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.

# # #

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.

# # #

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.

# # #

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.

# # #

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.

# # #

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”.

# # #

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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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As demand for AI and cloud infrastructure accelerates, the industry is entering a period of reassessment. Operators, investors, and ecosystem partners are reevaluating how infrastructure is designed, powered, and deployed to support the next phase of growth.

The upcoming infra/STRUCTURE Summit 2026, hosted by Structure Research, will take place October 6–8 in Las Vegas, bringing together more than 600 senior executives across hyperscale, data center, cloud, edge, and AI infrastructure. Now in its seventh year, the event continues to serve as a vendor-neutral forum for industry leaders to connect and exchange insights.

This year’s theme, “Interlude,” reflects a moment of transition across the digital infrastructure landscape. As AI workloads scale and demand intensifies, organizations are recalibrating strategies around power availability, deployment models, connectivity, and capital allocation. The summit will focus on how this shift is influencing the next phase of infrastructure development.

“infra/STRUCTURE continues to serve as a critical platform for understanding where the infrastructure market is today—and where it’s going next,” said Philbert Shih, founder and managing director of Structure Research. “The theme ‘Interlude’ captures the importance of this moment as the industry recalibrates to support the next wave of AI and cloud demand.”

The 2026 program will include a dedicated day for hyperscale and neocloud-focused 1:1 meetings, followed by two days of curated content and executive panels. Discussions will center on AI infrastructure scaling, modular deployment strategies, and the continued evolution of cloud platforms.

In parallel, Structure Research has released its updated 2026 NeoCloud Report, offering analysis on emerging cloud models and the growing influence of neocloud providers on infrastructure demand.

The summit is supported by a range of sponsors across the digital infrastructure ecosystem, including Duos Edge AI and Foresight, reinforcing its role as a key industry gathering point.

Early bird registration is open through April 30.

Read more in the press release here.

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For the past few weeks, I have been writing a series of article about the national data center debate from a few angles. The absence of coordinated planning frameworks doesn’t just affect where infrastructure gets built,  it also shapes how projects are perceived. Increasingly, debates that appear to focus on environmental impact or land use are actually reflections of deeper governance challenges. Digital infrastructure has become a proxy conversation for political cycles, institutional readiness, and community trust. You can read the previous posts in my series here, to learn more.

Across the United States, debates about data center developments are intensifying. Public hearings are becoming more emotional. Moratoria are being proposed. Projects are being delayed or canceled.

From the outside, it can appear that communities are simply pushing back against data centers often framed as environmental or land-use disputes.

But the reality is more complex.

Increasingly, these debates are not about data centers themselves. They are about governance, political cycles, institutional readiness, and the absence of shared planning frameworks. As a former elected official having served two-terms in Westchester County, New York, it is clear that the issue has become political, and not about data centers themselves, but about how decisions are made at the county and local level.

Data center and other digital infrastructure developments intersect with multiple policy domains at once: Power generation and grid capacity;  Water use and sustainability; Tax incentives and economic development strategy; Land use planning; Even national competitiveness and security considerations

Few other forms of development carry this level of cross-sector impact.

At the same time, many of the leaders responsible for evaluating these projects are operating under significant structural constraints. As I tell nearly anyone who will listen, as a former elected official myself, the truth is, anybody can get elected. Many officials simply don’t have the background to understand how complex digital infrastructure development really is.

This is not a criticism, it is a reflection of how local governance works. Elected officials are expected to respond to immediate community needs while also making decisions about long-term infrastructure investments that may shape regional competitiveness for decades.

Election cycles further complicate the equation. Leadership turnover can disrupt continuity. Projects that begin under one administration may face new skepticism under the next. Without long-term planning constructs in place, infrastructure decisions can become reactive and episodic rather than strategic.

The industry itself has also contributed to the challenge. Historically, development efforts often prioritized speed, confidentiality, and incentive negotiations. These approaches were understandable in competitive markets, but they have also created trust gaps.

Communities see large capital commitments, complex tax structures, and rapid land acquisitions. They may not fully understand the broader economic ecosystem these projects activate. When technical explanations are dense and timelines feel compressed, uncertainty grows.

And uncertainty often leads to caution. My personal approach and thesis to solving this challenge is that community resistance is often not opposition, it’s overwhelming.

