expanding within the NYC metropolitan area with follow-on commercialization via lease-up of those assets across multiple customer verticals and use cases,” said Chris Morley, CEO at Lightpath.

Customers within the expansion footprint will also gain access to Lightpath’s broader portfolio of AI-grade connectivity solutions, including optical transport up to 800 Gbps, Ethernet, dedicated internet access, dark fiber, and private network services.

This announcement follows Lightpath’s recent network expansions across Greater New York, Eastern Pennsylvania, Greater Miami, Phoenix, and Columbus as the company continues building scalable, low-latency infrastructure for carriers, hyperscalers, enterprises, and data-intensive applications nationwide.

Read more in the press release here.

The post Lightpath Expands Dense NYC Metropolitan Fiber Infrastructure to Support Major Wireless Providers appeared first on Data Center POST.

TL;DR

• Green Capital S.A. and Prime Capital AG are partnering to develop a 300 MW battery storage portfolio in Poland.
• The project will span multiple sites in Poland and is designed to support grid stability, renewable integration, and energy flexibility within the European market.
• The collaboration combines local development expertise and infrastructure investment experience to accelerate delivery and long-term growth.

Green Capital S.A. and Prime Capital AG are partnering to develop a 300 MW portfolio of Battery Energy Storage Systems (BESS) in Poland, marking a notable addition to the country’s growing energy storage market. The portfolio is designed to support grid stability, renewable integration, and the broader shift toward a more flexible power system.

Project Scope

The buildout is expected to span multiple sites across Poland, with one advanced-stage project to begin construction in Q2 2026. The partners will also jointly advance a second large-scale project, expected to reach Ready-to-Build status by the end of 2026, establishing a clear development path for both partners.

The collaboration combines Green Capital’s local development expertise with Prime Capital’s infrastructure investment experience. This partnership aims to move Green Capital from a developer to an Independent Power Producer, and help Prime Capital expand its battery energy storage footprint and further cement its presence in the ever-evolving European storage market.

Market Momentum

Large-scale storage is gaining traction across Europe as utilities, developers, and investors look for ways to strengthen grid resilience and support the energy transition. Poland is emerging as an increasingly important market in that shift, with projects like this helping lay the foundation for future growth.

Michał Polanowski, CEO, Green Capital, expressed, “We are delighted to welcome Prime Capital as our partner. By establishing a joint venture for the realization of a 300 MW / 1,200 MWh BESS portfolio, we are marking a transformative moment for Green Capital. Prime Capital brings proven expertise in hybrid infrastructure investment across Europe, including a strong BESS track record, and together we are the first to bring this combination of scale and institutional capital to the Polish storage market. This portfolio will play a crucial role in balancing the national grid, enabling a faster and safer energy transition.”

Company Background

Green Capital S.A. focuses on renewable infrastructure and utility-scale project development. Prime Capital AG brings experience across energy and infrastructure investment. Together, they are advancing a portfolio that is set to play a meaningful role in expanding Poland’s battery storage capacity and modernizing its energy landscape.

The post Green Capital and Prime Capital Partner on 300 MW Battery Storage Portfolio in Poland appeared first on Data Center POST.

TL;DR

• Great Plains Communications is acquiring Fastwyre Broadband’s Nebraska business, expanding its footprint across more than two dozen communities.
• Nebraska customers will gain access to GPC’s fiber network, local support, and future network upgrades.
• The deal strengthens GPC’s long-standing commitment to Nebraska and supports continued regional growth.

# # #

Great Plains Communications (GPC), the leading Midwestern digital infrastructure provider and a portfolio company of Grain Management, LLC, is expanding its Nebraska footprint through the planned acquisition of Fastwyre Broadband’s Nebraska business, a move that strengthens its position across the state and supports its long-term network growth strategy.

The transaction will bring more than two dozen Nebraska communities into GPC’s service footprint and give current Fastwyre customers access to expanded service options, future upgrades and the company’s MEF-certified 20,000+ mile fiber network. It also extends GPC’s locally rooted support model, with call centers, representatives and technicians who live and work in the communities they serve.

“Our vision has always been to expand our fiber network throughout the Midwest and beyond and acquiring Fastwyre’s Nebraska business is a strategic milestone in that journey,” said Todd Foje, CEO of Great Plains Communications. “This acquisition strengthens our position in key markets, opens new opportunities for growth and builds on our 115-year history as a trusted technology partner in Nebraska. What continues to set us apart is the strength of our high-performing network and the dedication of our high-performing people, enabling us to consistently create long-term value while delivering the superior experience customers expect and deserve.”

Following the closing of the transaction, which is subject to customary conditions including applicable regulatory approvals, GPC said it will work to ensure seamless continuity of service and a smooth transition for Nebraska Fastwyre customers. The company also plans to upgrade and integrate the newly acquired business as part of its reinvestment strategy. This investment is expected to enable both residential and business customers across these Nebraska communities to access advanced fiber-driven services, while positioning Nebraska and beyond for future growth as technology needs continue to accelerate.

Nick Wilkin, Chief Financial Officer of Great Plains Communications shared,“The financial strength of our company allows us to pursue strategic acquisitions like this while also funding the critical network upgrades that Nebraska homes and businesses need. We are well-positioned to integrate these communities seamlessly to bring GPC’s customer-first service to Nebraska Fastwyre customers. We are also excited to welcome over two dozen Nebraska-based Fastwyre employees to GPC.”

The acquisition reflects GPC’s continued focus on infrastructure investment, customer service and regional growth.

Read the full release here.

The post Great Plains Communications (GPC) to Acquire Fastwyre Broadband’s Nebraska Business appeared first on Data Center POST.

TL;DR

• New long-haul route: Aureon and partners deliver a 100 Tb transport network across the Midwest.

• AI-driven demand: Built to support growing cloud and AI workloads, with expansion planned to 400 Tb.

• Strategic corridor: Strengthens the Midwest as a key on-ramp to major data center hubs.

As Artificial Intelligence continues to reshape the digital infrastructure landscape, the demand for high-capacity, low-latency connectivity is accelerating at an unprecedented pace. Across the United States, regional networks are playing a more critical role in supporting hyperscale growth, cloud expansion, and the infrastructure required to power next-generation workloads.

Against this backdrop, Aureon is expanding its long-haul transport capabilities with a new 100 Tb route designed to support AI and cloud-driven traffic growth.

Built alongside partners t3 Broadband, Nokia, and Midco, the route connects Ellendale, North Dakota to Chicago through a diverse fiber corridor spanning the Midwest. Designed for both performance and resilience, the network provides a direct, low-latency pathway into major data center hubs, reinforcing the region’s role as an increasingly important connectivity corridor.

The network is being brought online in phases, with initial capacity reaching 100 Tb and a clear path toward 400 Tb as demand increases. Aureon will oversee ongoing support and maintenance, ensuring consistent performance as traffic requirements scale.

“This deployment required a high level of coordination across networks, vendors, and timelines,” said George O’Neal, President and CEO at Aureon. “Thanks to the expertise and ambition of our team, and the strength of our partner relationships, we were able to deliver the solution our customer needed in the timeframe requested.”

The collaboration highlights the complexity involved in delivering high-capacity transport infrastructure at speed. The deployment also reflects how multi-vendor coordination is becoming standard for high-capacity builds, combining optical innovation, system integration, and existing fiber infrastructure to deliver performance at scale.

Together, these efforts underscore a broader industry shift. As AI workloads increase, network operators are being pushed to rethink how infrastructure is designed, deployed, and interconnected. High-density compute environments, GPU clusters, and data-intensive applications are placing new pressure on transport networks to deliver both scale and reliability without compromise.

In this environment, regional routes like Aureon’s Midwest corridor are becoming more than just connectivity pathways. They are strategic assets that enable access to compute, support data movement between markets, and help balance capacity across an increasingly distributed infrastructure landscape.

This announcement reflects a growing recognition that the Midwest is not simply a pass-through region, but a critical component of the national connectivity fabric. With access to power, land, and expanding data center ecosystems, the region is well-positioned to support the next phase of digital infrastructure growth.

As AI continues to drive bandwidth demand higher, investments in scalable, high-performance transport networks will remain essential. Deployments like this demonstrate how collaboration across operators, technology providers, and infrastructure partners can deliver the capacity needed to keep pace with that growth.

Learn more in the full release: https://www.imillerpr.com/news/aureon-and-partners-deliver-100-terabit-route-for-the-ai-era/

The post Aureon and Partners Deliver 100 Tb Midwest Route to Support AI and Cloud Growth appeared first on Data Center POST.

TL;DR

• The Shift to the Edge: While massive “AI factories” built for model training currently dominate public attention, the real economic transformation of AI will happen at the inference layer or the edge, where capabilities are deployed directly to businesses and public services.
• Beyond Isolated Projects: Communities must move away from evaluating individual hyperscale projects in isolation and instead adopt a layered infrastructure architecture that strategically interconnects centralized compute, regional data centers, connectivity hubs, and edge nodes.
• Long-Term Competitiveness: Infrastructure decisions require a decade-long outlook, as building an aligned, distributed ecosystem today will directly dictate a region’s future workforce development, business attraction, and public service modernization.
• Empowering Local Leadership: To prevent overbuilding centralized capacity and missing out on distributed innovation, municipalities need architectural awareness and strategic frameworks to confidently align their digital infrastructure with local economic, sustainability, and community goals.

# # #

In this seventh article of my series, we can see how industry and government got to where we are today. Even as trust and governance challenges evolve, there is another strategic issue communities must grapple with: understanding that digital infrastructure is not one-dimensional. The current focus on large AI training facilities risks obscuring the broader architectural transformation underway. Long-term competitiveness will depend not just on attracting hyperscale projects, but on planning for layered and distributed infrastructure ecosystems. You can read the previous posts in my series here, to learn more.

Artificial intelligence is accelerating infrastructure development at a pace few communities have experienced before.

Across the United States, large-scale AI training facilities, often described as “AI factories”, are being planned or built to support the next generation of computing demand. These projects are significant in scale, capital intensity, and resource requirements. They are also capturing the majority of public attention.

But they are only one layer of a much larger infrastructure evolution. Due to the lack of a national vision for AI factory development, there is fear that we may be overbuilding AI factories today. And, we have not yet even begun to plan for the inference infrastructure communities will need at the edge.

Training facilities represent centralized computers, the environments where massive models are developed and refined. Yet the real economic transformation enabled by artificial intelligence will increasingly occur at the inference layer, or edge, where AI capabilities are deployed closer to businesses, public services, and everyday life.

This shift will require a more distributed infrastructure landscape.

Edge nodes, regional data centers, connectivity hubs, and specialized facilities supporting robotics, healthcare innovation, smart city platforms, and industrial automation will all play a role. Communities that focus exclusively on attracting hyperscale projects without considering how these layers interconnect may find themselves unprepared for the broader digital economy.

Infrastructure strategy, therefore, cannot be defined by individual projects alone.

It must be guided by architecture.

This is particularly important because investment cycles in emerging technologies rarely unfold evenly. Periods of rapid buildout in one segment can create perceptions of overcapacity, while adjacent segments remain underdeveloped. Without holistic planning, regions may overbuild centralized capacity while failing to support distributed innovation ecosystems that ultimately drive sustained economic value.

The time horizon also matters. This is not about the next year or the next project,  it’s about where communities will be competitive ten years from now.

Infrastructure decisions made today will influence workforce development, business attraction, real estate markets, and public service modernization for decades. Yet many communities are evaluating proposals in isolation, without frameworks that help them understand how different infrastructure types contribute to long-term economic positioning.

This is one of the reasons strategic planning efforts are becoming increasingly important.

Through the work of the OIX Associations Digital Infrastructure Framework Committee (DIFC), there is growing recognition that municipalities need guidance not only on whether to support development,  but on how to think about infrastructure layering, sequencing, and regional coordination.

Digital infrastructure is not monolithic. It is an evolving system of interconnected assets that must be aligned with community priorities, sustainability considerations, and economic aspirations.

Engagement models must evolve alongside this complexity. Helping communities help themselves is the most effective engagement strategy.

When local leaders are equipped with architectural awareness, understanding the relationship between centralized compute, distributed deployment, connectivity networks, and sector-specific applications, they are better positioned to make confident, strategic decisions.

The goal is not to predict exactly how technology adoption will unfold. It is to ensure communities are prepared to participate in that evolution rather than reacting to it.

AI will not reshape only one industry or one region. It will influence how cities operate, how healthcare is delivered, how transportation systems function, and how businesses compete globally.

Communities that adopt a layered infrastructure vision will be better positioned to capture these opportunities.

Those that do not may struggle to keep pace.

Planning for digital infrastructure is no longer just about capacity. It is about architecture.

Learn more about what we are doing at iMiller Public Relations to bridge the gap between industry and community for the digital infrastructure sector, go to www.imillerpr.com.

For information about the OIX DIFC, visit www.oix.org/standards-and-certifications/oix-dif-standard.

The post From AI Factories to Edge Nodes: Why Communities Need a Layered Infrastructure Vision appeared first on Data Center POST.

TL;DR

• The AI Inflection Point: Artificial Intelligence is driving a massive surge in the digital infrastructure industry, requiring an unprecedented scale of technology, capital, and energy resources.
• Sovereign AI: The European market is focusing heavily on data privacy and “sovereign AI,” leading to the rise of homegrown “neoclouds” to reduce reliance on US-based hyperscalers.
• Curated Networking: Structure Research’s upcoming infra/STRUCTURE Summit (Oct 6-8, 2026, in Las Vegas) is focusing on a “quality over quantity” approach, emphasizing manageable attendance sizes and curated “Hyperscale and Neocloud one-on-ones”.

# # #

The digital infrastructure industry is experiencing a massive paradigm shift, driven by the unprecedented demands of Artificial Intelligence. In a recent episode of NEDAS Live!, host Ilissa Miller sat down with Phil Shih, the Founder and Managing Director of Structure Research, to discuss the rapidly evolving landscape of data centers, hyperscale platforms, and global connectivity.

With both iMiller Public Relations and Structure Research celebrating their 15th anniversaries in 2026, their conversation in episode 65 offered a unique look back at how far the industry has come, and a critical look forward at the macro trends shaping its future.

The AI Inflection Point and the “Crypto Pivot”

According to Shih, the industry is currently in the midst of a major inflection point. The technology, resources, and capital required to support AI infrastructure represent a massive step function higher than the cloud boom that preceded it. Interestingly, this capacity crunch is creating unexpected industry crossovers.

Shih noted that a significant wave of cryptocurrency and Bitcoin mining companies, many holding vast portfolios of land and energy resources, are actively moving into the data center infrastructure sector to support hyperscale platforms and AI models. Because these crypto firms are already experienced in navigating community pushback and strict jurisdiction legislation regarding power and water usage, they are uniquely positioned to execute successful leasing deals and transition their purpose-driven data centers into AI factories.

Global Markets: Sovereign AI and Geopolitical Impacts

The conversation also ventured into international territory, specifically touching upon Shih’s recent insights from the European market. As the global race for AI dominance continues, Europe is heavily focused on “sovereign AI” and data privacy. To reduce reliance on US-based hyperscalers, Europe is steadily developing its own homegrown “neoclouds” to deliver localized computing infrastructure.

Shih and Miller also discussed the sobering reality that data centers are increasingly viewed as critical infrastructure targets amidst global geopolitical conflicts. Recent events in the Middle East, and historic drone threats to major cloud facilities, have shed a light on the vital importance of business continuity and proactive disaster recovery planning.

Looking Ahead: The infra/STRUCTURE Summit 2026

To help industry leaders make sense of these complex data points, Structure Research continues to champion collaboration through its marquee annual event, the infra/STRUCTURE Summit. Returning to the Wynn Las Vegas from October 6-8, 2026, for its seventh installment, the summit prides itself on a “quality over quantity” approach.

Unlike massive, overwhelming trade shows, the infra/STRUCTURE Summit is a highly manageable experience capped at a curated number of attendees. This year, the event is expanding its highly successful private meeting spaces to include “Hyperscale and Neocloud one-on-ones,” ensuring that operating companies, real estate firms, and energy providers can maximize their time and forge meaningful relationships.

As the industry navigates the complexities of AI demand, global conflicts, and power constraints, making data-driven decisions has never been more critical.

To learn more about Structure Research and their latest reports, visit structureresearch.net. To secure your spot at the upcoming event in Las Vegas, head over to infrastructuresummit.io.

To listen to the full conversation, please click here.

The post Navigating the AI Inflection Point and the Future of Digital Infrastructure appeared first on Data Center POST.

TL;DR

• Communities are becoming a critical factor in digital infrastructure deployment as public understanding, permitting, and local governance increasingly influence the success of AI, data center, and connectivity projects.
• AI infrastructure is evolving beyond hyperscale facilities into distributed edge deployments, creating new opportunities and planning challenges for municipalities, public safety agencies, and underserved markets.
• Local governments are being asked to make highly technical decisions about AI, sovereign AI, cybersecurity, bandwidth, and infrastructure ownership without adequate education, staffing, or strategic guidance.
• The OIX Digital Infrastructure Framework Committee (DIFC) is working to provide communities with practical planning frameworks that help city leaders evaluate digital infrastructure responsibly while supporting long-term economic growth and competitiveness.

# # #

At Connected America 2026, which focus on strategy, business models and innovation fo telecom operators, government bodies and their partners, one message became abundantly clear: the future of AI, connectivity, and economic competitiveness will depend not only on technology itself, but on whether communities are prepared to understand, evaluate, and plan for digital infrastructure responsibly.

During a fireside chat titled From Resistance to Readiness: Why Communities Need a Digital Infrastructure Framework, Ilissa Miller, CEO of iMiller Public Relations and as the Chair of the OIX Digital Infrastructure Framework Committee (DIFC), joined Peter Murray, CEO and President of Dense Networks, for a candid discussion about the growing disconnect between infrastructure deployment and public understanding. The conversation explored everything from AI infrastructure and sovereign AI to edge deployments, municipal readiness, public trust, and the urgent need for education and engagement.