When faced with decisions involving unfamiliar technologies, large-scale energy demand, and long-term environmental considerations, saying “no” can feel like the most responsible option, especially when neutral guidance is limited.

This is why engagement models must evolve.

Community engagement initiatives must reframe infrastructure developments from persuasion to translation. Programs, like my company’s Groundswell™ initiatives, focus on helping companies and the communities they want to enter, to understand the implications of development within their own economic and civic context. It emphasizes early education, identification of local priorities, and structured dialogue that reduces fear rather than escalating it.

At its core, the approach is grounded in a simple principle: Helping communities help themselves is always the best approach,  because they literally don’t know what they don’t know.

When stakeholders are equipped with shared frameworks and credible information, conversations shift. Infrastructure proposals become part of broader economic planning discussions rather than isolated flashpoints.

The debate then moves beyond whether to build, toward how to build responsibly, sustainably, and strategically.

Digital infrastructure will continue to expand. The real question is whether the processes guiding that expansion will mature at the same pace.

Understanding that the debate is not truly about data centers may be one of the most important steps forward.

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.

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Originally posted on 1547 Realty.

Artificial intelligence is changing what enterprises, service providers, and cloud platforms need from digital infrastructure. As AI environments scale, success depends on more than compute capacity alone. It also depends on how efficiently data can move between networks, clouds, applications, and users. For fifteenfortyseven Critical Systems Realty (1547), that reality reinforces a principle that has long shaped the company’s approach to digital infrastructure: interconnection is a core enabler of performance, resilience, and growth.

A New AI Infrastructure Reality

AI workloads place new pressure on the network layer of the data center. Training workloads require the movement of large datasets across systems, while inference workloads demand low-latency access closer to users and applications. Deloitte notes that rising AI adoption is increasing the need for power, connectivity, and infrastructure capable of supporting more demanding digital workloads. As HPE explains in its overview of AI data center networking, AI environments rely on fast, high-capacity networking to keep data flowing efficiently between compute, storage, and end-users.

That shift changes how organizations evaluate data center environments. The question is no longer only whether a facility can deliver power and space. Increasingly, the question is whether it can support dense, flexible connectivity across carriers, clouds, internet exchanges, and service providers.

Why Network Density Matters for AI Performance

Network density has always been valuable in carrier hotels and interconnection hubs, but it is becoming even more relevant in the AI era. In highly connected environments, customers can access multiple carriers, cloud platforms, and partners within the same facility, reducing unnecessary network hops and improving routing flexibility. That can support lower latency, stronger resilience, and more efficient data exchange across distributed environments.

To continue reading, please click here.

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As demand for high-capacity, low-latency connectivity continues to grow, the ability to quickly access and deploy network services is becoming increasingly important for channel partners and the customers they support. Yet, the process of sourcing connectivity has often remained fragmented, requiring multiple steps across different systems before a service can even be activated.

A new partnership between Lightpath and CableFinder is designed to change that.

CableFinder’s platform is built to simplify quoting and contracting for technology service distributors (TSDs) and their partners. By integrating Lightpath’s fiber network, the platform will provide direct, API-driven access to Lightpath services across key U.S. markets. Once live, partners will be able to check serviceability, access pricing, generate contracts, and initiate orders within a single session—moving from qualification to signed agreement in minutes.

The integration also expands access to one of the most densely built, owned fiber networks in the United States. Lightpath owns and operates more than 12,100 route miles of fiber, connecting over 17,500 lit locations and 190+ data centers and subsea cable landing stations across major metro markets. The network spans regions including the New York City metropolitan area, Long Island, New Jersey, Boston, and Ashburn, and is engineered to support cloud, AI, and mission-critical workloads.

Because Lightpath owns its infrastructure end to end, partners and their customers work with a single provider, supported by one SLA and one operational team. This model simplifies network deployment while maintaining the performance and reliability required for today’s data-intensive environments.

By bringing Lightpath into the CableFinder platform, the partnership broadens how channel partners can access and deploy fiber connectivity. The result is a more automated, streamlined experience designed to reduce friction and accelerate the path from inquiry to deployment.

The integration is expected to go live early this summer, with Lightpath and CableFinder continuing to engage with partners ahead of the launch.