The discussion was grounded in a simple but increasingly urgent reality: digital infrastructure is no longer optional. It is becoming foundational to economic growth, government operations, public safety, and national competitiveness.

The AI Infrastructure Race Has Already Begun

Miller opened the conversation by framing the broader geopolitical implications behind the surge in data center and AI infrastructure development. “We’re in the global race for AI dominance. That means that countries are out there trying to attract investment, innovation on that front line, and that also means countries are working against us.”

As communities across the United States confront proposals for new data centers, edge deployments, and fiber expansion, Miller emphasized that much of the public conversation is being driven by misunderstanding, oversimplification, and fear. “Not all data centers are created equal,” Miller explained. “You’ve got edge data centers, commercial enterprise data centers, cloud data centers, AI data centers, data centers sitting at the edge of a cell tower. They’re all called data centers, but nobody’s asking the right questions.”

That lack of clarity, she argued, is creating resistance rooted not necessarily in opposition to technology itself, but in uncertainty and lack of empowerment.

Municipalities Are Being Asked to Solve Problems They Don’t Yet Understand

Throughout the discussion, Murray reinforced the challenges local governments face as AI adoption accelerates faster than public sector planning capabilities.

“Most municipalities don’t have an innovation person,” Murray noted. “It really does take someone with the knowledge of the technology beyond the day-to-day to look at the overall environment and how the incentives are there for industry and growth.”

One of the key themes explored was the emergence of “Sovereign AI”, which is the need for governments and public safety agencies to securely manage and control sensitive data and AI systems internally.

Murray explained that municipalities are increasingly confronting difficult questions around bandwidth, security, compliance, and infrastructure ownership as AI becomes embedded into police, emergency response, transportation, and government systems.

“The municipalities are seeing high usage now taking place on their chatbots and internal uses of AI,” Murray said. “But on the other end of it, they have these critical applications that have regulations that require that they control their information and the data isn’t leaked or corrupted in any way.”

Miller emphasized that communities are not being given sufficient guidance on how to navigate these increasingly complex decisions.

“Nobody’s telling them how to do this, why they need to be doing it, how to navigate it, what questions to ask,” she said. “They need to be empowered with the information, the data points, and the ability to implement this in a very complex environment.”

Edge Infrastructure Will Shape the Next Wave of Community Development

The conversation also explored how AI infrastructure is evolving beyond hyperscale facilities into distributed edge deployments closer to population centers and public services.

Miller described what she called the “edge inference problem,” the challenge of deploying smaller, localized digital infrastructure environments that can support next-generation AI applications in cities and municipalities.

“Edge deployments will empower cities, municipalities and businesses with a competitive advantage,” Miller said, “if we’re saying no to large-scale data center developments, do we think they’re going to be saying no to these smaller edge inference locations?”

Murray pointed to growing opportunities in Tier 2 and underserved markets, particularly as federal broadband and connectivity investments continue to expand.

The discussion highlighted how digital infrastructure creates what the industry commonly refers to as “data gravity,” which is the idea that connectivity and compute resources naturally attract additional businesses, applications, and economic development.

“Digital infrastructure attracts other data points,” Miller explained. “Data gravity attracts other data applications and data usage.”

Why the Digital Infrastructure Framework Matters

A major focus of the session centered on Miller’s work leading the OIX  Digital Infrastructure Framework Committee (DIFC). The initiative aims to provide communities with practical guidance for evaluating and planning digital infrastructure projects.

Miller described the framework as an effort to bring structure, consistency, and long-term planning into infrastructure conversations that are often reactive and fragmented.

“The purpose of this framework is to provide a guidance planning document for city planners to implement digital infrastructure into their master plans,” Miller said.

She warned that communities failing to understand the strategic importance of digital infrastructure risk losing businesses, investment, and competitiveness over time.

“If we do not know the importance of that to government services, to business services, let alone to consumers, we are going to have a mass migration of businesses relocating across the country to where that data is.”

The framework initiative reflects a broader shift happening across the industry: moving conversations away from conflict and toward preparedness, planning, and informed decision-making.

A Call for Industry Engagement

One of the strongest moments in the fireside chat came when both Miller and Murray challenged industry professionals to become more actively involved at the local level.

Miller urged attendees to volunteer for planning boards, zoning committees, and local government advisory groups.

“Go to your local municipality and volunteer for your land use boards. Volunteer for your planning committees,” Miller said. “They need help. They do not know all this infrastructure, what it is and how to use it.”

Drawing on her own experience as a former elected official, she emphasized that many local leaders are being asked to make decisions about highly technical infrastructure without sufficient expertise or guidance.

Murray echoed the importance of education and public engagement, sharing examples of municipalities struggling with infrastructure planning despite significant funding opportunities.

“They don’t know what they don’t know,” Murray said. “One big voice can make a big difference in those areas.”

Building Trust Through Education and Transparency

As the session concluded, Miller emphasized that successful infrastructure deployment will require more than engineering and investment. It will require empathy, transparency, and trust.

“Before you say no, know what you’re saying no to,” Miller said. She encouraged attendees to continue having difficult but necessary conversations with communities about the realities, tradeoffs, and opportunities associated with digital infrastructure development.

“Have compassion and empathy when you’re doing that,” Miller advised. “We don’t all have to agree. That’s why this is a paradox. It’s both good and it’s bad, but we all have to figure out how to navigate this together.”

In many ways, the fireside chat captured a defining challenge for the next decade of infrastructure development: how to balance rapid technological advancement with public understanding, local governance, and long-term community planning.

As AI adoption accelerates and connectivity becomes even more foundational to society, the industry’s ability to move communities from resistance to readiness may ultimately determine how successfully the next generation of digital infrastructure gets built.

To learn more about Connected America and to save your seat at the next one, visit www.terrapinn.com/conference/connected-america/index.stm.

For information about the OIX DIFC, visit www.oix.org.

For support navigating community concerns, learn more about the Groundswell™ program offered by Miller’s company here www.imillerpr.com/community-engagement.

The post Why Communities Need a Digital Infrastructure Framework appeared first on Data Center POST.

TL;DR

• Lightpath launched a new 392-mile fiber route connecting Columbus and Chicago to support growing AI and cloud demands.
• The multi-conduit network delivers scalable, low-latency connectivity with enhanced resiliency and route diversity.
• The expansion strengthens Midwest infrastructure for enterprises, hyperscalers, carriers, and data center operators.

# # #

As demand for AI infrastructure, cloud connectivity, and high-capacity data transport continues to grow, organizations are placing increasing pressure on the networks that support modern digital operations. Scalable, low-latency connectivity and route diversity have become critical requirements for enterprises, hyperscalers, carriers, and data center operators alike.

To help meet these evolving infrastructure demands, Lightpath has announced a new 392-mile long-haul fiber route connecting Columbus, Ohio, and Chicago, Illinois.

The multi-conduit route is designed to provide scalable, high-capacity connectivity between two rapidly growing Midwest markets. Columbus continues to emerge as a major data center and cloud hub, while Chicago remains one of the country’s most important interconnection markets. By directly connecting the two, the new route will support increasing demand for AI, cloud, and data-intensive applications requiring resilient, low-latency transport.

The expansion also complements Lightpath’s broader infrastructure strategy, including LightCube edge data centers designed to support AI and edge compute deployments across key network corridors.

The system is engineered with multiple conduits to support future growth, additional fiber deployments, and enhanced route diversity. Because Lightpath owns and operates its infrastructure, customers benefit from a simplified operational model supported by a single provider and SLA.

Read more in the press release here.

The post Lightpath Announces New Long-Haul Route Connecting Columbus and Chicago appeared first on Data Center POST.

TL;DR

• New market launch: Empire Fiber Internet is now available in Wellsville, NY.
• 1,000+ locations reached: More homes and businesses can now access 100% fiber internet.
• Community presence growing: Empire is pairing service expansion with local engagement in Wellsville.

# # #

Empire Fiber Internet, a leading fiber optic internet service provider serving communities across New York and Pennsylvania, has expanded its service into Wellsville, NY, bringing next-generation connectivity to more than 1,000 homes and businesses. The expansion delivers fast, reliable internet with consistent performance built for today’s digital demands.

Unlike traditional cable or wireless services, Empire Fiber delivers a dedicated fiber connection directly to every home and business. That means symmetrical upload and download speeds, greater reliability, and dependable performance during peak usage for streaming, remote work, cloud-based applications, video meetings, and business operations.

“Wellsville deserves internet that works as hard as the people who live and work here,” said Kevin Dickens, CEO of Empire Fiber Internet. “From families relying on connectivity for school and work to businesses that depend on our internet to serve customers, fiber delivers the speed and consistency that modern life requires. And just as important, our customers can count on responsive, local support when they need it.”

Empire Fiber Internet offers multiple high-speed plans ranging from 500 Mbps to 2 Gig, all powered by a 100% fiber optic network with no data caps, no throttling, and transparent pricing. Local businesses can also access scalable fiber solutions designed to support reliability, security, and growth using the same proven technology trusted by enterprise organizations.

As part of its ongoing commitment to the community, Empire Fiber Internet has joined the Wellsville Area Chamber of Commerce and will participate in upcoming local events, including the Annual Main Street Festival. Empire Fiber Internet representatives will be available to answer questions, explain the benefits of fiber internet, and help residents and business owners understand their connectivity options.

This announcement reflects Empire Fiber Internet’s continued growth, strengthens the company’s presence in Western New York, and reinforces its position as a provider focused on both performance and local support. As communities are increasingly looking for future-ready broadband infrastructure that can support households, small businesses, and long-term economic development, Empire Fiber Internet is prepared to deliver.

To learn more about Empire Fiber Internet, visit empirefiber.com.

The post Empire Fiber Internet Brings 100% Fiber Internet to Wellsville, New York appeared first on Data Center POST.

TL;DR

• AI workloads are accelerating demand for high-density infrastructure, driving increased adoption of liquid cooling, GPU-optimized environments and edge deployment strategies.
• Power availability and grid access are becoming primary factors in determining where data center projects can move forward across Southern Europe.
• Spain and Portugal continue emerging as strategic digital infrastructure hubs due to growing connectivity ecosystems, subsea cable access and hyperscale investment activity.
• Sustainability, energy efficiency and long-term operational resiliency remain central priorities as operators balance rapid expansion with evolving regulatory and environmental expectations.

# # #

Southern Europe’s role in the global digital infrastructure market continues to expand as companies look for new regions capable of supporting AI growth, subsea connectivity and large-scale data center deployment. That momentum was on full display at DCD>Connect Southern Europe 2026, held between May 6 and 7, 2026 in Madrid, where industry leaders gathered to examine the realities shaping the next phase of infrastructure growth across Spain, Portugal and the broader European market.

The conference agenda reflected an industry navigating increasingly complex demands tied to AI workloads, energy availability, cooling technologies and long-term sustainability. Across two days, conversations focused on how operators are adapting infrastructure strategies.

AI Infrastructure and High-Density Computing

AI remained at the center of nearly every major discussion throughout the event as operators prepare facilities for increasingly dense compute environments. Sessions explored how accelerated computing and GPU-driven workloads are changing infrastructure planning, with greater emphasis on liquid cooling, edge deployments and scalable facility design.

Rod Evans, EMEA VP – Supercomputing & AI Cloud Infrastructure at NVIDIA, contributed to discussions examining how AI infrastructure requirements are driving changes in compute architecture and facility design. Additional conversations featuring Tiziano Durante, Cloud Region Lead – EMEA at Microsoft, focused on operational efficiency and the growing importance of scalable cloud infrastructure across the European market.

The panel “Liquid Cooling as a Shared Strategy Among Manufacturers and Operators in the High-Density Era” examined how cooling technologies, facility architecture and chip innovation must evolve together to support next-generation AI infrastructure. Discussions reinforced that liquid cooling is rapidly moving from an emerging technology to an operational requirement for high-density deployments.

Additional sessions addressed how next-generation processors are reshaping data center design, including impacts on rack density, thermal management and power distribution strategies as AI workloads continue increasing infrastructure demands.

Power Availability and Sustainability Pressures

Power constraints and energy procurement remained among the most significant concerns discussed in Madrid. Multiple sessions addressed the growing challenge of securing grid capacity while balancing sustainability goals and long-term infrastructure expansion.

Emma Fryer, Director of Public Policy for Europe at CyrusOne, participated in ESG-focused discussions examining sustainability strategy, regulatory expectations and the role of public policy in supporting future data center growth. Additional panels explored battery energy storage systems (BESS), renewable integration and power resiliency strategies as operators look for ways to support AI growth without overwhelming existing infrastructure.

The conference also featured extensive conversations around energy efficiency and infrastructure viability. Sessions emphasized that access to power is increasingly determining where projects move forward and how operators prioritize long-term development strategies.

Southern Europe’s Growing Infrastructure Position

Regional growth and connectivity also played a major role throughout the conference as Spain and Portugal continue positioning themselves as strategic digital infrastructure markets within Europe.

Emilio Diaz, CEO of Nabiax, participated in the panel “Building Europe’s Next Digital Growth Engine – Lessons from Portugal’s Acceleration,” which explored how investment, connectivity and public-private collaboration are helping drive regional infrastructure expansion. Discussions examined how Portugal’s development model could influence broader European growth strategies as operators seek new locations capable of supporting hyperscale and AI deployments.

Eulalia Flo, Vice President at Equinix, also contributed to discussions around edge infrastructure and the increasing importance of proximity, latency and distributed deployment models as enterprises expand AI and cloud capabilities closer to end users.

DCD>Connect Southern Europe 2026 demonstrated how rapidly the European infrastructure market is evolving as AI adoption, energy strategy and operational scalability continue reshaping data center development priorities. The conversations in Madrid reflected an industry focused less on future possibilities and more on the immediate realities of deploying infrastructure capable of supporting the next generation of digital growth.

To learn more about DCD>Connect and upcoming events, visit www.datacenterdynamics.com/es/dcd-connect-live/south-europe/2026.

The post DCD>Connect Southern Europe 2026 Highlights AI Infrastructure Expansion, Power Strategy and Cooling Innovation appeared first on Data Center POST.

TL;DR

• Open house incoming: Duos Edge AI is hosting a public showcase of its newly operational Waco Edge Data Center on May 21.
• Serving the region: 77 school districts and 12 counties across the Region 12 footprint will benefit from localized AI, network, and disaster recovery capabilities.
• Growing the footprint: The Waco deployment is a key step in Duos’ broader strategy to scale distributed edge infrastructure across Central Texas and beyond.

# # #

Duos Technologies Group Inc. (Nasdaq: DUOT), through Duos Edge AI, Inc., has announced a newly operational Edge Data Center in Waco, Texas, designed to serve as a scalable local computing hub for the broader Central Texas region. The facility supports high-performance compute, network infrastructure, AI workloads, education technology, telemedicine, and disaster recovery solutions for the Region 12 Education Service Center footprint spanning 77 school districts and 12 counties.

The Waco deployment advances Duos Edge AI’s continued rollout of modular edge data centers, bringing low-latency connectivity and computing power closer to where data is created and consumed rather than routing it through distant tier one city data centers. The facility is built to integrate seamlessly with existing network infrastructure and scale alongside growing demand for real-time applications across education, healthcare, business, and emerging AI use cases.

“Waco plays a key role in Duos Edge AI’s growth strategy,” said Doug Recker, CEO of Duos Edge AI and Duos Technologies Group,Inc. “With this deployment, we’re delivering reliable, localized computing resources closer to the schools, businesses, carriers, and communities that rely on them. We’re honored to contribute to the advancement of digital infrastructure in Waco and across Central Texas.”

Community leaders, business representatives, education stakeholders, and industry partners are invited to tour the facility at the open house on Thursday, May 21, 2026, from 11:00 AM to 1:00 PM CT at 2101 W. Loop 340, Waco, TX 76712.

To learn more about Duos Edge AI and register for the open house, visit freeevite.com/event.php?e=o66IsNQrkH8Y7xG49SDytA.

The post Duos Edge AI to Host Waco Edge Data Center Open House appeared first on Data Center POST.

TL;DR

• The Limits of Reactive Monitoring: Traditional alert-based monitoring struggles to manage today’s complex, multi-domain data center environments, often generating excessive noise rather than anticipating system issues.
• Anticipating Risk with Predictive and Causal AI: Moving beyond basic correlation, predictive AI forecasts potential failures hours or days in advance, while causal AI identifies root cause-and-effect relationships across interconnected systems.
• The Rise of Agentic Operations: Advanced AI systems can now recommend and independently execute corrective actions, such as adjusting cooling or redistributing workloads, which elevates human operators from manual triage to strategic oversight

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As data center environments evolve, operators are managing far more than racks and servers. Today’s facilities span hybrid architectures, support increasingly dense workloads, and operate under strict energy and sustainability constraints. Yet many operations teams still rely on traditional monitoring—thresholds, alerts, and dashboards—to maintain performance. That model is reaching its limits.

Reactive monitoring was built for a simpler era. Static thresholds and rules-based automation can surface known issues, but they struggle with dynamic, multi-domain environments where signals from power, cooling, network, and IT systems are deeply interdependent. The result is often noise: thousands of alerts, limited context, and delayed response times. More importantly, these approaches lack the ability to anticipate problems before they occur.

A new operational paradigm is emerging—one defined by predictive and agentic AI.

Predictive AI enables operations teams to move upstream, identifying patterns and anomalies that signal potential failures hours or even days in advance. Instead of waiting for a temperature threshold breach or a server failure, models continuously learn from historical and real-time telemetry to forecast risk. This shift from detection to anticipation is foundational to improving reliability at scale.

Equally important is causal AI, which provides the “why” behind an issue. In complex environments, correlation alone is not enough. Operators need to understand the chain of events across systems: how a cooling inefficiency might impact compute performance, or how a network anomaly could cascade into application degradation. By establishing cause-and-effect relationships, causal AI reduces ambiguity and enables higher-confidence decision-making.

Building on this foundation is the rise of agentic operations. Unlike traditional systems that simply surface alerts, agentic systems can recommend, and increasingly execute, actions. These systems operate with context, memory, and defined guardrails, allowing them to take corrective steps such as workload redistribution, cooling adjustments, or automated ticket resolution. The goal is not to remove humans from the loop, but to elevate their role—shifting from manual triage to oversight and optimization.