Read more in the press release here.

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Why AI Inference Benchmarking Has Become a Capital Allocation Strategy

By Mike Hodge, AI Solutions Lead, Keysight Technologies

During the early years of generative AI, the overarching strategy was straightforward, at least from an infrastructure standpoint: deploy more GPUs. Wash, rinse, and repeat.

Back then, it was a race to train larger models. Performance was measured in scale (parameter count, cluster size, training throughput) and capital flowed toward compute density. At the time, it was the clearest lever for progress.

Fast forward to today, and inference is changing that logic.

Inference is not episodic, not bounded, and isn’t as controlled as training. It’s a continuous system, directly tied to user experience. But more than anything, inference is where AI stops being a research artifact and becomes a revenue generation machine.

High stakes like these, however, put a premium on performance. When revenue is on the line, inefficiency isn’t measured in latency; it’s measured in cost.

Inference Is an Economic System, Not Just a Technical One

Every inference request is a transaction. It consumes compute cycles, memory bandwidth, storage access, network traversal, security enforcement, and energy. And each generated token represents a measurable cost.

But unlike training, where inefficiencies can be amortized across long-running jobs, inference inefficiencies are persistent. They show up in every response. Because of that, even the smallest inefficiency — a few milliseconds of unnecessary latency, a slight drop in sustained tokens per second, or a minor imbalance in memory allocation — compounds across millions or billions of requests.

Beyond the snowballing effect of inefficiencies, there’s also the risk of getting a deployment wrong. Between personas, pipelines, models, GPUs, memory, and storage networks, inference infrastructure offers an almost limitless amount of choice for AI deployments. But hardware isn’t just expensive, it’s also in exceedingly short supply. That means the cost of inefficiency can’t be constrained to a single point in time. Given AI’s lengthy procurement timelines, a few sub-optimal choices can set a data center back by a year or more.

This the major reason why inference economics are fundamentally different from training economics. Training inefficiency slows progress, while inference inefficiency erodes margin. That distinction is key; it means we need to take a different approach in how inference infrastructure is validated.

The Problem with Peak Metrics

Most AI benchmarking environments still rely on the idea of “peak” measurements. Think about things like peak throughput, peak GPU utilization, and peak token generation under idealized conditions. These kinds of metrics are attractive because they’re easy to communicate and suggest strength and headroom. But inference economics are not governed by peak behavior. They are governed by sustained performance under variable workload conditions.

Real inference environments operate under a different set of criteria. Things like burst concurrency, mixed prompt sizes, and asymmetric prefill and decode phases all have major influence on inference systems. But these dynamics don’t produce smooth averages; they produce nonlinear behavior like latency cliffs, token pacing instability, utilization imbalance.

If benchmarking does not model these realities, organizations risk major capital investments on an incomplete understanding of performance.

Architectural Imbalance Is a Hidden Tax

Inference systems are tightly coupled ecosystems. Compute, memory, networking, storage, and security layers interact continuously. That means that when one layer underperforms, the performance impacts cascade across other layers.

Consider a scenario where decode pacing is constrained not by GPU capacity, but by subtle network jitter or KV-cache retrieval latency. GPU dashboards may show underutilization. The instinctive reaction might be to scale accelerators to increase headroom. But if the actual constraint lies upstream or downstream, additional GPUs increase capital expenditure and power draw without increasing sustained token output. The imbalance persists, and costs increase.

Workload-accurate benchmarking exposes imbalances like these. By modeling realistic workload personas and correlating inference-native metrics (tokens per second, latency percentiles, and concurrency thresholds) across the full stack, engineering teams can identify which subsystem fails first under real conditions. This effectively changes the calculus of AI optimization. In place of relentless expansion, you have continuous rebalancing.

Using Realistic Benchmarking as a Financial Lever

In inference infrastructure, predictability is as important as speed. After all, customers buy reliability and responsiveness. They sign contracts based on latency percentiles and service-level agreements. When latency expands unpredictably, providers compensate by provisioning excess capacity to maintain guarantees. Meanwhile, costs per token rise due to idle overhead.

Workload-accurate benchmarking, by contrast, helps providers avoid this scenario by revealing where variability originates. It allows teams to measure not just average latency, but how tail behavior responds to burst concurrency and prompt diversity. Moreover, it also shows how guardrails and policy layers affect response pacing under adversarial conditions.

Understanding variability at this level means providers can right-size network headroom instead of overinflating it, yielding considerable savings along the way.

Energy Efficiency Is Increasingly Strategic

Power is becoming one of the most constrained resources in AI infrastructure planning. Data center expansion isn’t just limited by hardware availability; energy budgets play a substantial role as well.

Inference runs continuously. Unlike training clusters that cycle through jobs, inference infrastructure often operates at sustained load levels tied directly to user demand. If systems aren’t properly balanced, power inefficiencies add up exponentially. Overprovisioned GPUs consume copious amounts of energy, network retransmissions increase processing overhead, and storage latency overtaxes compute resources.

Workload-accurate benchmarking introduces a more meaningful metric: sustained tokens per watt under realistic workload conditions. This measurement reframes optimization in energy-constrained environments. It’s not just about maximizing throughput; it’s about economically efficient optimization. And in energy-constrained data centers, that distinction determines ROI.

Continuous Benchmarking Prevents Configuration Drift

Inference workloads evolve rapidly. Prompt distributions change with user behavior, models evolve, retrieval systems expand, and agentic workflows introduce new execution paths. That means infrastructure that is balanced today may drift tomorrow.

Therefore, workload-accurate benchmarking must become continuous governance. By treating it as an operational discipline, network teams can monitor efficiency drift and validate architectural changes before scaling.

In this sense, benchmarking becomes a financial safeguard. It means organizations can find and fix performance regressions early, validate cost efficiency against realistic workloads, and align infrastructure expansions with revenue forecasts.

Inference Is a Competitive Advantage

The next competitive divide in AI infrastructure won’t depend solely on hardware access. It will be shaped by how intelligently that hardware is deployed.

Organizations that benchmark inference using simplified traffic models risk trapping themselves in a cycle of reactive scaling. They will respond to instability by adding capacity and treat hardware as the primary lever for solving systemic imbalance.

On the other hand, organizations that adopt workload-accurate benchmarking as a core engineering discipline will be far more proactive. They will identify potential bottlenecks before allocating capital and optimize architectures before expanding them.

One approach consumes margin; the other creates it.

Inference is where AI revenue materializes. And in revenue-generating systems, precision is profit. Workload-accurate benchmarking is not simply a technical refinement. It is a strategic mechanism for controlling total cost of ownership, stabilizing energy consumption, and protecting return on investment.

In the inference era, the most important question is no longer “How powerful is our infrastructure?” It’s “How efficiently does our infrastructure convert capital into sustained value?”

Answering that question begins with measuring reality — not generic averages or peak potential. And for organizations serious about the economics of AI, that distinction can be the difference between profit and loss.

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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 Value of Certainty appeared first on Data Center POST.

Effective fire prevention in data centers requires a coordinated approach that adapts to evolving hazards such as high-power densities, lithium-ion UPS systems and operational changes. Success depends on early and frequent design integration, adherence to codes and the selection of detection and suppression technologies suited to specific risks. Early warning systems – typically air-aspirating smoke detectors – are vital in environments with high airflow and rapid smoke dispersion. Lithium-ion batteries pose challenges with thermal runaway, ventilation and gas detection, necessitating informed system choices. Infrastructure and layout decisions, including interior structures and hot aisle containment areas, demand flexible sprinkler system approaches. Overall, proactive, integrated fire protection is essential for safety, operational continuity and compliance as data centers expand in size and complexity.

Designing for Change 

Change is constant in data center projects and operations. System density, client occupancy and spatial configurations are continually evolving, requiring fire protection strategies that can accommodate these shifts. A design philosophy built on flexibility ensures that protection systems remain effective despite operational changes. For example, specifying Extra Hazard sprinkler density can accommodate a potential switch to lithium-ion UPS systems, while matching overhead coverage ensures hot-aisle containment locations remain protected regardless of quantity or location.

Air-aspirating smoke detection systems are widely used in data centers due to their sensitivity and ability to operate effectively in high-airflow environments. To minimize false alarms and ensure these systems respond appropriately, they should be baselined during commissioning. Seasonal variations, such as wildfire smoke, should also be monitored to protect equipment.