A critical enabler of this transformation is unified operational intelligence. By fusing telemetry across facility and IT domains into a single, continuously learning system, organizations can break down silos that have historically slowed response. This integrated view accelerates root cause analysis, reduces duplicate effort, and ensures that actions taken in one domain do not negatively impact another.

The benefits are tangible: fewer incidents, faster resolution times, reduced operational noise, and the ability to scale infrastructure without proportional increases in headcount. As portfolios grow and complexity increases, this becomes not just an advantage, but a necessity.

Looking ahead, the concept of the “self-driving data center” is no longer theoretical. With the right combination of predictive insight, causal understanding, and agentic execution, implemented with strong governance and safety controls, operations teams can run facilities that continuously learn, adapt, and improve.

Organizations exploring this shift are beginning to evaluate platforms that combine predictive, causal, and agentic capabilities into a unified operational model. One emerging approach is applying these capabilities at the front line of operations, such as L1 or NOC environments, where AI can reduce noise, provide real-time context, and guide or automate initial response.

In this model, the role of the operator evolves. Instead of reacting to alarms, teams oversee systems that anticipate risk, act at machine speed, and deliver consistent, reliable performance across increasingly complex environments.

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About the Author

Casey Kindiger is the Founder and CEO of Grokstream, where he is driving the next wave of AI-driven IT operations through a neuroscience-inspired approach to automation and prediction. A serial entrepreneur with more than 25 years of experience in enterprise IT, Casey previously founded and led gen-E and Resolve Systems as President and CEO and earlier built the consulting practice at Tidal Software as Vice President of Consulting Services.

At Grokstream, Casey established a strategic partnership with Numenta to apply cutting-edge neuroscience research, continuing to advance cognitive learning principles in the development of Grok, a self-healing AI platform that reduces alert noise, identifies root causes in real time, and enables predictive and agentic operations at scale.

His vision for cognitive AI has positioned Grokstream as an award-winning disruptor in the evolving operations market.

The post From Monitoring to Autonomy: How Predictive and Agentic AI Is Transforming Data Center Operations appeared first on Data Center POST.

TL;DR

• Rising Densities Dictate Design: As rack densities surge to 50–100kW and beyond to support high-performance computing, cooling decisions can no longer be an afterthought; they must be integrated early because they fundamentally influence the entire data centre layout, structural loading, and plant space.
• The Shift to Liquid and Hybrid Solutions: Traditional air cooling becomes difficult to manage beyond roughly 15–25kW per rack, driving the adoption of direct-to-chip liquid cooling and carefully zoned hybrid environments that mix both air and liquid cooling to retain flexibility.
• Critical Water vs. Power Trade-offs: Developers must balance Power Usage Effectiveness (PUE) against Water Usage Effectiveness (WUE), carefully evaluating local water availability, discharge constraints, and the added maintenance requirements of water-based systems.

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Cooling strategy is becoming one of the earliest design decisions in high-density data centre projects, as rack densities rise and operators look for systems that can support different workloads within the same facility.

The issue is no longer limited to choosing between air and liquid cooling. Designers need to decide when a cooling approach should be fixed, how much flexibility can be retained during early design, and what operational requirements will be introduced once more advanced systems are built into the facility.

Rack-level heat density is increasing as data centres support more high-performance computing, including GPU-based infrastructure and other accelerated workloads. Traditional enterprise and cloud environments have commonly operated at around 5–15kW per rack, while higher-density requirements are now regularly moving to 30kW and above, with some reaching 50–100kW per rack and beyond.

Once that level of power and heat is concentrated into a smaller footprint, cooling begins to influence the wider building design. Data hall layout, plant space, technical corridors, structural loading, distribution routes, commissioning and long-term asset flexibility all become affected by the cooling route selected.

Air-based systems remain important for lower-density environments. Below around 15–20kW per rack, fan wall units, computer room air handlers (CRAHs) and hot/cold aisle containment continue to support many facilities effectively, with dry air or evaporative heat rejection used depending on the site and climate.

There is no fixed threshold at which air cooling stops being viable. Local climate, energy restrictions, site constraints, CapEx and OpEx priorities all influence the decision, as does the level of future flexibility the operator needs to preserve. In many data centre applications, however, air-based cooling begins to become less attractive once power densities move beyond roughly 15–25kW per rack.

Across a typical row of 24–40 racks, that can equate to around 600kW. At this level, the air volumes required become harder to manage without compromising spatial efficiency, while air velocity through racks, pressure losses, fan energy, noise and uneven air distribution all become more difficult to control.

Air cooling can often still be engineered at these densities, but the question is whether it remains the best use of space, power and capital once the wider building constraints are taken into account.

For high-density environments, direct-to-chip liquid cooling is currently the most widely adopted liquid-based approach. By removing heat closer to the source, it reduces reliance on moving large volumes of air through the data hall, which is why cooling distribution units and technology water loops are now being considered much earlier on projects where high-density zones are expected.

Immersion cooling offers strong heat transfer performance, although it is not yet being adopted at the same scale in conventional commercial data centre projects. Its use often requires changes to operational procedures, maintenance practices and supply chains, making direct-to-chip a more practical route for many operators at present.

Hybrid cooling strategies are becoming more common as operators try to retain flexibility across the data hall. These allow lower-density air-cooled loads and higher-density liquid-cooled loads to sit within the same facility, which matters while customer requirements, hardware roadmaps and cooling technologies are still developing.

A hybrid hall cannot be treated as a conventional hall with liquid cooling added in selected areas. High-density zones need to be deliberately planned, with cooling and power infrastructure concentrated in the right locations. Cooling distribution units and technology water loops serve the liquid-cooled zones, while air-based systems support lower-density rows.

This zoning is determined by hall geometry, airflow distribution, resilience requirements and the ability to maintain operating temperatures during failure conditions. Computational fluid dynamics modeling now needs to inform the design earlier, helping teams test normal and failure scenarios, including outages affecting CRAHs or fan wall units.

During due diligence and early RIBA Stage 2, the priority is usually to keep options open. Design teams will assess a range of cooling approaches across a broad vendor base, often allowing for the most onerous equipment footprints and plant replacement requirements so the scheme remains vendor-agnostic for as long as practical.

That flexibility has to narrow before detailed design. By the end of RIBA Stage 2, the cooling approach needs to be fixed if the project is to progress with confidence. The chosen system determines plant allocations, technical corridors, primary distribution routes, structural design loadings and permitting requirements.

Leaving the decision too late can appear to preserve options, but it often increases the risk of redesign once other systems are fixed. In high-density facilities, cooling is too closely linked to the physical and operational model of the building to be treated as a late-stage package decision.

Water use also influences the choice of system. From a thermal perspective, water is an effective medium for heat transfer and can help reduce mechanical cooling loads and improve power usage effectiveness. That does not mean water-based heat rejection is always the right answer.

Developers increasingly have to balance power usage effectiveness against water usage effectiveness. Water availability, abstraction limits, discharge constraints, local climate, access to potable or non-potable water and the potential for rainwater harvesting all affect whether water-based heat rejection is viable. In water-scarce locations, every cubic metre of water use may need to be justified.

Operational and public health factors also need to be considered. Adiabatic and evaporative systems can support efficiency, but they introduce maintenance requirements, including water treatment and legionella control. In some locations, modern air-cooled chillers and dry air coolers, particularly those using free cooling and magnetic bearing compressors, may offer a more appropriate balance between efficiency, resilience and water use.

Where some water availability exists, hybrid air and evaporative systems can provide a useful compromise. These systems can operate in dry mode for much of the year and use water during peak ambient conditions, balancing energy and water performance rather than optimising one metric at the expense of the other.

Liquid cooling brings further design, installation and operational considerations. Leakage remains an obvious concern, particularly where distribution systems or components are not installed and maintained correctly. Installation quality becomes more important, and contractors and operations teams need the right training to manage coolant systems, cooling distribution units and distribution networks.

Compared with conventional air-cooled environments, there is also limited operational field experience. As more high-density data centres enter service, operating teams are likely to influence future system design more strongly, particularly around access, maintenance, isolation, monitoring and coolant management.

Standardisation remains another constraint. Direct-to-chip cooling is becoming more established, but vendor approaches still vary, creating integration challenges and increasing the risk of lock-in if flexibility is not protected during design and procurement.

Cooling strategy now affects technical performance, programme, water use, operational readiness and long-term asset value. The decision is no longer based only on which technology removes heat most efficiently. It is about selecting an approach that allows the facility to support higher densities without reducing resilience, limiting future adaptation or introducing operational issues that have not been fully accounted for.

As rack densities increase, advanced cooling technologies will form a larger part of the design response. Projects that retain flexibility during early design, while fixing the cooling strategy before detailed design, will be better placed to protect programme, resilience and long-term asset value.

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About the Author

Aurore Knight is an Associate Director at Black and White Engineering based out of our European headquarters in Newcastle. Her primary responsibilities as Associate Director include project delivery, design management, client liaison and technical quality assurance. She has an MSc in Building Services Engineering with Renewable Energy, is a Chartered Engineer with the Engineering Council UK and is a member of the Chartered Institute of Building Services Engineers (CIBSE).

She has worked extensively across the UK, Middle East and Europe since 2007. Aurore was part of the founding team of Black & White when operations started in August 2014.

Aurore has worked on projects in a wide range of sectors including education, healthcare, commercial, hospitality, super high-rise and mixed-use developments. During her time at Black & White, she has developed into a data centre specialist and has worked on many projects throughout Europe.

She has experience not only in leading mechanical designs but also leading full MEP and CSA design teams. Aurore has worked with a range of data centre clients, leading designs all the way from site due diligence through to construction. She has a practical approach to design and a proven record of delivering complex projects. She strives to maintain positive working relationships using a collaborative approach to problem solving.

The post Advanced Cooling Technologies Are Changing Data Centre Design Decisions appeared first on Data Center POST.

TL;DR

• FiberLocator will debut its next-generation fiber intelligence platform in July 2026, with an exclusive preview at ITW 2026.
• The updated platform introduces enhanced performance, scalable tiered offerings and expanded API and download capabilities.
• FiberLocator expanded its direct-source data integrations to provide more detailed and actionable fiber network intelligence.
• The platform is designed to support carriers, enterprises, infrastructure investors and network planners navigating increasingly complex connectivity environments.

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As global demand for connectivity infrastructure continues to accelerate, access to accurate and actionable fiber intelligence is becoming increasingly important for carriers, enterprises, infrastructure investors and network planners. To support these evolving requirements, FiberLocator has announced the upcoming launch of its next-generation platform, designed to provide faster performance, expanded data access and more flexible solutions for users operating in increasingly complex network environments.

The new platform, scheduled for public release in July 2026, will be previewed during International Telecoms Week (ITW) where attendees can meet with the FiberLocator team at Meeting Room 3-164 and Meeting Table B2 for an early look at the enhanced capabilities. The announcement comes at a time when organizations across the U.S., EMEA, and Latin America are seeking more efficient ways to evaluate connectivity options, identify fiber routes and support data center and network expansion initiatives.

According to FiberLocator, the updated platform introduces significant performance enhancements alongside new tiered product offerings tailored to a wider range of users. The company has expanded its platform to better support organizations ranging from enterprise network planners and carriers to infrastructure developers and investors, allowing customers to select the level of functionality and data access that best aligns with their operational requirements.

A key enhancement to the platform includes expanded download and API capabilities intended to support advanced analytics and third-party integrations. As network planning becomes increasingly data-driven, these tools are expected to provide users with greater flexibility when evaluating routes, analyzing infrastructure opportunities and integrating fiber intelligence into broader planning workflows.

FiberLocator has also expanded the depth and breadth of its data sources to deliver more detailed and solution-oriented insights. By sourcing information directly from providers, the company continues to focus on delivering transparent and accurate fiber intelligence designed to simplify decision-making for network operators and infrastructure stakeholders.

The launch also reflects broader industry trends shaping the digital infrastructure sector. As AI workloads, cloud expansion, edge deployments and hyperscale connectivity continue to drive demand for bandwidth and low-latency infrastructure, access to reliable fiber intelligence is becoming increasingly important in site selection, network expansion and infrastructure investment strategies.

For data center operators, carriers, and enterprises, the ability to identify available fiber assets and connectivity opportunities can significantly impact deployment timelines, scalability and long-term operational planning. Enhanced visibility into global network infrastructure is also becoming more critical as organizations evaluate emerging markets and expansion opportunities outside traditional Tier 1 hubs.

FiberLocator’s latest platform enhancements position the company to support these evolving requirements through a combination of direct-source data, scalable functionality and flexible access options designed to meet the needs of a diverse global customer base.

Industry attendees interested in previewing the platform during ITW 2026 are encouraged to schedule a meeting with the FiberLocator team to learn more about the new capabilities and upcoming launch.

To learn more about FiberLocator, visit www.fiberlocator.com.

The post FiberLocator Expands Fiber Intelligence Capabilities Ahead of ITW 2026 appeared first on Data Center POST.

TL;DR

• AI is already embedded in hyperscale data center program management — synthesizing portfolio data, generating risk briefings, and driving capital decisions across portfolios of 50 or more active construction sites simultaneously.
• Unlike AI in financial services, healthcare, or aviation, data center program management AI operates with no external governance framework, no auditability standards, and no defined accountability structures.
• The industry needs an AI governance framework built on four pillars: auditability of AI-generated decisions, risk-based oversight design, data governance for sensitive infrastructure intelligence, and clear accountability structures.
• Organizations like the Uptime Institute and the Project Management Institute are well positioned to lead this work — and the industry does not need to wait for regulatory intervention to begin.

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The data center industry is in the middle of the most consequential infrastructure build cycle in modern history. Hundreds of billions of dollars in capital investment. Hundreds of active construction sites across every major market simultaneously. Power grids strained. Permitting systems overwhelmed. Labor markets stretched thin.

And increasingly, the program operations managing all of this are being run — at least in part — by AI.

Large language models now synthesize portfolio data, generate executive briefings, flag risk conditions in construction timelines, and accelerate decision-making for the technical program managers who orchestrate these massive programs. This is not a future scenario. It is the present reality of how hyperscale infrastructure is being built and operated today.

What is notably absent from this reality is any governance framework designed specifically for it.

The Governance Gap Nobody Is Talking About

When AI is deployed in financial services, it faces regulatory scrutiny. When it is deployed in healthcare, it faces auditability requirements. When it is deployed in aviation, it faces rigorous certification standards. When AI is deployed to manage a portfolio of data center programs — facilities that will house the compute powering global financial systems, healthcare records, and logistics networks for the next two decades — it operates with essentially no external governance requirement whatsoever.

This is not a theoretical concern. It is a live operational reality with downstream consequences that the industry has not yet seriously engaged with. Consider three specific governance failures already materializing across hyperscale programs:

• AI-generated recommendations flow into capital decisions without documented reasoning or defined accountability for outcomes.
• Automation bias goes unmanaged in high-pressure, high-volume environments where program managers handle 30, 50, or more active sites simultaneously.
• Sensitive infrastructure intelligence — facility locations, power capacity commitments, security posture data — is ingested by AI systems governed only by internal policy, with no industry-wide standards for access control or data retention.

A Framework Built on Four Pillars

The data center sector has mature frameworks for physical security, power redundancy, environmental compliance, and construction safety. It needs equivalent standards for the AI systems now embedded in program operations. Four pillars provide the foundation:

• Auditability — Every AI-generated decision in a critical program context should be logged, reviewable, and traceable to source data. AI systems must produce decision records as a standard output, not as an afterthought.
• Oversight Design — Human review requirements should be defined by risk class. A schedule optimization warrants different oversight than an AI-generated risk assessment informing a site acquisition decision. Glancing at a briefing and approving it is not oversight.
• Data Governance — Sensitive infrastructure data ingested by AI platforms — facility locations, power commitments, security posture — should be subject to explicit classification, access controls, and retention standards. Organizations should require vendors to answer: who has access, and is this data used to train the model?
• Accountability Structures — Clear chains of accountability for AI-influenced outcomes should be documented as part of standard program governance. When a flawed AI recommendation drives a capital write-down or a delayed program, the organization needs to know who was responsible and what they knew.

How the Industry Can Move Forward

The Uptime Institute, the Project Management Institute, and infrastructure industry associations already set operational standards for data center programs. They are the natural home for this work — and they do not need to wait for regulatory intervention to begin. A working group focused on minimum requirements for AI auditability, oversight, data governance, and accountability would give the industry a foundation it can implement immediately.

The facilities being built today will define the digital economy for decades. The AI managing those programs deserves governance frameworks commensurate with that responsibility.

Conclusion

Hyperscale data center AI is a present operational reality, not a future consideration. The governance vacuum is real, consequential, and addressable without waiting for regulators or high-profile failures. The industry needs a working group, a baseline framework, and the will to treat AI governance as seriously as it treats power redundancy. The infrastructure is too important for anything less.

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About the Author

Sanchita Hosur is a Technical Program & Product Leader with 12+ years of experience in global data center infrastructure, AI-powered program operations, and enterprise technology delivery. She has led AI platform programs serving 200+ global stakeholders across hyperscale infrastructure portfolios spanning AMER, EMEA, and APJC. Her research focuses on AI governance frameworks for critical infrastructure program management. She holds an MS in Technology Management from the University of Illinois Urbana-Champaign and a BE in Electrical & Electronics Engineering from Visvesvaraya Technological University.

The post When AI Manages Infrastructure: The Case for a Data Center AI Governance Framework appeared first on Data Center POST.

TL;DR

• AI infrastructure strategy is shifting from centralized training environments toward distributed inference deployments that require lower latency, regional proximity and edge connectivity.
• Power availability remains a major obstacle, but policy, permitting, and community engagement are emerging as equally important factors influencing where and how projects move forward.
• Workforce shortages and supply chain limitations involving transformers, turbines, fiber and construction labor are creating new execution risks, even as capital investment in digital infrastructure continues to accelerate.
• Connectivity and interconnection density may become as critical to the future of AI as power itself, particularly as AI-generated data volumes increase and inference workloads expand across distributed environments.