Lithium-Ion UPS Systems

The use of lithium-ion UPS systems has expanded significantly across data center facilities in recent years, appearing in data halls, adjacent electrical spaces, outdoor containers or all three locations simultaneously, with increasing energy densities. It is important to note, however, that the battery density of these systems is generally significantly lower than what you might see in a grid-scale system.

The smaller battery sizes typical of data center UPS installations, coupled with the relatively large room volumes in which they’re located, often alleviate explosion concerns under likely thermal runaway scenarios. In many cases, explosion control can be achieved with modest or even zero ventilation rates, maintaining likely explosive gas concentrations below 25% of the lower flammability limit. That said, each configuration should be analyzed individually to ensure appropriate hazard mitigation measures are in place.

Future-Proofing Fire Protection

As data centers continue to grow in scale and complexity, fire protection strategies must evolve alongside them. The integration of lithium-ion UPS systems, increasing power densities and frequent layout modifications demand a design philosophy built on flexibility and foresight. By implementing Extra Hazard sprinkler densities, properly commissioned air-aspirating detection systems and thoughtful ventilation strategies, facility operators can accommodate inevitable changes while maintaining robust protection. While the relatively lower battery densities and larger room volumes in data center applications often mitigate explosion risks compared to grid-scale installations, careful analysis of each configuration remains essential. Ultimately, successful fire protection in modern data centers requires not just compliance with current codes, but a forward-thinking approach that anticipates future modifications and emerging technologies, ensuring that safety systems remain effective throughout the facility’s lifecycle, regardless of how operational needs evolve.

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About the Author

Alison Wakelin, Market Leader South, Fire Protection Specialist, Jensen Hughes

Alison is a Market Leader for Jensen Hughes’ Southeast region. She has been the Fire Protection Designer of Record on more than 200 Federal projects for the DoD, and her specialized completed projects include: barracks, child development centers, military working dog facilities, hospitals, exchanges, elementary schools and aircraft hangars. This work includes design of fire alarm, sprinkler, standpipe and fire pump systems, as well as analysis of the overall life safety approach for the buildings. Her work also focuses on Data Centers – the use of Lithium Ion (Li-ion) battery UPS systems, and sprinkler and VESDA system design. She has performed design work for the Veteran’s Administration on hospital and clinic projects, while her commercial work includes analysis of high hazard storage, grain and paper dust and flammable liquids projects.

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In the high-stakes world of data centers, where AI workloads demand instantaneous power and safety can’t be compromised, ZincFive^® has quietly been rewriting the rules. Today, the Oregon-based innovator announced a major achievement: surpassing 2 gigawatts (GW) in power delivered or contracted globally. This isn’t just a number – it’s a testament to the growing adoption of nickel-zinc (NiZn) batteries as the go-to alternative for uninterruptible power supplies (UPS), alongside legacy lead-acid and lithium-ion systems.

Picture this: Data center operators face exploding energy needs from AI training and inference, all while navigating fire risks, space constraints, and sustainability mandates. ZincFive stepped in with its patented NiZn chemistry, offering high power density in a compact footprint, eliminating thermal runaway risk, and lower lifecycle emissions. This milestone reflects contracts and shipments that have scaled this technology across global facilities, proving it thrives in mission-critical environments without the tradeoffs of other batteries.

At the heart of this surge is ZincFive’s expanding portfolio. The BC Series, headlined by the BC 2 AI battery cabinet, bridges traditional backup power with dynamic AI demands. Designed for both steady-state and bursty loads, it delivers reliable performance where milliseconds matter. Complementing this, the newly launched NiZn Retrofit Kit lets operators replace lead-acid batteries in existing cabinets without requiring major system changes, just drop-in upgrades that slash costs, disruption, and complexity in brownfield sites.

“This 2 GW mark underscores the real-world performance of our technology and the trust our customers have in it,” said Tod Higinbotham, CEO of ZincFive. He highlighted how the company is ramping up manufacturing to match accelerating demand, fueled by NiZn’s blend of safety, sustainability, and power.

ZincFive’s rise builds on a track record of accolades, including TIME’s America’s and World’s Top GreenTech Companies lists, an Edison Award for resilient solutions, and CleanTech Breakthrough’s Overall Innovation of the Year. These honors spotlight how NiZn leverages abundant, recyclable materials to propel “The Power of Good Chemistry^®” forward.