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At the recent  IMN Data Centers Private Equity East 2026 and Investor Forum held at the Union League Club in NYC, one conversation stood apart from the recurring themes of capital deployment, land acquisition and power procurement. Instead of simply asking how fast the industry can build, or how do we overcome barriers like power and community, the panel, moderated by Ilissa Miller, CEO of iMiller Public Relations, challenged the executive and investor attendees to consider a more fundamental question: Are we building the right infrastructure for the future of AI?

The panel titled “The Data Center Industry Future: Technology, Power, Government & The Kind of Opportunities That Will Be Created,” brought together leaders from operations, investment advisory, market intelligence and infrastructure development to discuss the rapidly changing future of digital infrastructure. The esteemed panelists included:  Bob DeSantis, Co-Founder and Board Member at 365 Data Centers; Daniel Watts, CEO at US Signal; Benton Erwin, Principal at Arup; Colby Cox, Managing Director – Americas at DC Byte, and Goncalo Bernardo, Investment Partner at Palistar Capital.

The discussion quickly evolved beyond traditional conversations around hyperscale growth and into deeper questions about LLMs, AI inference, distributed infrastructure, Agentic AI, policy friction, workforce shortages, and whether the market is overbuilding for the wrong model of compute.

The Industry’s Biggest Miscalculation: Assuming Bigger is Better

Opening the panel, Miller framed the conversation around a thesis that resonated throughout the session,“the question isn’t just can we build fast enough. It’s whether we’re building the right things for the future.”

That framing became especially relevant as panelists discussed the shift from AI training infrastructure toward AI inference infrastructure, a distinction many outside the industry still misunderstand.

Today’s massive gigawatt-scale AI campuses are largely designed around training large language models (LLMs). And, the future economic opportunity may lie in inference, the real-time deployment and operational use of AI applications closer to users, enterprises and machines.

Watts explained the difference succinctly, “Inference is just where you leverage the model your computer creates… and that’s why that market is so massive.”

The implication is significant. Training can happen in concentrated hyperscale environments. Inference, however, requires low latency, geographic distribution and proximity to users and enterprise systems. That changes everything.

The Rise of Distributed Infrastructure

One of the strongest themes throughout the discussion was that the next generation of infrastructure may not be dominated solely by mega campuses, but by distributed networks of smaller, strategically placed facilities.

Cox argued that inference “brings edge to reality,” noting that the market may evolve toward “a distributed network” of smaller deployments rather than only centralized hyperscale campuses.

Similarly, Cox observed that enterprise customers are already demanding higher density deployments in edge facilities closer to population centers, “There are demands now for doubling commits during the term of a five-year contract, and they’re doing it… primarily [in] edge data centers, meaning data centers that are close to population centers, close to users and subscribers.”

This shift could reshape everything from investment models and site selection to permitting strategies and community engagement. It also reframes the future role of existing regional and edge operators.

Power is Still King and Policy May Become the Bigger Constraint

The panel confirmed what many in the industry already know: power availability remains the primary bottleneck. And, several panelists emphasized that policy, permitting and community resistance are rapidly becoming equally critical constraints.

According to Cox, “The conversations that I’m having with private equity… [are] not just ‘where can I find power,’ but ‘where can I find power under today’s policy?’” He further warned that communities are mobilizing faster against projects, often before developers establish a local narrative or educational framework.

That observation aligns closely with the growing industry need for proactive community engagement and digital infrastructure education, particularly as public scrutiny around power, water, land use and AI accelerates nationwide. And is near and dear to Miller’s practice at her firm, where she offers a Groundswell™ community engagement program. This sentiment was reinforced by Watts, who emphasized that “part of our job as an industry… [is] educating people.”

The panel also acknowledged that misconceptions continue to dominate public discourse, especially around water use, environmental impact and economic value creation.

Workforce and Supply Chain Pressures Are Intensifying

While power dominated much of the conversation, panelists repeatedly returned to workforce shortages and supply chain constraints as looming challenges.

Colby described the workforce challenge as a “massive problem,” explaining that customers are now evaluating engineering firms, contractors and development partners based not only on expertise, but on whether they actually have labor availability to execute projects.

Meanwhile, Bernardo warned that the industry is simultaneously scrambling for available transformers, turbines, fiber infrastructure and broader supply chain ecosystems. The discussion highlighted an uncomfortable reality, even if capital and demand remain abundant, physical execution capacity may become the limiting factor.

Are We Assuming the Future will be Mission-Critical, as such, are we Overbuilding for “Five Nines”?

Another provocative topic centered around whether the industry is designing infrastructure for a world that no longer needs the five nines guarantees. Historically, data center design has prioritized “five nines” reliability, near-perfect uptime standards built for centralized enterprise architectures.

But AI inference and distributed compute may require a different model.

Panelists questioned whether future infrastructure needs to be centralized or whether resiliency itself may become distributed. The conversation suggested that future architectures could prioritize flexibility, modularity and geographic distribution over singular perfection.

That shift could fundamentally alter capital allocation strategies and infrastructure design philosophies over the next decade.

Connectivity May Become the Most Underestimated Constraint

As the panel concluded, Miller asked each speaker what the industry is underestimating today that will matter most in five years.

DeSantis pointed toward connectivity,“bandwidth for network capabilities are going to be way below the needs for AI.” As AI-generated datasets become exponentially larger, the conversation around infrastructure may increasingly shift from simple power availability to network transport capability and interconnection density.

In other words: the future AI economy may depend just as much on fiber and connectivity as it does on megawatts.

Final Thought: The Industry is Entering Its Next Phase

The panel made one thing abundantly clear: the digital infrastructure industry is no longer simply expanding, it is evolving, and it must evolve to meet local demands, manage resources and commit to industry promises like sustainability commitments. .

The next wave of opportunity may not belong exclusively to the largest campuses or the biggest power procurements. It may belong to the operators, investors, communities and policymakers who understand how AI inference, distributed infrastructure, connectivity and public trust intersect.

As Miller concluded during the session, “hopefully you learned something a little bit different… Are we building for the right or wrong future?”

To learn more about IMN, visit www.imn.org.

To find out how iMiller Public Relations can help you navigate communications around digital infrastructure investments, visit www.imillerpr.com.

The post Are We Building for the Right Future? Key Takeaways from the IMN NYC Data Center Investment Forum appeared first on Data Center POST.

TL;DR

• Open house announced: Duos Edge AI will host a Victoria open house on May 14 to showcase its newly operational Edge Data Center.
• Built for the community: The facility supports 37 school districts across the Region 3 footprint alongside AI, network, and disaster recovery needs.
• Bigger regional impact: The project strengthens Duos’ edge infrastructure footprint and supports digital growth in the region.

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Duos Technologies Group Inc. (Nasdaq: DUOT), through Duos Edge AI, Inc., has announced the deployment of a newly operational Edge Data Center in Victoria, Texas. The facility strengthens digital infrastructure in South Texas and supports carriers, enterprises, healthcare organizations, school districts, and other local users that need secure, low-latency computing closer to where data is created and consumed.

The Victoria Edge Data Center is positioned to serve as a regional communications hub supporting a range of modern connectivity and computing needs. The facility offers AI readiness, capacity for high-performance workloads, and resilient infrastructure for disaster recovery, while also serving as a dedicated resource for the 37 school districts within the Region 3 footprint. This deployment is another example of how Duos Edge AI is helping bridge the gap between rising digital demand and local capacity.

“Victoria and the Region 3 footprint are important markets for Duos Edge AI’s continued expansion,” said Doug Recker, CEO of Duos Edge AI and Duos Technologies Group, Inc. “This deployment brings high-availability, localized computing power closer to the schools, communities, carriers, and industries that need it. We are proud to help strengthen the digital infrastructure supporting Victoria and the greater Region 3 community.”

Duos Edge AI will also host a Victoria open house to showcase the new facility and highlight the role edge data centers can play in supporting regional growth. Community leaders, education stakeholders, industry representatives, and partners will have an opportunity to tour the site and learn more about the company’s edge infrastructure approach.

To learn more about Duos Edge AI and register for the open house, visit freeevite.com/event.php?e=2oda7vpQtUHp_cNcaHL3yA.

The post Duos Edge AI to Host Victoria Edge Data Center Open House appeared first on Data Center POST.

TL;DR

• Historical Secrecy Drives Distrust: The digital infrastructure sector has traditionally prioritized confidentiality for valid competitive and security reasons, which inadvertently created a narrative vacuum and fostered public distrust.
• Vulnerability to Misinformation: In the absence of clear, unified communication, complex infrastructure realities are often reduced to emotional, binary debates, allowing polarized media and bad actors to spread misinformation and shape public perception before communities are properly informed.
• The Need for Collaborative Storytelling: Fragmented, independent messaging among developers, utilities, and local officials only reinforces confusion and delays projects. The industry must evolve from reactive silos toward intentional “narrative leadership”.

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Welcome to article #6 in my eight-part series. As infrastructure decisions move into more visible civic arenas, another dynamic becomes clear: the way the industry has historically communicated, or not communicated,  is influencing today’s trust environment. The tension between protecting competitive and security interests while building public understanding has created a messaging paradox that leaders must now navigate more intentionally. You can read the previous posts in my series here, to learn more.

Digital infrastructure has always operated in a complex environment.

On one hand, these facilities underpin financial systems, healthcare delivery, public services, national security operations, and the rapidly expanding AI economy. On the other, they are increasingly visible in local communities: physically, economically, and politically.

For many years, the industry navigated this tension by prioritizing protection.

Projects were often developed under code names. Incentive negotiations took place quietly. Site acquisitions moved quickly. Public education efforts were limited until late in the development process. Messaging varied widely across stakeholders, with each organization advancing its own narrative.

There were valid reasons for this approach.

Competition for land, power, and capital is intense. Security considerations are real. Market timing can determine whether projects succeed or fail. In many cases, confidentiality was not only strategic, it was necessary.

The industry has not done itself any favors. We operated in secrecy for good reasons, but it created distrust. An unintended consequence to connecting the world in secrecy.

In the absence of clear, consistent, and collaborative communication, a narrative vacuum emerged. And narrative vacuums rarely stay empty for long.

Today, misinformation can spread faster than technical clarification. And, with a global race for AI-dominance, global bad actors spreading misinformation can easily derail a nation’s momentum toward dominance. Advocacy groups and polarized media environments often shape public perception before communities have access to balanced information. Complex issues are reduced to binary debates. Emotional framing replaces nuanced understanding.

The paradox we work with is that it’s easy to frame the issues as black and white, but digital infrastructure is complex. It is both necessary and challenging. The uncomfortable middle is where communities are being forced to navigate without guidance and frameworks to empower them toward decisions that, otherwise, could seem uncomfortable.

Infrastructure development brings economic opportunity, innovation, and regional competitiveness. It also raises legitimate questions about sustainability, resource use, and long-term community impact. Holding these realities together requires maturity,  from industry leaders, policymakers, and the public alike.

Yet fragmented messaging continues to complicate the landscape. Coupled with emotions such as fear, distrust and a global race for technology (AI) dominance, we’re in a real quagmire here. If we can’t rely on our own truths, whose can we rely on?

Individual developers, utilities, technology firms, and local officials often communicate independently rather than collaboratively. Without shared frameworks or coordinated storytelling, stakeholders can unintentionally reinforce confusion or mistrust. And, that’s not without global interference from others looking to derail the United States’ own national policies.

The result is not just delayed projects. It is a broader erosion of confidence in the processes guiding infrastructure expansion.

This is why we need collaboration. The industry must evolve from reactive communication toward intentional narrative leadership. We cannot solve the digital revolution in silos.

Collaborative storytelling does not mean uniform messaging or suppressing debate. It means aligning around core principles such as: transparency where possible, clarity around trade-offs, and consistent education that empowers communities to engage meaningfully in decision-making.

It also means recognizing that infrastructure conversations are no longer purely technical or transactional. They are civic conversations. They involve identity, economic aspirations, environmental values, and political accountability.

Organizations that can translate complexity into accessible context will play an increasingly important role in shaping how digital infrastructure is understood and evaluated.

At iMiller Public Relations, we often describe this work as narrative architecture. It is not simply about promoting projects. It is about building bridges between industry expertise and community perspective, creating space for informed dialogue rather than polarized reaction.

Digital infrastructure will continue to expand. The question is whether the narratives surrounding that expansion will remain fragmented and reactive; or become collaborative, transparent, and strategically aligned with long-term societal goals.

Trust is not built overnight. But it can be rebuilt intentionally.

Learn more about what we are doing at iMiller Public Relations to bridge the gap between industry and community for the digital infrastructure sector, go to www.imillerpr.com.

For information about the OIX DIFC, visit www.oix.org/standards-and-certifications/oix-dif-standard.

The post Transparency vs Protection: The Digital Infrastructure Industry’s Messaging Paradox appeared first on Data Center POST.

TL;DR

• New deployment completed: Duos Edge AI launched its Corpus Christi Edge Data Center in South Texas.
• Built for local demand: The facility adds more than 450kW of critical IT load capacity for AI, network, and disaster recovery needs.
• Bigger regional impact: The project strengthens Duos’ edge infrastructure footprint and supports digital growth in the region.

# # #

Duos Technologies Group Inc. (Nasdaq: DUOT), through Duos Edge AI, Inc., has announced the deployment of a newly operational Edge Data Center in Corpus Christi, Texas. The facility strengthens digital infrastructure in South Texas and supports carriers, enterprises, healthcare organizations, and other local users that need secure, low-latency computing closer to where data is created and consumed.

The Corpus Christi deployment delivers more than 450kW of critical IT load capacity and is designed to support high-performance compute, network infrastructure, artificial intelligence workloads, and disaster recovery solutions. It also reflects Duos Edge AI’s broader strategy of expanding modular edge infrastructure into underserved and high-growth markets.

“This deployment represents another important step in our continued expansion across Texas,” said Doug Recker, CEO of Duos Edge AI and Duos Technologies Group, Inc. “By bringing high-availability computing power closer to the communities and industries that need it, we are helping strengthen the digital backbone of South Texas.”

The Corpus Christi Edge Data Center is positioned to serve as a regional communications hub supporting a range of modern connectivity and computing needs. The facility offers AI readiness, capacity for high-performance workloads, and resilient infrastructure for disaster recovery. This deployment is another example of how Duos Edge AI is helping bridge the gap between rising digital demand and local capacity.

Duos Edge AI will also host a Corpus Christi open house to showcase the new facility and highlight the role edge data centers can play in supporting regional growth. Community leaders, industry stakeholders, and partners will have an opportunity to tour the site and learn more about the company’s edge infrastructure approach.

To learn more about Duos Edge AI and register for the open house, visit freeevite.com/event.php?e=6jmQhOxF4THQ7V6B5ogfXw.

The post Duos Edge AI Expands South Texas Footprint with Corpus Christi Edge Data Center Deployment appeared first on Data Center POST.

TL;DR

• Broadband expansion is moving from planning to execution, bringing increased focus on BEAD funding distribution, state-level implementation strategies and the regulatory and operational challenges of large-scale deployment.
• AI is reshaping network design, deployment and operations, driving demand for scalable, low-latency infrastructure while enabling greater automation and efficiency across service delivery.
• Fiber remains the backbone of connectivity, supported by a mix of technologies including fixed wireless, satellite and 5G, with open access models and partnerships helping expand coverage and improve long-term economic outcomes.

# # #

Connected America 2026 brought together the broadband and digital infrastructure community in Dallas, Texas, April 14–15, convening more than 1,500 connectivity leaders and over 175 speakers from across telecom, policy, investment and technology. Through two days of keynote sessions, panels and networking discussions, the event focused on how the industry is evolving to support next-generation broadband, AI-driven networks and nationwide connectivity expansion, while highlighting the growing importance of collaboration between public and private stakeholders as the U.S. works to modernize its digital infrastructure.

A key highlight of the event was participation from Ilissa Miller, CEO of iMiller Public Relations (iMPR). Ilissa spoke on the panel “From Resistance to Readiness: Why Communities Need a Digital Infrastructure Framework,” where she addressed the importance of aligning developers, policymakers and local communities through structured frameworks that prioritize transparency, education and long-term planning. Her participation reinforced iMPR’s ongoing role in shaping industry dialogue around responsible infrastructure development and community engagement.

Broadband expansion and policy were central themes throughout the event. Multiple sessions explored the progress and challenges associated with the Broadband Equity, Access, and Deployment (BEAD) program, including how states are balancing federal requirements with local implementation strategies and how funding is being deployed to close connectivity gaps. As broadband initiatives move from planning to execution, discussions highlighted the operational and regulatory complexities shaping large-scale deployment efforts.

Artificial intelligence and next-generation networks also played a major role in shaping the conversation. Industry leaders examined how AI is transforming network design, deployment and performance, while also increasing demand for scalable, low-latency infrastructure. Sachin Gupta, SVP & GM of Application Platforms & Services at Comcast, discussed how AI and automation are transforming network operations and enabling more efficient service delivery at scale.

Fiber infrastructure remained a foundational topic throughout the agenda. Keynotes and panels addressed the continued expansion of fiber networks, the economics of overbuild and return on investment, and how operators are leveraging AI to optimize fiber deployment and maintenance. At the same time, discussions around middle-mile infrastructure emphasized the importance of building scalable backbone networks to support last-mile connectivity and nationwide coverage.Sessions explored how technologies such as fiber, fixed wireless, satellite and 5G will work together to deliver resilient, high-capacity networks capable of supporting future workloads.

Stephen Rose, CEO of Render Networks, highlighted the role of digitization in accelerating fiber deployment and improving construction outcomes. Executives from IQGeo emphasized how geospatial intelligence and real-time network visibility are supporting more resilient and adaptive infrastructure planning.

Additional discussions featured leaders from UTOPIA Fiber and the Community Broadband Action Network, who explored how open access models and collaborative infrastructure strategies are shaping deployment across U.S. markets. Panels focused on how municipalities and private operators can work together to expand broadband access, improve competition and deliver long-term economic value to underserved communities.

Beyond infrastructure, the event also provided a platform for broader industry engagement, including meetings between operators, investors and technology providers exploring partnership opportunities, project development and market expansion. These interactions are critical to advancing the next phase of broadband deployment and reinforcing Connected America’s role as a key convening point for the industry.

Looking ahead, Connected America continues to serve as a critical platform for advancing broadband policy, investment and infrastructure development. As deployment accelerates and technologies evolve, the event remains a central forum for shaping how the United States builds and scales the next generation of digital infrastructure.

To learn more about Connected America and stay updated on future announcements, visit the official event website and explore opportunities to participate in upcoming programs.

The post Connected America 2026 Focuses on Broadband Deployment, Policy and the Path to Nationwide Connectivity appeared first on Data Center POST.

TL;DR

• Strategic Partnership Launch: 365 Data Centers teams with Aphorio Carter to develop 200 MW of AI-ready, high-density data centers in key U.S. markets like Colorado and Kentucky.
• Rapid Deployment Focus: Facilities support 50-200+ kW liquid-to-chip cooling, with initial sites online in 9-24 months via asset conversions – faster than traditional builds.
• Leadership Synergy: Combines Aphorio’s $6B real estate expertise with 365’s operations for accelerated AI infrastructure delivery.
• AI Market Impact: Addresses surging demand for high-performance computing, positioning both for enterprise growth in the AI era.

# # #

365 Data Centers has unveiled a powerhouse partnership with Aphorio Carter to unleash about 200 megawatts of cutting-edge, AI-ready data center capacity. This strategic alliance targets high-demand U.S. sites, transforming existing assets into high-density hubs for next-gen computing workloads.

The move comes at a pivotal moment for the data center industry, where exploding AI demands are straining power and infrastructure. 365, a leader in high-density colocation and AI-enabled cloud services, has teamed up with Aphorio Carter – the data center arm of Carter Funds – to scout, convert, and operate facilities optimized for liquid-to-chip cooling and densities from 50 to over 200 kW per cabinet. Initial letters of intent are already in motion for priority spots in Aurora, Colorado, and Simpsonville, Kentucky, with more lined up in Trumbull, Connecticut; Louisville, Kentucky; Harrisonburg, Virginia; and Columbus, Ohio.

A Perfect Match Fuels Rapid Deployment

Derek Gillespie, CEO and CRO of 365 Data Centers, calls it a game-changer: “Through this partnership, we’re in an ideal position to create a new class of high-density infrastructure designed specifically for AI-era workloads.”

John Regan, President and COO at Aphorio Carter, echoes the synergy, stating, “We’ve aligned the delivery of utility power with critical infrastructure, allowing us to provide scalable, high-density infrastructure where it’s needed most.” Projects are slated to go live in nine to 24 months, prioritizing power-rich environments that outpace traditional builds.

This strategic collaboration serves as a blueprint for the AI future. 365’s platform already converges colocation, connectivity, and cloud with AI, ensuring clients get scalable, sovereign solutions. Aphorio Carter brings over $5.5 billion in data center experience, targeting institutional investors eager for growth in this high-stakes asset class.

Why This Matters for AI and Beyond

Operators today face intense pressure to deliver speed and scale. This recently announced pipeline positions 365 to power AI for enterprise while maximizing asset value through redevelopment. These facilities promise to bridge the capacity gap, enabling breakthroughs in high-performance computing. For more information, explore 365 Data Centers or Aphorio Carter.

The post 365 Data Centers and Aphorio Carter Ignite 200 MW AI Data Center Boom Across U.S. Markets appeared first on Data Center POST.

TL;DR

• Community alignment is now a critical factor influencing data center permitting timelines and project success.
• Public perception, environmental concerns, and policy dynamics are reshaping how digital infrastructure projects are evaluated.
• Clear communication and structured frameworks are essential to help communities make informed decisions.
• Demonstrating measurable local benefits, such as economic development and infrastructure investment, is key to building trust and advancing projects.

# # #

Data center growth is colliding with a new set of realities that extend well beyond land and power.  What was once driven by access to land, power, and capital is now increasingly shaped by community alignment. At ITW 2026, this shift will take center stage as industry leaders examine how public perception, policy dynamics, and local engagement are influencing development timelines.

As demand accelerates, particularly with AI-driven workloads, developers are encountering new challenges. Projects are being evaluated not only on technical and financial viability, but also on environmental impact, water usage, and long-term community value. Permitting delays and opposition are often tied to uncertainty, reinforcing the need for clearer communication and more transparent planning.

A featured session, “Debunking the Data Center Misinformation Dilemma,” will address these issues on May 19, 2026 during the Digital Infrastructure Policy & Investment Summit. The panel will explore how public perception and policy pressures are shaping project timelines and what the industry must do to respond.

The discussion includes Ilissa Miller CEO at iMiller Public Relations (iMPR), who also serves on the board of OIX and leads its Digital Infrastructure Framework Committee (DIFC). She will be joined by Buddy Rizer of Loudoun County Department of Economic Development, Joanna Soucy of Aligned Data Centers, Holly Elwood of Global Electronics Council, and Kanan Joshi of CVC DIF. The session will be moderated by Chris Pumphrey of Signal Ventures GA, LLC.

At the core of the conversation is the need for better alignment between developers, policymakers, and communities. Many municipalities are being asked to evaluate complex infrastructure projects without consistent frameworks or accessible information, creating gaps that can slow progress.

The panel will highlight practical ways to improve transparency, align messaging, and demonstrate measurable community benefits such as economic development, education funding, and infrastructure investment. These approaches are increasingly critical as the industry works to build trust alongside capacity.

As digital infrastructure continues to scale, the ability to engage communities effectively is becoming a defining factor in project success. ITW 2026 offers a timely forum to advance that discussion and explore how the industry can move forward with greater clarity and confidence.

Read more in the press release.

To learn more about iMiller Public Relations, visit www.imillerpr.com. For information about the OIX DIFC, go to www.oix.org/standards-and-certifications/oix-dif-standard.

The post When Growth Meets Reality: Why Community Alignment Is Reshaping Data Center Development at ITW 2026 appeared first on Data Center POST.

Data Center POST had the opportunity to connect with Scott Yappen , a Senior Business Development Manager at Wärtsilä with over 20 years of experience providing data centers with on-site power solutions. He has extensive experience modeling AI load profiles and applying highly reliable power quality solutions using Wärtsilä’s scalable 10-20+ MW medium-speed reciprocating internal combustion engines (RICE), stored energy systems (BESS), and energy management control software (GEMS).

He also has career experience with gas turbines, fuel cells, solar PV, wind turbines, UPS, nuclear, combined heat and power (CHP), waste heat recovery, steam, and absorption cooling systems.  Scott is a certified data center energy practitioner (DCEP) and holds an M.S. Management of Technology degree from New York University and BBA from the University of Texas at Austin.

What does your company do?  

Wärtsilä Energy leads the transition to a 100% renewable energy future by providing flexible engine power plants, energy storage systems, and optimization software that accelerate decarbonization. We deliver fuel-efficient engine power plants that provide reliable, low-emission on-site power for data centers and other primary power needs.

What problems does Wärtsilä solve in the market? 

Across the United States, a once-in-a-generation surge in digital power demand is reshaping how energy infrastructure is planned, financed, and deployed. Data center growth, accelerated by AI, cloud expansion, and hyperscale development, is driving unprecedented pressure on grids, utilities, and developers. Wärtsilä is helping address this challenge by providing fast-to-market, firm, flexible power solutions, specifically reciprocating engines, that bridge delays in grid interconnection and support long-term operational resilience. Developers are increasingly turning to flexible engine-based solutions to ensure availability, avoid multi-year delays, and support new power demand models.

What are Wärtsilä’s core products or services?

Wärtsilä offers reliable, efficient, and low-emissions technology for on-site data center power supply. Wärtsilä engine power plants form an off-grid system that offers reliable, fuel-efficient, sustainable, and future-proof primary power. Our power plants consist of 10-20+ MW engines that can provide 750+ MW of power.

What markets do you serve?

Wärtsilä primarily serves the global energy and marine markets, providing advanced technologies, lifecycle solutions, and services focused on decarbonization. Key segments include power plant technologies, energy storage, marine propulsion, and ship-related services for commercial and industrial customers worldwide.

What challenges does the global digital infrastructure industry face today?

Revenue for AI data centers is limited by access and speed to power. Traditional utility grid power supply may not be available at the scale demanded or in the timeframe required.  Other challenges include mitigating risks related to power output reliability, load volatility, CapEx and OpEx cost control, and ensuring equipment performance to guarantee ROI. Off-grid solutions such as Wärtsilä RICE are filling the power imbalance and solving these challenges.

How is Wärtsilä adapting to these challenges?

Wärtsilä has expanded its RICE offerings to data center developers, recently marking the first use of the company’s highly proven 34SG model in a data center application. Currently, our engines offer modular scalability for 100-750+ MW.  In less than one year, Wärtsilä has announced five major U.S. data center-related orders, totaling 2.4 GW of power capacity:

• April 2026: 790 MW order in Texas, the next Data Center Alley
• April 2026: 412 MW of engine power to support a major new hyperscale data center project in Ohio
• January 2026: 429 MW for a power plant serving a data center, owned and operated by a U.S. investor-owned utility
• November 2025: 507 MW for a U.S. data center project
• July 2025: 282 MW for a new Ohio data center project

What are Wärtsilä’s key differentiators?

Data center developers are increasingly turning to flexible engine‑based solutions to ensure availability, avoid multi‑year delays, and support new power‑demand models. Wärtsilä’s modular engine plants operate with extremely high reliability, scaling rapidly as data‑center loads grow. They ramp quickly, use significantly less water and fuel than many traditional alternatives, and offer a dependable foundation at a time when power continuity is non‑negotiable for AI and cloud operators.

Wärtsilä off-grid and near-grid engine solutions are engineered for future fuel readiness. Engines run on natural gas today and can be converted to sustainable fuels, including synthetic methane and biobased alternatives, as they become commercially viable. This positions data center operators to lower emissions over time while maintaining cost-efficient operations.

Independent analysis, including reports from Ascend Analytics and Charles River Associates,  shows that RICE plants deliver superior flexibility, economics, and firm capacity value compared to gas turbines in U.S. markets such as ERCOT. With turbine pricing rising and supply chains tightening, engine‑based power plants have become more competitive, more efficient, and more adaptable.

What can we expect to see from Wärtsilä in the future? 

We intend to significantly grow our delivery capacity for data center engines, particularly in the U.S. market, which is home to around half the world’s data centers. Growth in this industry is expected to surge over the next few years as companies race to scale computing power. Engine-based solutions will remain a cornerstone for fast, reliable, and sustainable power.  They’ll continue to be the go-to solution because of their efficiency, modular design, heat tolerance, low emissions, minimal water use, and operational flexibility.

What upcoming industry events will you be attending?

In 2026, you can find our team at several major data‑center and digital‑infrastructure events. We’ll be at Data Cloud USA in Austin, the Yotta event in Las Vegas, and the Data Center Power eXchange in Washington, DC. Our participation across these gatherings underscores our commitment to advancing data‑center power, infrastructure resilience, and next‑generation energy solutions.

Do you have any recent news you would like us to highlight?

• April 2026: Wärtsilä continues to expand its data center footprint with new 790 MW order in Texas, the next Data Center Alley
• April 2026: Wärtsilä’s 34SG engine makes its data center debut with new 412 MW U.S. project
• January 2026: Wärtsilä chosen for a major U.S. power plant project addressing critical energy demand driven by data center development
• November 2025: Wärtsilä continues growth in the data center segment with a 507 MW order in the US, offering engines as a reliable power solution
• July 2025: Wärtsilä will supply 282MW of flexible engines to operate a new data center project in Ohio, USA

Is there anything else you would like our readers to know about your company and capabilities?

Wärtsilä’s modular approach requires far less additional installed capacity to meet the stringent availability requirements of data centres. This translates into a more attractive CapEx and lifetime cost of energy relative to aeroderivative and combined-cycle gas turbines. Wärtsilä’s engine plants operate with extremely high reliability, scaling rapidly as data‑center loads grow. They ramp quickly, use significantly less water (due to closed-loop cooling) and fuel than many traditional alternatives, and offer a dependable foundation at a time when power continuity is non‑negotiable for AI and cloud operators. Wärtsilä’s off-grid and near-grid solutions are engineered for future fuel readiness. Engines run on natural gas today and can be converted to sustainable fuels, including synthetic methane and biobased alternatives, as they become commercially viable. This positions data center operators to reduce emissions over time while maintaining cost-efficient operations. Wärtsilä engine power plants offer data center developers reliable, fuel-efficient, sustainable, and future-proof primary power.

Where can our readers learn more about Wärtsilä? 

You can learn more about Wärtsilä at www.wartsila.com/energy/engine-power-plant-solutions/flexible-baseload-power-plants/data-center-power-solutions.

How can our readers contact Wärtsilä?

You can contact us on our website, www.wartsila.com/energy/area-expertise/americas.

# # #

About Wärtsilä Technologies

Wärtsilä delivers scalable, fuel-efficient engine power plants that ensure reliable, low-emission on-site power for data centers. We offer a fast, flexible solution for continuous operations. With greater than 50% electrical efficiency, near-zero water use, and the ability to run on sustainable fuels, Wärtsilä helps data centers meet performance and sustainability goals. Learn more at www.wartsila.com/energy.

About Data Center POST

Data Center POST provides a comprehensive view of the digital infrastructure landscape, delivering industry insights into the global data center ecosystem. As the industry’s only peer-contributed and online publication, we offer relevant information from developers, managers, providers, investors, and trendsetters worldwide.

Data Center POST works hard to get the most current information and thought-provoking ideas most apt to add relevance to the success of the data center industry. Stay informed, visit www.datacenterpost.com.

If you are interested in contributing to Data Center POST, contact us at contributions@datacenterpost.com or submit your article here.

Want more digital infrastructure news? Stay in the know and subscribe to Data Center POST today!

The post Executive Profile: A Conversation with Scott Yappen, Senior Business Development Manager at Wärtsilä Energy appeared first on Data Center POST.

TL;DR

• AI is driving immediate infrastructure build-out, shifting the conversation from future potential to deployment realities, including distributed architectures and latency-sensitive workloads.
• Power availability has become the primary constraint, influencing where and how data centers are developed, while geopolitical and national security considerations are increasingly shaping infrastructure decisions.
• Supply chain limitations and capital discipline are tightening project timelines, pushing investors and operators to prioritize projects with secured energy access, realistic delivery plans, and long-term viability.

# # #

The InfraAI Global Summit 2026, held March 30–April 1, 2026 on the Athenian Riviera in Athens, brought together senior decision-makers across AI, data centers, energy, and investment to examine the realities of scaling infrastructure for artificial intelligence. Designed as a high-level, retreat-style gathering, the event focused on the physical, financial, and geopolitical challenges shaping AI infrastructure at scale.

Discussions throughout the event centered on the cost of scaling AI, from capital discipline and supply chain constraints to energy availability and national policy. The agenda reflected a cross-sector perspective, with participation from capital markets, hyperscale platforms, infrastructure operators, and government stakeholders, all addressing how to align deployment with real-world constraints.

Highlighted speakers included Marc Ganzi, CEO of DigitalBridge Group, who opened the conversation with a fireside discussion on capital flows and execution risk in AI infrastructure. Yannis Tsakiris, Vice President of the European Investment Bank, provided a public-sector perspective on financing large-scale digital infrastructure. Vladimir Prodanovic, Principal Program Manager at NVIDIA, delivered insights into the evolution of AI factories and infrastructure design. Oran Dror, CEO and Co-Founder of Frontera AI Transformations, contributed to discussions around global market dynamics, while Dr. Thanos Dokos, Secretary General for National Security of the Hellenic Republic, addressed the growing intersection of AI infrastructure and national security.

AI at the Core of Infrastructure Growth

AI dominated the agenda, with a clear shift from theoretical growth to immediate execution. Sessions explored how infrastructure must evolve to support both training and inference workloads, with increasing emphasis on latency-sensitive deployments and distributed architectures. Discussions highlighted that AI is redefining not only data center design, but also where infrastructure is built and how quickly it must be delivered.

Power, Energy, and Geopolitical Influence

Energy emerged as one of the most critical constraints discussed in Athens. Panels such as “Nuclear, Renewables, or Gas? Powering AI at National and Global Scale” underscored the complexity of aligning energy strategy with AI growth. Speakers emphasized that power is now a primary gating factor, influencing site selection, investment decisions, and national competitiveness. At the same time, geopolitical considerations and national security concerns are increasingly shaping who builds and controls AI infrastructure.

Supply Chain, Capital Discipline, and Execution

Another major theme was the strain on supply chains and the shift toward more disciplined investment strategies. From GPUs and cooling systems to grid infrastructure, delays and constraints are impacting deployment timelines. Investors and operators alike are placing greater emphasis on execution, prioritizing projects that demonstrate clear access to power, realistic delivery schedules, and long-term operational viability.

From Strategy to Reality

InfraAI Global Summit 2026 reinforced that AI infrastructure is no longer a future concept, it is an active, global build-out requiring coordination across capital, energy, technology, and policy. The conversations in Athens made clear that success will depend on disciplined execution, cross-sector collaboration, and the ability to navigate constraints that are becoming increasingly complex.

To learn more about InfraAI and upcoming events, visit thetechcapital.com.

The post InfraAI Global Summit 2026 Highlights AI Infrastructure, Power Strategy, and Global Investment Trends appeared first on Data Center POST.

TL;DR

• AI and digital infrastructure competitiveness is being shaped less by Washington and more by local zoning, permitting, and planning decisions.
• Data center and infrastructure projects are becoming politicized because they intersect with energy, sustainability, tax policy, and economic development.
• Local resistance is often driven by confusion and overload, not outright opposition, and many officials lack the background to evaluate these complex proposals.
• Delays or refusals at the local level can fragment regional growth and push companies toward areas with clearer, faster access to digital capacity.