As data centers evolve into AI powerhouses, ZincFive’s 2 GW milestone signals a pivotal shift. Operators worldwide are evaluating alternatives to legacy battery technologies in favor of solutions that offer improved safety, performance, and sustainability. With global deployments locked in and production expanding, the company is poised to energize the next wave of digital infrastructure.

For full details, please read the press release here.

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CloudFest Americas is expanding its role in the Internet infrastructure ecosystem following a newly announced partnership with the Internet Infrastructure Coalition (i2Coalition). The collaboration reflects a broader effort to bring business, technology and policy conversations into a more unified environment as the industry responds to accelerating demand, regulatory pressure and evolving security requirements.

By aligning two organizations with deeply connected audiences, the partnership creates a more structured forum for addressing both operational and policy challenges. CloudFest, known globally for its cloud and hosting events, and i2Coalition, which represents companies building and operating the Internet’s core infrastructure, are formalizing a relationship that has long existed across their communities. The goal is to provide a setting where infrastructure operators, service providers and policymakers can engage more directly on the issues shaping the Internet’s future.

As part of the partnership, i2Coalition will play an active role in shaping event programming, supporting speaker development and encouraging executive-level participation. The collaboration also extends to i2Coalition-affiliated initiatives, including the Secure Hosting Alliance, Domain Name Association, VPN Trust Initiative, and Ethical Web Data Collection Initiative, helping broaden representation across the ecosystem. Christian Dawson, executive director of i2Coalition, has been named chief evangelist of CloudFest Americas, further strengthening alignment between industry and policy discussions.

Taking place Nov. 11–12, 2026, in Miami and co-located with NamesCon Global, CloudFest Americas will bring together cloud providers, hosting companies, domain registries and registrars, cybersecurity leaders and policymakers. The event is designed to serve as a central meeting point for stakeholders navigating the technical, economic and regulatory forces influencing digital infrastructure development.

As the industry continues to scale and diversify, initiatives like this highlight the growing need for collaboration across sectors that have traditionally operated in parallel. Register to attend CloudFest Americas to connect with peers and take part in conversations shaping the future of Internet infrastructure.

Learn more and secure your spot at CloudFest Americas 2026 cloudfest.com/americas.

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As demand for digital infrastructure accelerates across the United States, communities are increasingly being asked to evaluate projects that carry long-term implications for power, land use and economic development. Many municipalities, however, lack the frameworks needed to assess these opportunities with confidence, creating a growing gap between industry momentum and community readiness.

This challenge will be a focal point at Connected America 2026, taking place April 14-15 in Dallas. Ilissa Miller, board member of the OIX Association and CEO of iMiller Public Relations, will participate in a fireside chat on April 14 titled “From Resistance to Readiness: Why Communities Need a Digital Infrastructure Framework,” alongside Peter Murray director at Dense Networks. The session will explore how communities, developers and policymakers can better align on infrastructure planning through practical frameworks and clearer communication.

As investment in data centers, fiber networks and AI infrastructure expands, municipalities are being asked to make decisions that will shape their regions for decades. These projects involve complex considerations related to energy, water, zoning and long-term economic impact. Without consistent benchmarks or shared frameworks, communities often approach each project independently, limiting their ability to evaluate tradeoffs and outcomes effectively.

Miller’s perspective is shaped by her work spearheading the Digital Infrastructure Framework Committee (DIFC) within the Open Infrastructure Exchange (OIX), which is focused on developing vendor-neutral guidance to support community-level planning. The initiative aims to establish a structured approach that enables municipalities to evaluate infrastructure projects more consistently while supporting collaboration among developers, investors and public sector stakeholders. By creating a common framework, the effort seeks to reduce uncertainty and improve the decision-making process.

The session will also address a broader industry narrative that frames communities as resistant to development. In many cases, hesitation stems from uncertainty rather than opposition. Communities are being asked to make high-stakes decisions without standardized tools or clear guidance. Providing structure and context can help shift that dynamic toward more informed engagement.

In parallel with her work at OIX, Miller developed the GroundswellTM methodology through iMPR to improve how infrastructure projects are introduced and communicated. The approach emphasizes transparency, early engagement and stakeholder alignment, helping build trust and support more effective planning outcomes.

Connected America brings together industry leaders, policymakers and technology providers to address the future of connectivity and infrastructure development across the country, with increasing focus on aligning growth with community readiness.

For more information about the OIX Association and the Digital Infrastructure Framework Committee, visit www.oix.org/standards-and-certifications/oix-dif-standard.

For more information about iMiller Public Relations and its services, visit www.imillerpr.com.

To learn more about upcoming events in the terrapinn portfolio, visit www.terrapinn.com/events.

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Are You Solving the Licensing Problem or the Infrastructure Problem?

Organizations exiting VMware face procurement spreadsheets full of hypervisor alternatives. Proxmox, Nutanix AHV, OpenStack, and Hyper-V compete for attention. IT teams build comparison matrices tracking licensing costs, migration timelines, and feature parity.

The comparison matrices miss the actual decision.

Hypervisor replacement solves the licensing problem Broadcom created. Infrastructure consolidation solves the operational problem that made VMware painful and expensive before Broadcom acquired it. These are different problems with different solutions and different five-year outcomes.

The Hidden Cost Structure

VMware licensing accounted for 15-25% of total infrastructure costs for most organizations. Broadcom’s price increases moved that to 30-40%. Organizations reacted to the visible cost increase. The reaction treats licensing as the problem. Licensing is a symptom.

The actual problem is infrastructure fragmentation across multiple products with independent lifecycles, separate support relationships, and continuous coordination overhead. Storage firmware updates happen independently from compute updates. Hypervisor patches follow different schedules than storage releases. Troubleshooting spans multiple vendor support organizations.

This coordination overhead consumes 40-60% of the infrastructure team’s time. Licensing costs appear on procurement spreadsheets. Coordination overhead appears as delayed projects, extended troubleshooting sessions, and infrastructure teams that never finish planning the next refresh cycle.

Hypervisor replacement changes the vendor receiving licensing payments. Coordination overhead remains unchanged.

Two Architectural Approaches

The “private cloud” category contains two fundamentally different architectural models. Vendors use identical terminology to describe them.

Orchestrated private clouds coordinate separate products through automation layers. Dell Private Cloud exemplifies this approach—PowerEdge servers, PowerStore or PowerFlex arrays, and external hypervisors managed through APEX automation. The automation provides value. It does not eliminate the underlying products or their independent lifecycles.

Integrated private clouds consolidate infrastructure functions into a platform. Compute virtualization, distributed storage, networking, and data protection run as native functions of a private cloud operating system unified into a single codebase. Organizations manage one platform rather than coordinating across five products.

The architectural difference determines operational outcomes. Orchestrated platforms improve coordination. Integrated platforms eliminate the need for coordination.

Operational Reality

Storage firmware updates illustrate the difference. Orchestrated platforms update storage arrays independently from compute nodes. IT teams check compatibility matrices, schedule maintenance windows, coordinate update sequences, and validate functionality across the stack.

Integrated platforms update storage with the platform. One update window. One validation process. No compatibility matrices across vendors.

Troubleshooting shows the same pattern. Orchestrated platforms require investigating across product boundaries—storage array problem, hypervisor scheduling problem, network bandwidth problem. Organizations coordinate across multiple vendor support organizations to isolate root cause. Integrated platforms troubleshoot within one system with unified diagnostics and single vendor accountability.

Platform-Level Efficiency

Integrated architectures deliver efficiency gains impossible in orchestrated models. Traditional hypervisors allocate cache per VM. Each VM carries its own cache allocation. The hypervisor over-provisions RAM to account for caching overhead across all VMs.

Integrated platforms handle caching at the platform level. VMs share a unified cache pool participating in global inline deduplication. VMs running on integrated platforms require 30-40% less RAM than identical VMs on traditional hypervisors.

Organizations migrating to integrated platforms consistently discover they need fewer servers than planned. Teams that spec six nodes based on VMware capacity requirements find four nodes sufficient after migration. At current DRAM prices, this architectural efficiency translates directly into fewer hardware purchases.

The Decision Framework

Organizations should evaluate VMware alternatives based on the problem they’re trying to solve.