# # #

In my ongoing series about the national discourse on data center and digital infrastructure, this one gets to the heart of the matter. When infrastructure debates become politicized, the implications extend far beyond individual projects. One of the most important realities emerging in the AI era is that national competitiveness is increasingly being shaped through localized decision-making. Township planning boards and county zoning hearings are now playing an outsized role in determining how and where digital capacity is deployed. You can read the previous posts in my series here, to learn more. 

When people think about the future of artificial intelligence (AI) and digital infrastructure in the United States, they often imagine national strategies, federal investments, or global technology competition.

But the reality is far more localized.

Today, many of the decisions shaping America’s digital competitiveness are being made not in Washington, but in township planning meetings, county zoning hearings, and municipal budget discussions. As a former elected official in Westchester County, New York, I can assure you that there is no national vision for AI infrastructure, and local decisions are shaping our global competitiveness. Whether we mean for this to happen or not, the democratic society that was designed over 250 years ago ensures we operate locally versus nationally.

AI is no longer simply an abstract innovation topic. It is a geopolitical capability. Nations are racing to build the computing infrastructure, energy capacity, and connectivity systems required to support advanced technologies across industries.

Yet the deployment of that infrastructure depends on thousands of localized decisions, each influenced by local community priorities, political dynamics, and varying levels of institutional readiness. This creates a structural paradox.

National competitiveness is increasingly tied to digital infrastructure availability. But authority over land use, permitting, and development timelines largely resides at the local level. Communities are being asked to evaluate complex proposals with long-term implications, often without shared planning frameworks or consistent access to neutral guidance.

In that environment, caution is understandable. As I observe and opine every day, community resistance is often not opposition, it is a reaction to feeling overwhelmed.

Data center and AI infrastructure proposals intersect with energy policy, sustainability goals, tax incentives, and economic development strategies. For many local leaders, these are not familiar domains.

As a former elected official who served two terms, the truth is, anybody can get elected. Many officials simply don’t have the background to understand how complex digital infrastructure development really is. 

Again, this is not about assigning blame. It is about recognizing the realities of governance. Local officials are expected to manage immediate civic concerns while simultaneously making decisions that may shape regional competitiveness for decades.

When the stakes feel unclear and the information landscape is polarized, saying “no” can feel like the most responsible path. But the cumulative effect of localized hesitation can create broader fragmentation. Regions that move forward with infrastructure investment may attract businesses, talent, and innovation ecosystems. Others may experience slower growth or increasing pressure as companies seek environments with more predictable access to digital capacity.

And the reality could be more stark than we realize. If local communities don’t have the infrastructure locally to enable businesses, we will see a massive migration of companies trying to go where those hubs are so they can remain competitive. This is not the intent of community overwhelm forcing them to say no to developments, however, it may be the inevitable outcome.

This dynamic has implications not only for economic development but also for workforce distribution, supply chain resilience, and national technology leadership.

At the same time, infrastructure debates are becoming increasingly political. And, when politics enters the conversation the rhetoric is not about data centers themselves, but about how decisions are made at the county and local level. In politically fragmented environments, infrastructure projects can become symbolic battlegrounds rather than components of long-term strategic planning.

This is where structured engagement models can make a meaningful difference.

My company’s Groundswell™ program is designed to bridge the gap between global stakes and local understanding. It focuses on equipping communities with context, credible information, and collaborative engagement approaches that reduce fear and enable more confident decision-making.

At its core is a simple but powerful idea: Helping communities help themselves is always the best approach, because they literally don’t know what they don’t know.

Digital infrastructure expansion is inevitable. The question is whether its deployment will be guided by reactive politics or informed planning.

In a moment defined by technological acceleration and geopolitical competition, strengthening the link between local governance and national strategy may be one of the most important leadership challenges we face.

Learn more about what we are doing at iMiller Public Relations to bridge the gap between industry and community for the digital infrastructure sector, go to www.imillerpr.com. 

For information about the OIX DIFC, visit www.oix.org/standards-and-certifications/oix-dif-standard.

The post The Digital Future Is Being Decided by Local Politics — Whether We Realize It or Not appeared first on Data Center POST.

TL;DR

• New entity established: Datalec Precision Installations (DPI) has officially incorporated in the Kingdom of Saudi Arabia, strengthening its Middle East footprint and end-to-end data center delivery capabilities.
• Strategic market entry: Saudi Arabia is targeting approximately 1.5 gigawatts of data center capacity by 2030, with hyperscale providers including AWS, Google, Oracle, and Microsoft investing heavily in local cloud regions.
• Regional platform expansion: The Saudi entity builds on DPI’s 51,000-square-foot Dubai hub, bringing integrated design, build, fit-out, and lifecycle services closer to customers driving the Kingdom’s digital transformation.

# # #

Datalec Precision Installations (DPI), a global provider of integrated data center delivery solutions, has officially incorporated a new entity in the Kingdom of Saudi Arabia, marking a significant milestone in its strategic growth across the Middle East.

Saudi Arabia is targeting approximately 1.5 gigawatts of data center capacity by 2030 under its National Data Center Strategy, supported by large-scale public and private investment. Personal Data Protection Law and cloud regulations requiring data to be hosted in-country are accelerating demand for local infrastructure solutions. Hyperscale cloud providers including Amazon Web Services, Google, Oracle, and Microsoft are investing in cloud regions in the Kingdom, with Microsoft Azure expected to be live by Q4 2026.

“Formalising our presence in Saudi Arabia is a pivotal step in DPI’s Middle East growth journey and reflects our long-term commitment to the Kingdom’s digital transformation,” said Sean Christie, regional director, Middle East, DPI.

The expansion builds on DPI’s 51,000-square-foot Dubai hub, which serves as its Middle East head office, manufacturing center, and training facility. The Saudi entity will enable DPI to deliver grey space technical fit-outs, whitespace integration, lifecycle services, and facilities management closer to customers as they scale to meet growing cloud, AI, and data localization requirements.

To learn more about Datalec Precision Installations, visit datalecltd.com.

The post Datalec Unveils Next-Generation Modular Data Centre Solution to Accelerate Deployment appeared first on Data Center POST.

TL;DR

• Power availability is now the primary constraint on data center growth, shifting site selection toward regions where energy access, interconnection, and permitting align with deployment timelines.
• Operators are adapting strategies through hybrid energy sourcing, long-term power purchase agreements, and closer coordination with utilities to secure reliable capacity.
• ESG has become central to investment decisions, with capital increasingly tied to sustainability, energy efficiency, and alignment with community and regulatory expectations.
• Circular design, renewable integration, and high-density infrastructure optimization are emerging as key approaches to improve performance, reduce waste, and support long-term scalability.

# # #

With power availability tightening across key markets, Datacloud Energy & ESG 2026 focused squarely on the practical realities shaping data center growth. Held March 25–26, 2026 in Brussels, the event brought together operators, utilities, investors, and policymakers to examine how energy constraints, sustainability expectations, and regulatory frameworks are influencing development timelines and long-term strategy.

Discussions throughout the two-day program reflected an industry adjusting to a new set of constraints. The rapid rise of AI workloads continues to drive demand for capacity, but access to reliable power is emerging as the primary limiting factor. Rather than expanding wherever land is available, operators are increasingly prioritizing locations where energy procurement, grid interconnection, and permitting processes can align with deployment schedules.

Sessions featuring Bruce Owen, President of Global Data Centers at Equinix, explored how operators are adapting expansion strategies to reflect these realities. The shift toward hybrid energy sourcing, including long-term power purchase agreements and on-site generation, is becoming more common as companies look to secure capacity while managing risk tied to grid availability.

The role of utilities and infrastructure planning was another key focus. John Pettigrew, CEO of National Grid, addressed the growing pressure on transmission and distribution networks as data center demand accelerates. His remarks highlighted the need for earlier engagement between developers and utilities, as well as increased investment in grid modernization to support large-scale digital infrastructure projects.

From an investment standpoint, ESG considerations are now embedded in how projects are evaluated and financed. Alec Fedorov, Managing Director at ICG, noted that capital allocation is increasingly tied to a project’s ability to demonstrate long-term sustainability, efficient energy usage, and alignment with community priorities. Environmental impact and energy sourcing are no longer secondary factors, but central to investment decisions.

Circularity and operational performance were also key themes. During the panel on building more efficient, circular data centers, Fabiola Bordino, Chief Sustainability Officer at TTSP-HWP, focused on how circular design principles can improve power usage, cooling performance, predictive operations, and scalability. The discussion explored practical steps to embed circularity from design through end-of-life, including a three-pillar approach to sustainability and energy efficiency. Panelists also examined the ROI of circularity, highlighting reduced waste, improved resource utilization, and longer-term infrastructure value.

Design strategies are also evolving in response to higher-density workloads. Thomas Meier, CEO of Maincubes, discussed how operators are optimizing power distribution and cooling to increase compute output per megawatt, reflecting a broader shift toward performance-driven infrastructure rather than footprint expansion.

Adding a broader perspective, Dr. Nina Skorupska, CEO of the Renewable Energy Association, emphasized the importance of integrating renewable energy into the data center ecosystem while addressing challenges related to intermittency and storage. Her comments reinforced the need for a more coordinated approach across energy providers, infrastructure developers, and policymakers, particularly as energy strategy becomes a defining factor in how and where new data center capacity is deployed.

To learn more about upcoming Datacloud events and industry insights, visit the Datacloud event series.

The post Brussels Sets the Stage for Critical Energy and ESG Conversations at Datacloud Energy & ESG 2026 appeared first on Data Center POST.

TL;DR

• New data center capacity in New York: Hudson InterXchange (Hudson IX) has launched a 1 MW expansion at the 60 Hudson Street data center, delivering high-density colocation in one of the most connected carrier hotel NYC locations.
• Solving NYC data center constraints: The expansion adds scalable data center power and space in a supply-constrained New York City colocation market, supporting AI infrastructure, cloud platforms, and low-latency connectivity.
• Expansion ahead: Hudson IX plans an additional 1 MW data hall in Q2 2026, reinforcing its role as a key provider of colocation NYC and digital infrastructure growth in the region.

# # #

As demand for high-density infrastructure continues to accelerate, access to power and space in key metro markets has become increasingly limited—especially in New York City. Hudson InterXchange (Hudson IX) has announced an expansion at 60 Hudson Street, one of the most important data center and carrier hotel locations in NYC.This will introduce new capacity in one of the most network-dense buildings in the United States.

The company’s newly launched 1 MW data hall is now operational and available for high-density colocation deployments, providing rare access to both power and connectivity in a market where both remain constrained. Located within a carrier hotel that supports more than 300 networks and service providers, the expansion enables customers to deploy infrastructure in close proximity to critical ecosystems, an essential advantage for low-latency connectivity in NYC.

This development is coming during a time in which infrastructure requirements are evolving rapidly. Cloud adoption, AI-driven workloads, and real-time applications are placing increased pressure on existing capacity, particularly in legacy connectivity hubs like 60 Hudson Street. As a result, data center capacity constraints in NYC have become a growing challenge for enterprises and providers alike. By bringing new supply to market, Hudson IX is helping address a gap that many operators and enterprises are actively navigating.

This new data hall will support a broad range of deployments, from traditional enterprise environments to enterprise colocation solutions and high-density configurations required for compute-intensive workloads like AI inference.This flexibility positions Hudson IX to serve a diverse customer base, including network providers, content platforms, financial institutions, and cloud operators seeking AI infrastructure in New York.

“This expansion is the result of our remarkable team and its commitment to delivering a large, world-class, high-performance data center platform, with scalable solutions ranging from single cabinets to bespoke cages, supporting a wide spectrum of rack densities, all within one of New York City’s most highly connected buildings,” said Atul Roy of Hudson InterXchange. “We are grateful to our customers for entrusting us with their infrastructure, and we look forward to expanding our facility to support their growing needs.”

The announcement also reflects a longer-term growth strategy. Hudson IX plans to bring an additional 1 MW data hall online in the second quarter of 2026, with a broader roadmap that will expand total capacity at 60 Hudson Street beyond 10 MW. This continued investment reinforces the company’s role as a key provider of scalable data center power.

As digital infrastructure demand continues to scale, expansions like this highlight the importance of unlocking new capacity within existing interconnection hub NYC environments. For organizations seeking proximity, performance, and scalability, developments at 60 Hudson Street represent a critical opportunity in an otherwise supply-constrained market.

The post Hudson IX Expands at 60 Hudson with New 1 MW Data Hall, Roadmap Beyond 10 MW appeared first on Data Center POST.

TL;DR

• Predictable Performance for Mature AI: While hyperscale environments are ideal for early experimentation and rapid scaling, colocation offers the stability and long-term cost predictability required as AI workloads transition to continuous operation and fine-tuning.
• The Optimal Middle Ground: Colocation bridges the gap between on-premises and cloud setups, allowing enterprises to deploy dedicated hardware and maintain strict control without taking on the capital-intensive complexities of building their own facilities.
• Purpose-Built Infrastructure: Modern colocation facilities are being heavily upgraded with advanced environmental controls, reinforced structures, and dense network ecosystems, making them perfectly adapted to support continuous, high-density AI workloads.

# # #

Most of the current conversation around AI infrastructure tends to point in one direction. Hyperscale environments dominate the headlines, and for good reason: they offer immediate access to large pools of compute, making them an obvious starting point for many teams. However, when AI workloads move beyond early experimentation, things change. Running models continuously, managing expanding datasets, while keeping performance consistent over time introduces a different set of concerns, ones that can’t always be addressed by scale alone. What’s starting to matter more is how predictable and reliable the environment is, how costs behave long-term, and how closely the infrastructure can be reshaped around the workload itself.

Today, many colocation facilities are already being adapted to handle higher-density deployments, with upgrades in power distribution, cooling design, and interconnection capacity to support modern AI environments. Established sites are expanding their connectivity ecosystems, which makes it easier to integrate colocation into hybrid architectures without ending up with unnecessary complexity.

So, colocation for AI stays in the focus of infrastructure decisions as a very reasonable and relevant solution that continues to offer value in the age of AI. Let’s take a closer look at recent changes and why enterprises continue to choose colocation.

Hyperscalers are Not the Only Way

Hyperscale environments will continue to play a major role in how AI infrastructure evolves, especially as large-scale model training pushes demand for tightly integrated GPU clusters and massive power footprints. For certain workloads, particularly those that require rapid scaling or short-term access to large amounts of compute, they remain a very practical option.

At the same time, not every AI deployment operates at that level, and treating hyperscale as the default can lead to mismatches between the workload and the environment it runs in. Many organizations are working with more contained models, fine-tuning existing architectures, or running inference pipelines that need to perform consistently over time rather than scale unpredictably. In those cases, access to unlimited capacity matters less than having a stable, well-understood infrastructure baseline.

As a result, colocation for AI can offer a more balanced approach. Instead of relying on shared cloud environments, teams have the opportunity to deploy dedicated hardware, shape the infrastructure around their specific requirements, and maintain the necessary level of control, which is becoming increasingly important as workloads mature.

These tendencies are showing in the broader market trajectory. According to recent predictions, the global colocation data center market is projected to grow from roughly $83 billion in 2024 to over $180 billion by 2030, with a compound annual growth rate above 14%. That kind of expansion doesn’t happen if colocation is becoming less relevant. On the contrary, it points to ongoing demand from organizations that are looking for alternatives that can offer a balanced approach between the constraints of on-prem solutions and the abstraction of hyperscalers.

It’s becoming more apparent across the industry that AI infrastructure is settling into operating within a mix of models. Hyperscale, colocation, and edge environments are being used together, depending on how workloads behave and where they need to run. In this context, colocation is an essential part of how enterprises design scalable and predictable AI environments.

The Optimal Solution is the One That Fits Workloads

There isn’t a single best environment that works well for every AI deployment, and that becomes clear the moment workloads move beyond the initial isolated experimentation. Large model training, fine-tuning existing architectures, and running inference pipelines all behave differently at the infrastructure level, which in most cases leads to decisions around placement following the workload, and not a pre-established strategy. Most organizations end up distributing workloads across multiple environments. Because hyperscale platforms are useful when access to large-scale compute is the priority (especially for burst-heavy or short-lived tasks), but on-premises setups still make sense where strict control or data locality is important. A growing share of workloads, however, sits between those extremes, requiring more complex solutions, because of their complex needs: performance has to stay consistent, infrastructure needs to be adaptable, and costs should preferably remain predictable over time.

Colocation for AI offers a viable solution that many choose as a middle ground solution. Colocation makes it possible for organizations to deploy their own hardware in facilities designed specifically for IT workloads, without taking on the full complexity of building and operating those environments themselves. So, instead of adapting workloads to fit a predefined platform, this way teams can shape the infrastructure around how their systems actually run, and what they need to run optimally.

Why Colocation for AI is More Relevant Than Ever

What’s been unfolding over the past few years is a steady alignment between the demands of AI workloads and the way colocation environments are built and upgraded. Facilities are now designed with reinforced structures, advanced fire suppression systems, and controlled environmental conditions that can support the continuous, high-density operation requirements of AI workloads. Providers that meet strict compliance and certification requirements are a must for organizations operating in regulated sectors where infrastructure decisions carry not just operational, but legal weight as well.

Colocation environments have changed a lot, and this means that they have also become far more interconnected in the past few years. Direct access to cloud platforms, dense carrier ecosystems, and high-capacity interconnection layers are now standard features in many facilities, making it easier to integrate colocation into hybrid architectures without friction. As AI workloads grow in complexity, combining dedicated infrastructure with this level of connectivity and operational support becomes difficult to replicate internally. For this reason, and many others, choosing colocation for AI increasingly shows up as the most practical infrastructure choice.

Colocation for AI Compared to Other Types of Data Centers

When you step back and look at the broader infrastructure landscape, most deployments fall into a few well-defined categories: on-premises, hyperscale cloud, edge, and colocation. Each model exists for a reason, but each one serves a very different operational priority.

On-premises environments offer maximum control, but scaling them to support high-density AI workloads can become complex and capital-intensive, especially when power, cooling, and physical resilience have not been upgraded. Hyperscale platforms remove much of that burden, but instead, they introduce a level of abstraction that can make it harder to control performance characteristics or manage costs when workloads grow. Edge environments bring compute closer to users or devices, but they are typically optimized only for latency-sensitive use cases, and not for sustained, high-throughput processing.

Colocation for AI can work like a solution that brings together the best of all of these different models by combining dedicated infrastructure with facilities purpose-built for reliability and performance. Organizations can deploy their own systems, connect directly to cloud providers and network ecosystems, and scale their environments without redesigning the underlying facility. This makes colocation particularly effective for AI workloads that need both stability and flexibility, especially as part of a broader, distributed architecture.

Wise Infrastructure Choices for Long-term Value

As AI workloads move into continuous operation, infrastructure decisions start to show their real impact over time. What matters at that stage isn’t just how quickly resources can be provisioned, but also how reliably systems perform under sustained load, how costs evolve as usage stabilizes, and how easily the environment can adjust as requirements change. These are the factors that shape long-term value, and they tend to become visible only after workloads have already been running for a while.

When early choices start to show their limitations, disfunctionalities become obvious: sometimes  the environment itself makes it difficult to control the costs changed by scale, or sometimes there’s not enough visibility and flexibility once workloads mature. Choosing colocation for AI can prove to be just the right kind of stable, purpose-built environment that allows managing the infrastructure more directly. The advantage comes from this balance over time: having predictably behaving systems that can be tuned precisely to the workload can support the growth and easy scaling that is so essential for the health and optimal operation of these workloads long-term.

# # #

About the Author

Michael Zrihen is the Senior Director of Marketing & Internal Operations Manager at Volico Data Centers.

The post Colocation for AI: Why Enterprises are Making the Switch appeared first on Data Center POST.

Originally posted on Datalec Ltd.

TL;DR

Following Data Centre World (DCW) London 2026, it is clear that rapid AI-driven growth and constrained power availability have made the choice of infrastructure partners a business-critical decision. Operators navigating hyperscale and colocation expansion require partners capable of planning with a power-first approach, deploying quickly, and maintaining reliability in high-density settings. Datalec Precision Installations (DPI) demonstrated these integrated capabilities, addressing consistent global concerns about designing and sustaining AI workloads.

The physical profile of data centres is being reshaped by GPU-rich clusters, which are pushing rack densities past the limits of traditional cooling strategies. To mitigate the rising risk of outages associated with this complexity, successful operations must link density, advanced cooling, and ongoing facilities management into a single, continuous discipline. Furthermore, sustainability and lifecycle value have become central to procurement decisions, requiring operators to balance thermal risks with efficiency and responsible capacity delivery.

These industry pressures will intensify as the market looks ahead to DCW Asia in Singapore. In regions where land is scarce and power is heavily regulated, infrastructure partners will be differentiated by their ability to industrialise repeatable designs while adapting to local grid, climate, and regulatory demands. Ultimately, organizations are seeking long-term partners capable of supporting their evolving sustainability commitments and complex AI workloads over the next decade.

To continue reading, please click here.

The post Data Centre World London 2026: Three Questions Every AI‑Driven Operator Should Ask Their Infrastructure Partner appeared first on Data Center POST.

Originally posted on Harbor Network Solutions.

TL;DR

• Overcoming traditional bottlenecks: Older networks designed with low fiber counts are struggling to keep up; adopting “fiber-rich” infrastructure provides the higher fiber counts needed to scale capacity and flexibly support growing AI demands without requiring constant network rebuilds.
• Route diversity ensures resilience: Because digital infrastructure requires high uptime, networks must incorporate physical and geographic route diversity to eliminate single points of failure and maintain continuity during localized outages.
• Regional connectivity is expanding: As data center development moves beyond major central hubs into distributed clusters, high-capacity corridors between regional markets are becoming essential to support distributed workloads and long-term future-readiness.

# # #

The rapid expansion of artificial intelligence is fundamentally changing network traffic patterns, significantly increasing the volume of “east-west” data movement between data centers, cloud regions, and edge environments. Unlike traditional applications that rely on predictable “north-south” traffic, AI workloads require continuous, massive data exchanges for both model training and real-time inference. As a result, older network architectures designed for lower capacities and centralized routing are increasingly strained, often lacking the fiber depth needed to prevent congestion and high latency.

To overcome these limitations, there is a growing necessity for “fiber-rich” infrastructure that prioritizes higher fiber counts. This approach provides the scalability and operational flexibility required to manage intense AI workloads without necessitating constant network rebuilds. Furthermore, modern infrastructure heavily emphasizes physical route and geographic diversity, ensuring that dual-path connectivity can prevent single points of failure and improve overall resilience against localized disruptions.

This evolution in network design also highlights the critical importance of regional connectivity, as data center development expands beyond traditional major hubs into distributed regional clusters. Because emerging technologies and real-time analytics will continue to drive unprecedented data velocity, infrastructure planning must account for sustained, long-term growth rather than just immediate needs. Ultimately, prioritizing highly scalable, fiber-rich networks allows organizations to maintain continuous performance and adaptability in an increasingly demanding digital environment.

To continue reading, please click here.

The post Why AI Is Driving the Need for Fiber-Rich Network Infrastructure appeared first on Data Center POST.

TL;DR

• Major expansion completed: Empire Fiber Internet finished its latest fiber build in Steuben County, bringing service to Avoca, Birdseye Hollow, Caton, Hornby, Howard, and Savona.
• Nearly 2,000 homes connected: The project expands access to reliable high-speed internet for more local residents and businesses.
• Bigger impact beyond the build: This expansion highlights Empire’s community investment and supports the broader push to close rural broadband gaps.

# # #

Empire Fiber Internet, a leading fiber optic internet service provider serving communities across New York and Pennsylvania, has completed its latest fiber expansion in Steuben County, bringing reliable high-speed service to residents in Avoca, Birdseye Hollow, Caton, Hornby, Howard, and Savona. Nearly 2,000 more homes are now connected, strengthening access to the kind of broadband service needed for work, school, and daily life.

The expansion reflects Empire Fiber Internet’s continued partnership with Steuben County to bring modern broadband infrastructure to rural communities. For the company, the project reinforces its local roots, deepens its investment in the region, and extends its role as both a service provider and a community partner.

“Headquartered right here in Steuben County, we’re proud to employ local residents and invest in the community where we live and work,” said Kevin Dickens, CEO of Empire Fiber Internet. “This expansion is about more than fiber, it’s about connecting people to opportunities, education, and each other. Now, nearly 2,000 more households can experience fast, reliable internet that supports how they live, work, and learn every day.”

This announcement is significant for the company, showing measurable network growth, deepening its local footprint, and demonstrating execution on long-term infrastructure investment. It also reinforces Empire Fiber Internet’s reputation as a provider focused on reliability, community impact, and future-ready broadband.

“Steuben County is extremely proud and grateful for our partnership with Empire Access for the expansion of rural broadband services across our communities,” said Jack Wheeler, Steuben County Manager. “When the County received American Rescue Plan Act (ARPA) funding in 2021, the County Legislature made it clear that rural broadband was the top priority for use of these funds, and as a result, over 2,000 previously unserved homes and businesses will now have access to high-speed internet. This would not be possible without the investment and dedication of Empire Access, who has been a trusted and responsive partner. We are thrilled with the fruition of this project and will continue to work with Empire to explore opportunities to expand broadband to all.”

Across the broadband sector, providers and local governments are under pressure to close rural connectivity gaps. This project shows how public funding and private deployment can work together to expand access, turning broadband expansion into both a service milestone and a workforce-development opportunity.

On May 13, the team will also participate in Career Day with Prattsburgh Elementary School, giving students a hands-on look at careers in fiber internet and technology. That effort underscores that broadband expansion is not only about connectivity, but also about building awareness of the jobs and skills that support the industry’s future.

Steuben County residents can check availability and sign up at empirefiber.com. Empire Fiber Internet offers 100% fiber connections with symmetrical speeds up to 2 Gig, enterprise-level reliability, locally staffed customer support, and no data caps.

To learn more about Empire Fiber Internet, visit empirefiber.com.

The post Empire Fiber Internet Celebrates Major Steuben County Expansion appeared first on Data Center POST.

TL:DR;

• Full occupancy reached: Harrison Street Asset Management and 1547 have achieved full capacity at their Orangeburg, New York data center campus following a strategic, demand-driven expansion.
• Significant capacity growth: Since acquiring the site in 2021, the joint venture has successfully expanded the facility from 3.7 megawatts to approximately 18 megawatts of critical IT load.
• Future expansion underway: To meet continued market demand, the partners are developing an additional 12-megawatt utility feed and planning a pre-approved 230,000-square-foot expansion supported by a 60-megawatt on-site substation.

# # #

Harrison Street Asset Management and fifteenfortyseven Critical Systems Realty (1547) have reached a significant milestone at their Orangeburg, New York data center campus, achieving full occupancy following a phased, demand-driven expansion. The achievement highlights the continued demand for highly connected, low-latency digital infrastructure in the Greater New York market and reinforces Orangeburg’s growing role as a strategic hub for enterprise and financial services customers.

Located approximately 18 miles north of Manhattan, the purpose-built colocation facility has been expanded through a phased, demand-driven development strategy since Harrison Street and 1547 acquired the site in 2021. At the time of acquisition, the campus supported 3.7 megawatts of critical IT load. Since then, the joint venture has added roughly 14 megawatts of incremental capacity while increasing density across the existing 232,000-square-foot footprint.

The campus now supports approximately 18 megawatts of critical IT load and is operating at near-full utilization, driven largely by demand from financial institutions, high-frequency trading firms, hedge funds, and other organizations requiring ultra-low-latency connectivity into Manhattan and the broader metro region. The site also benefits from access to multiple terrestrial fiber routes and proximity to subsea cable landing infrastructure along the East Coast, making it an attractive destination for connectivity-focused workloads.

“With the facility now fully leased, each phase of development has been aligned to demonstrate customer demand,” said Michael Hochanadel, Head of Digital Assets at Harrison Street Asset Management. “Our partner delivered on schedule and within budget, while continuing to operate a critical data center with no downtime, reinforcing the strength of our collective platform.”

That disciplined approach has been central to how the Orangeburg campus has evolved. Rather than building ahead of demand, capacity has been delivered in step with customer needs, ensuring performance and reliability at every stage.

“Orangeburg is a prime example of what can be achieved through disciplined execution and close partnership,” said J. Todd Raymond, Chief Executive Officer and Managing Director of 1547. “From day one, our focus has been on delivering capacity in direct response to customer demand while maintaining the performance and reliability our clients depend on.”

With the facility fully leased, Harrison Street and 1547 are already advancing additional expansion plans to meet future customer demand. An additional 12-megawatt utility feed is currently under development, while the long-term roadmap for the campus includes a pre-approved 230,000-square-foot expansion supported by a planned on-site 60-megawatt substation.

As demand for low-latency, network-dense infrastructure continues to grow, projects like Orangeburg reflect a broader shift toward strategic, connectivity-rich locations that can scale in line with customer requirements. For Harrison Street and 1547, the continued momentum at Orangeburg further strengthens their growing data center platform and positions the campus for long-term growth.

Read the full release here.

The post Harrison Street and 1547 Reach Full Occupancy at Orangeburg Data Center as Expansion Continues appeared first on Data Center POST.

TL;DR

• AI-driven sales transformation: 365 Data Centers has entered a multi-year partnership with Collective[i], deploying its technology as a strategic intelligence layer to modernize its go-to-market operations and improve revenue predictability.
• Automated operational intelligence: The platform replaces manual processes with automation by automatically capturing activity, centralizing deal collaboration, and identifying buyer-specific risks in real time.
• Significant performance gains: The integration has led to consecutive quarters of above-plan performance, driving a 15% increase in win rates, a 35% reduction in sales cycles, and double-digit revenue growth within the first six months.

# # #

365 Data Centers is showing how AI can move beyond experimentation and into measurable business impact. In a new multi-year agreement with Collective[i], the company has transformed its commercial go-to-market operation, reporting improved win rates, shorter sales cycles, and stronger quarterly performance.

Since deploying the platform, 365 Data Centers reports that win rates have increased by more than 15% and sales cycle length has decreased by 35%. Those gains helped support several consecutive quarters of above-plan performance, including record bookings in the fourth quarter of 2025 and continued outperformance in the first quarter of 2026.

Embedding Intelligence Into Sales

365 is utilizing Collective[i]’s technology as a strategic intelligence layer across its revenue organization, replacing manual processes with automation and helping teams identify buyer-specific risks in real time. The platform also centralizes deal collaboration and captures activity automatically, which has strengthened its internal data and improved productivity.

Derek Gillespie, CEO and CRO of 365 Data Centers, expressed in the announcement that the integration supports the company’s broader commitment to data-driven inspection and AI enablement. Per Gillespie, the partnership has improved predictability and helped the company stay on track toward its long-term growth goals.

Within the first quarter of deployment, 365 Data Centers reported a 20% increase in productivity and a 34% increase in its contact database. The company also saw impressive double-digit revenue growth within just six months of deployment.

Industry Implications & Future Outlook

The timing is notable for the data center industry, where operators are under pressure to improve speed, precision, and commercial execution while serving increasingly complex customer needs. 365 Data Centers is positioning AI not only as an infrastructure advantage, but also as a tool for improving sales performance and revenue operations. Together, the two companies offer a clear example of how AI can support growth across both technical and commercial functions.

The post 365 Data Centers Partners with Collective[i], Leveraging AI to Drive Sales and Increase Revenue appeared first on Data Center POST.

Originally posted on EdgeIR.

Live streaming at scale, particularly for interactive broadcasts and sports, requires extremely low latency to maintain viewer immersion. Traditional centralized infrastructure often struggles with the “thundering herd” problem, where massive sudden spikes in viewership strain single origin points, resulting in buffering and expensive infrastructure overprovisioning. To resolve these bottlenecks, Multi-access Edge Computing (MEC) brings processing power and application hosting directly to local points of presence, drastically shortening data travel paths. Shifting tasks such as transcoding, caching, and adaptive bitrate (ABR) logic to the edge reduces first-frame delays and enables platforms to react rapidly to real-time local network conditions.

Even with these localized capabilities, high-performance bare metal servers remain vital for core, intensive workloads. Because bare metal environments lack hypervisor overhead and tenant contention, they provide the highly stable and predictable processing power necessary for demanding tasks like real-time 4K origin encoding and security orchestration. By adopting a hybrid architecture, organizations can split these responsibilities effectively, relying on bare metal for intensive central operations while utilizing edge nodes for user-proximity delivery.

Beyond optimizing the viewer experience, this hybrid approach addresses critical economic and regulatory challenges. Dedicated bare metal servers with generous included bandwidth often deliver substantially better economics for steady-state streaming compared to aggressive cloud autoscaling and expensive pay-per-GB egress models. Furthermore, keeping user ingest, sessions, and personalization local at the edge helps organizations comply with evolving regional data privacy frameworks, leaving central cores to manage global functions like digital rights management and billing.

To continue reading, please click here.

The post Why Streamers Need a Hybrid Edge-Bare Metal Architecture for Live at Scale appeared first on Data Center POST.

TL;DR

• Edge AI optimizes real-time performance: While cloud data centers are ideal for training massive AI models, running inference at the edge significantly lowers latency, improves data privacy, and ensures autonomous operation during network outages.
• Critical across multiple industries: Localized AI processing is vital for data-intensive, real-time applications such as healthcare diagnostics, advanced driver assistance systems (ADAS), manufacturing quality control, and security surveillance.
• Strategic deployment is required: Successfully operating AI in decentralized edge environments requires careful management of processing architecture tradeoffs, stable power distribution, thermal constraints, and system redundancy to handle potential component or power failures.
• Industry standards ensure reliability and security: Implementing established frameworks, specifically TL 9000 for system quality, TIA-942 for infrastructure resilience, and SCS 9001 for cybersecurity, is essential for keeping edge endpoints secure, robust, and highly available.

# # #

Artificial intelligence (AI) and machine learning (ML) are driving new levels of automation, insight, and responsiveness across a wide range of industries. As organizations deploy increasingly advanced generative AI (GenAI) models, they must continuously evaluate where and how to run workloads for optimal performance.

While cloud data centers offer the processing power and scale needed to train large language models (LLMs), many real-time AI applications—such as sensor networks and computer vision systems—perform more effectively when data is processed closer to the edge.

This article explores the advantages of edge AI for various applications such as healthcare, manufacturing, and advanced driver assistance systems (ADAS). It also reviews key deployment considerations, including processing architecture, power and cooling, resilient system management, and security.

Why Edge AI?

AI developers train complex LLMs in cloud-based data centers using vast datasets, high-performance compute, and petabyte-scale storage. Applying deep learning techniques, these models analyze historical data and identify patterns to refine their predictive capabilities. However, edge deployments typically perform inference—applying learned patterns to real-time data—more efficiently due to:

• Lower latency and reduced network congestion: Edge AI minimizes round-trip time by processing data locally, reducing transmitted data volume, easing traffic bottlenecks, and lowering egress costs.
• Improved data privacy and security: Onsite data processing reduces susceptibility to external threats such as man-in-the-middle attacks while simplifying compliance with data sovereignty and privacy regulations.
• Optimal resilience and autonomy: Many edge AI systems continue operating during wider network outages, a key capability for mobile, remote, or mission-critical applications.
• Increased scalability and flexibility: Distributed edge architecture allows organizations to expand AI capabilities incrementally, without overhauling centralized data center infrastructure.
• Incremental learning: Some edge systems are beginning to support incremental learning by adapting models locally based on real-time streams or historical data. This reduces the need for frequent retraining in the cloud.

Key Applications

Edge AI systems are increasingly critical for real-time, high-reliability, and data-intensive use cases. In healthcare, they enable early diagnosis and responsive care by analyzing patient telemetry and medical imaging in real time. These platforms also support robotic surgery, triage decisions, and remote patient monitoring. In pharmaceuticals, edge-deployed AI accelerates drug discovery and clinical trials through localized analysis of genomic and biomarker data. It also supports predictive modeling to customize therapies and assess patient outcomes more efficiently.

In advanced driver assistance systems (ADAS), edge AI enables real-time perception, decision-making, and actuation. Onboard processors run computer vision and sensor fusion models to detect obstacles, interpret traffic signals, and assess road conditions with millisecond-level latency. These capabilities support adaptive cruise control, lane keeping, emergency braking, and driver monitoring. Edge AI also facilitates fully autonomous driving, where vehicles must interpret and respond to complex environments without relying on cloud connectivity.

Manufacturing, industrial, and logistics operations leverage edge AI to improve quality control, identify inefficiencies, and enable predictive maintenance. Machine learning models trained in the cloud run locally to monitor sensor data, detect anomalies, and optimize equipment performance in real time. In supply chain deployments, edge systems support inventory tracking, demand forecasting, and shipping optimization. Computer vision helps verify shipments, sort goods, and maintain real-time visibility across warehouses and transit hubs.

Security and surveillance systems similarly benefit from local video processing. These applications can identify unauthorized access, classify threats, and automate alerts without immediately transmitting footage to the cloud, improving response time and maintaining data privacy.

Deployment Considerations

Processing Architecture

Edge AI system developers select processors based on workload demands, power budgets, and thermal constraints. Each processor type presents tradeoffs in performance, efficiency, and applicability to specific tasks. The table below outlines key processor considerations and options for edge deployments:

Table 1: Edge AI processor comparison, illustrating advantages, edge deployment considerations, and target applications.

Power and Cooling

Although edge systems generally run at lower densities than cloud clusters, AI workloads can still drive significant power consumption and thermal output. GPUs, in particular, draw more power than other edge AI silicon and often require more robust thermal management, especially in remote or space-constrained environments.

Stable power distribution is essential to maintain uptime in edge AI systems. Common strategies include uninterruptible power supplies (UPS), dual power feeds, and intelligent power distribution units (PDUs) with integrated monitoring. Where practical, remote monitoring tracks power quality, runtime, and system status. Some edge installations benefit from direct current (DC) power for improved efficiency, although most still require a combination of alternating current (AC) and DC infrastructure.

Resilient System Management

Edge AI deployments must tolerate component failures, communication disruptions, and power fluctuations. This requires redundancy across compute, storage, and power, along with intelligent failover mechanisms, remote management platforms, and orchestration tools that dynamically reroute workloads. Systems must also cache tasks locally and resume processing once connectivity is restored, an essential capability for high-availability and safety-critical deployments.

Developers can adopt the TL 9000 standard to embed quality and resilience into their edge AI systems efficiently and comprehensively. Defined by the Telecommunications Industry Association (TIA) and built on ISO 9001, the scalable TL 9000 adds more than 80 ICT-specific requirements spanning software, hardware, and service lifecycles.

TIA-942 complements the TL 9000 standard by defining rigorous infrastructure requirements for data centers supporting edge AI ecosystems. The standard addresses the architecture, power distribution, cooling, telecommunications, redundancy, physical security, and sustainability of data centers, ensuring high availability and scalability as AI workloads increase across both core and edge deployments.

Ensuring Security

Edge AI systems broaden attack surfaces by introducing more physical endpoints and increasing digital exposure across distributed architectures. Key cybersecurity strategies include:

• Securing AI models at rest, in transit, and during execution
• Enforcing authentication and encryption across systems
• Limiting access to verified nodes and provisioning securely
• Centrally managing nodes with granular policy controls

Organizations can implement TIA’s SCS 9001 cyber and supply chain security standard to ensure protections are applied consistently and verifiably across edge AI endpoints and infrastructure. SCS 9001 provides a certifiable, scalable ICT-specific framework that helps validate controls, assess supplier risk, and enforce safeguards in decentralized deployments. Extending quality management into the security domain, SCS 9001 can be adopted independently or alongside TL 9000 to support a unified quality and security strategy for edge AI systems.

Conclusion

High-bandwidth, low-latency applications are accelerating edge AI adoption across industries. While centralized data centers remain essential for training LLMs, edge deployments provide crucial advantages for real-time inference, data privacy, system resilience, and operational control. Effective edge AI implementation requires selecting silicon that aligns with power and thermal constraints, while embedding quality and security throughout the system lifecycle with industry standards such as TL 9000, TIA-942 and SCS 9001.

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About the Author

Mike Peterson serves as the Lead for the Data Center Program at the Telecommunications Industry Association, where he oversees the global TIA-942 certification ecosystem and works closely with TR-42 subcommittees to advance data-center standards. A longtime CTO/CIO with more than three decades of experience, Mike has led data-center operations, global cloud transformations, and large-scale engineering organizations at CFA Institute, Travelzoo, and Neustar. His background spans AI strategy, platform modernization, cybersecurity, large-scale data architectures, and enterprise operational resilience. He also brings entrepreneurial roots as a founder, patent holder, and innovation leader, giving him a unique perspective at the intersection of standards, engineering, and digital-infrastructure strategy.

Mike Peterson
Data Center Program Manager
TIA (Telecommunications Industry Association)
T: +1 469-450-7950
MPeterson@tiaonline.org

The post From the Cloud to the Intelligent Edge: Benefits, Applications, and Key Considerations appeared first on Data Center POST.

Originally posted on Nomad Futurist.

Nomad Futurist Foundation Ambassador Dan Ephraim recently engaged with MBA and BSBA students at Washington University’s Olin School of Business to introduce them to the digital infrastructure industry. During interactive sessions, students explored crucial industry topics such as real estate, energy, sustainability, supply chain, and business models. The goal was to demonstrate how students could apply their existing foundations in financial analysis, operations, and leadership to meaningful career pathways within this growing sector.

The initiative successfully energized the attendees, with many students requesting tours of data centers in Virginia and St. Louis to see the operations firsthand. Feedback indicated that the sessions were eye-opening and helped solidify their interest in pursuing roles that bridge technical knowledge with go-to-market strategies. For many participants, this served as their very first real introduction to the digital infrastructure field.

Ultimately, these outreach efforts reflect the core mission of the Nomad Futurist Foundation: to open doors, connect emerging talent with opportunities, and inspire future strategists, operators, and leaders. By partnering with educational institutions and encouraging industry experts to mentor students, the foundation aims to actively shape the next generation of digital infrastructure professionals.

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DCD>Connect New York 2026 took place March 23–24, 2026 in New York City, bringing together operators, engineers, investors, and energy providers to examine how digital infrastructure is adapting to the rapid acceleration of AI-driven demand. Across two days of panels, debates, and technical sessions, the focus centered on how the industry is navigating constraints tied to power, delivery timelines, and evolving design requirements, with companies such as ZincFive participating as a Mega Partner and exhibitor, showcasing its nickel-zinc battery solutions designed to support the growing power demands of AI-driven infrastructure. .

The 2026 event reflected a maturing market, where conversations have moved beyond forecasting growth and toward executing at scale. Sessions across the agenda addressed the realities of interconnection delays, rising construction costs, and supply chain limitations, while also highlighting the increasing role of policy, permitting, and community engagement in determining how quickly projects can move forward.

Artificial intelligence remained at the center of the discussion. Industry leaders explored how AI workloads are reshaping infrastructure requirements, particularly in terms of density, latency, and geographic distribution. As demand expands beyond core hyperscale markets, operators are being pushed to rethink where and how infrastructure is deployed to support both training and inference use cases.

Power infrastructure was a defining focus throughout the event. Panels such as “Eureka! How to power data centers in the age of AI” examined how traditional utility models are being supplemented with private generation, microgrids, and hybrid procurement strategies. As AI workloads increase power intensity, access to reliable and scalable energy is becoming one of the most critical factors influencing site selection and project viability.

Cooling and facility design also emerged as key areas of innovation. Discussions highlighted how rising rack densities are accelerating the adoption of liquid and hybrid cooling solutions, while new regulatory requirements and environmental considerations are shaping how these systems are deployed. The shift toward high-density compute is driving more fundamental changes in how data centers are engineered to support next-generation workloads.

Several speakers addressed how sustainability is evolving alongside these shifts. Simone Kramer, Head of Sustainability at Bloomberg, discussed the importance of balancing speed with responsible infrastructure development. Heather McGeory, Vice President of Sustainability at CoreWeave, focused on how efficiency is becoming a key metric in evaluating sustainability strategies as compute demands increase.

The event also highlighted workforce development through the “Powering the Next Generation – Student Workshop,” hosted by Nomad Futurist and Infrastructure Masons (iMasons), designed to introduce students to the digital infrastructure ecosystem and its career opportunities. The session featured industry leaders sharing practical insights and firsthand experiences, helping to clarify how the sector operates and where emerging talent can contribute. Ilissa Miller, Founder & CEO of iMiller Public Relations (iMPR), joined Vic Rose, Director, AI Inferencing, at Microsoft, and other participants in a discussion on the foundational role of digital infrastructure and the pathways available to the next generation of industry professionals.

Energy coordination between stakeholders was another area of focus. Gene Alessandrini, Senior Vice President of Energy & Location Strategy at CyrusOne, highlighted the need for closer collaboration between operators and utilities as demand profiles become more dynamic. Danielle Rossi, Global Director of Mission Critical Cooling at Trane, contributed to discussions on advancing thermal management strategies to support high-density AI environments.

From an investment perspective, Sharif Metwalli, Chief Financial Officer at Vantage Data Centers, examined how capital deployment strategies are evolving as developers and investors respond to increasing risks tied to power access, permitting timelines, and cost volatility. The conversation reflected a shift toward more disciplined investment, with a focus on projects that demonstrate long-term viability.

Beyond the formal sessions, DCD>Connect New York continued to serve as a key meeting point for the industry. Attendees spent significant time in one-on-one meetings and informal discussions, reinforcing the event’s role in facilitating partnerships, project development, and investment opportunities across the digital infrastructure ecosystem.

Looking ahead, the themes discussed in New York point to an industry entering a more execution-focused phase, where success will depend on the ability to align power, capital, and design with the realities of building infrastructure at scale.

Next, the industry will gather at DCD>Connect Virginia 2026 on November 3–4, 2026, bringing together more than 3,000 end users and specifiers across the cloud and colocation ecosystem to collaborate, build partnerships, and address key industry challenges. To learn more and register, visit DCD>Connect Virginia 2026 www.datacenterdynamics.com/en/dcdconnect-live/virginia/2026.

The post DCD>Connect New York 2026 Highlights Evolving Investment and Build Strategies appeared first on Data Center POST.

Originally posted on Sabey Data Centers.

Digital infrastructure serves as the crucial operating backbone for sectors like healthcare, finance, cloud platforms, and artificial intelligence. Because disruptions in these areas have immediate and widespread impacts that rarely stop at a single building, securing this infrastructure can no longer be treated merely as a perimeter issue. Instead, modern data centers must be recognized as dynamic, live operating environments where facility systems, infrastructure, software platforms, and customer expectations constantly intersect.

To address these complex needs, Sabey Data Centers integrates security directly into its overall operational resilience strategy. Rather than relying solely on visible physical barriers, this approach emphasizes disciplined processes, accountable operations, and careful environmental design that is supported over time. Protecting mission-critical infrastructure requires high visibility, consistency, and a deep security mindset that prioritizes long-term reliability, trust, and uptime.

Ultimately, customers are investing in confidence rather than just capacity. They need assurance that their provider truly understands the high operational stakes and weaves resilience into day-to-day execution. Sabey focuses on meeting this standard by continually building toward secure, resilient infrastructure that is tailored to the serious realities and demands of modern digital operations.

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The global data center heat exchanger market was valued at USD 2.8 billion in 2025 and is estimated to grow at a CAGR of 10.1% to reach USD 7.2 billion by 2035, according to a recent report by Global Market Insights Inc.

The industry is gaining strong momentum as advanced thermal management becomes critical to digital infrastructure performance. As artificial intelligence applications, cloud environments, and distributed computing architectures continue to scale, data center operators are prioritizing efficient and sustainable cooling technologies. Heat exchangers now play a central role in maintaining uptime, optimizing power usage effectiveness, and supporting higher rack densities. The market covers air-to-air, liquid-to-liquid, and refrigerant-based technologies integrated into rear-door systems, in-row platforms, and direct-to-chip liquid cooling architectures.

Increasing rack power densities exceeding 30-100 kW are accelerating the transition from legacy air-based models toward liquid and hybrid systems. The widespread deployment of AI processors and high-performance computing components is further elevating demand for compact plate and microchannel heat exchangers designed to improve thermal transfer while minimizing water and energy consumption. Growth is also supported by regulatory pressure, cost efficiency goals, and continuous innovation in hyperscale and colocation facilities.

The data center heat exchanger market from liquid-to-air heat exchangers segment accounted for 54% share in 2025 and is anticipated to grow at a CAGR of 9.7% between 2026 and 2035. This category represents the foundational cooling approach within many data centers, incorporating rear-door heat exchangers, chilled-water-based air handling systems, and integrated coil technologies. These solutions rely on water’s strong heat absorption capacity, transferring thermal energy from server exhaust air through engineered exchange surfaces before recirculating conditioned air back into the facility. Their established infrastructure compatibility continues to drive widespread adoption.

The air-cooled systems segment held a 55% share in 2025 and is forecast to grow at a CAGR of 9.8% through 2035. This segment includes direct expansion refrigerant technologies, chilled water air handlers, standalone chillers, and economizer-based free cooling configurations. Long-standing industry familiarity, proven reliability, and compatibility with raised-floor airflow designs have reinforced their dominance. Air-cooled platforms remain particularly effective for enterprise environments operating at 5-15 kW per rack, where installation costs and operational simplicity remain primary considerations.

United States data center heat exchanger market generated USD 782.1 million in 2025 and is estimated to grow at a CAGR of 9.4% during 2026-2035. Market leadership is supported by continued hyperscale development, strict energy efficiency mandates, and oversight from federal regulatory bodies. Rising demand for compute-intensive workloads and digital services is accelerating the shift toward high-performance cooling technologies, with liquid-to-air heat exchangers recognized for dependable and energy-efficient operation.

The competitive landscape includes key industry participants such as Airedale, Alfa Laval, CoolIT Systems, Eaton, Munters, Nortek Air, Rittal, Schneider Electric, STULZ, and Vertiv, all contributing to product innovation and global market expansion. Companies operating in the global data center heat exchanger market are strengthening their market position through technology innovation, strategic partnerships, and capacity expansion initiatives. Manufacturers are investing heavily in research and development to introduce advanced liquid cooling systems, compact microchannel designs, and energy-efficient hybrid solutions tailored for high-density data centers. Strategic collaborations with data center developers and infrastructure providers enable early integration of customized thermal management systems. Firms are also expanding manufacturing facilities and regional distribution networks to meet growing demand across North America and other high-growth regions. In addition, companies are focusing on sustainability-driven product enhancements that reduce water consumption and carbon emissions, aligning with regulatory expectations and enterprise ESG commitments.

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In ever-higher-density data center environments, unplanned downtime is costly. Whether it’s interrupting AI training workloads or impacting strict service-level agreements, the financial fallout can be severe.

Data center resilience is more important than ever.

Backup generator systems are a vital part of the sector’s resilience architecture. But while generator engines have been optimized and made more efficient, far less time has been spent engineering their starting systems – which often prove to be the weak point in backup generator reliability.

Now, a new ‘systems thinking’ approach is tackling this issue, while streamlining build time of the power distribution system.

Power Remains the Leading Cause of Outages

Data center outages are becoming less frequent, according to Uptime Institute’s most recent survey, but also more costly. However, the report also points out that, “Power remains the leading cause of impactful outages.” And when power fails, resilience depends on effective backup systems.

The Hidden Genset Weak Point 

Caterpillar and Cummins, along with NFPA, have all stated that the primary cause of standby generator failure is the starting battery system.

Too often, this stems from a ‘loose piece’ construction model. Batteries, chargers, redundancy components, racks, disconnects, and wiring are sourced as individual pieces from multiple vendors. These are then assembled on-site in a complex, costly, and high-risk integration processes.

Why Loose-Piece Construction is Riskier

Many starting system failures stem from this approach. Each component is viewed in isolation. Even if optimized to meet design specifications, it may not operate as efficiently when combined with the other elements.

This is especially true for batteries: the single greatest point of failure. Flooded lead-acid batteries are commonly chosen due to low cost and availability.

However, these batteries were designed for vehicle use, where they are only recharged by the alternator after cranking. In generator starting systems, on the other hand, the charge must be continuously maintained and the system kept on standby.

Under these conditions, battery life is severely curtailed, necessitating proactive replacement every 2-3 years. Yet even with regular maintenance, sudden, catastrophic failure still occurs.

Introducing Systems Thinking

Systems thinking is reshaping starting system design by tackling the underlying causes of failure. This means shifting attention from batteries in isolation to how they are charged and operate within the genset.

With this approach, all the components are engineered to work optimally together. It starts with selecting long-life, high-performance battery chemistries that need much less maintenance and are not harmed by constant float charging.

Smart chargers, hardened for harsh environments, monitor and respond to real-time conditions, optimizing the charging profile for the specific battery type, temperature and other factors.

Packaged engine starting systems house high-performance batteries with an integrated charger, best battery selectors, alternator and engine panel power redundancy, DC disconnects and racking, ensuring the greatest total system reliability in the smallest possible footprint.

Because these integrated systems are ordered as a single part, optimized and factory-tested by the manufacturer, they enable plug-and-play installation. Integration shifts from field conditions to a controlled factory environment, reducing points of failure while removing time-consuming, high-risk electrical work from the critical path.

A New Foundation for Resilience

Ever-increasing demand and AI-fueled growth have driven a technological transformation in chips, server racks, and cooling techniques. That evolution must now extend to a key element of data center resilience: backup generator starting systems.

Loose-piece construction no longer meets the resilience demands of today’s data center industry. When power fails, and genset reliability really counts, systems thinking and a new approach to starting system engineering are addressing this hidden weak point in data center resilience.

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About the Author 

Olen Scott, Chief Commercial Officer, SENS

Olen has over 30 years of experience leading high-growth businesses across global markets, from early-stage startups to Fortune 50 companies. At SENS, he oversees all sales, marketing, channels, and customer success, driving the company’s commercial strategy and growth.

The post Data Center Power Resilience: Systems Thinking for Reliability appeared first on Data Center POST.