Hypervisor replacement addresses VMware licensing costs, vendor dependence on Broadcom, and the need for feature parity with current capabilities.

Infrastructure consolidation addresses: Coordination overhead across multiple products, independent lifecycle management, multi-vendor support relationships, hardware refresh cycle misalignment, and team expertise fragmentation.

Both approaches solve legitimate problems. The question is which problem costs more.

Organizations with specialized infrastructure teams—dedicated storage, virtualization, and networking groups—already optimize for coordination overhead. Orchestrated platforms improve their existing model.

Organizations with lean IT teams cannot absorb coordination overhead. They need infrastructure that just works. Integrated platforms eliminate the coordination tax.

Validation Questions

• Ask vendors how many distinct products you’re managing. If the answer is more than one, ask about lifecycle coordination processes and troubleshooting across product boundaries.
• Ask where caching happens: VM-level or platform-level. The architectural difference determines memory requirements and server density.
• Ask about hardware requirements. Which servers are certified? Which storage arrays are required? The answers expose whether platforms coordinate complexity or eliminate complexity.

Looking Forward

The VMware crisis created an opportunity to fix infrastructure architecture, not just licensing costs. Organizations treating this as a hypervisor swap will face the same operational problems in three years. Organizations using this as an infrastructure reset position themselves differently.

The decision isn’t which hypervisor to choose next. The decision is whether infrastructure requirements demand architectural consolidation or component flexibility. Procurement sees licensing costs. Operations pays the coordination overhead. Make sure the decision framework accounts for both.

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About the Author

George Crump is Chief Marketing Officer at Verge.io, where he leads marketing and evangelizes VergeOS as a modern alternative to legacy HCI and public cloud infrastructure. He founded and led Storage Switzerland for 14 years, providing independent research on  storage, backup, virtualization, and cloud markets. With more than 30 years in IT, Crump has held executive roles in engineering, sales, marketing, and product strategy, including CMO and Chief Product Strategist at StorONE.

The post The VMware Exit Question No One Is Asking appeared first on Data Center POST.

Data Center POST had the opportunity to connect with Freddie Sarhan, Chief Executive Officer of Sapphire Technologies, who founded the company in 2021 after incubating the business within Calnetix Technologies for three years.

He joined Calnetix in 2018, heading business development in the industrial, energy, and aviation sectors. Prior to that, he served as Vice President of the Americas for Praxair Surface Technologies, overseeing the company’s business across North and South America. Earlier in his career, he was Vice President of Customer Service at Capstone Turbine Corporation.

Freddie began his career at Rolls-Royce as a member of the Trent industrial gas turbine development team, building a strong technical foundation that continues to inform his leadership today.

At Sapphire, Freddie is focused on advancing practical energy solutions that help customers generate clean power and improve the efficiency of their facilities. Under his leadership, Sapphire has recently expanded its presence in the data center market, where its turboexpander solutions create fast-to-deploy power and efficient cooling capacity.

Please share more about your background and how you came into your current position with Sapphire?

My background has been built across the industrial and energy sectors, with a strong emphasis on business development, operations, and scaling technology-driven businesses in ways that are both practical and customer-focused. Over the course of my career, I have had the opportunity to work across a range of markets, including energy, industrial systems, and aerospace-related applications, with a consistent focus on commercializing valuable technologies and building strong strategic partnerships.

What led me to found Sapphire was the opportunity to deploy a technology that addresses a clear and growing infrastructure need in a highly practical way. At Sapphire, we’ve developed a solution that recovers pressure energy that would otherwise be wasted and converts it into electricity and cooling. As market demand has evolved, particularly with the rapid expansion of AI and digital infrastructure, we recognized that our technology can play an important role in helping the data center sector manage its increasingly complex energy requirements. That combination of technical innovation and real-world applicability made the opportunity especially compelling to me.

What is Sapphire’s core mission?

At Sapphire, our mission is to recover otherwise wasted energy from gas infrastructure and convert it into monetized electricity and cooling. This is important to industry, and the data center sector in particular, as companies grapple with the challenges related to energy availability, operating efficiency, and speed to deployment.

Our technology enables customers to capture energy that already exists within upstream, midstream, and downstream gas infrastructure. High-pressure pipelines move gas across the world, but they are not equipped to recover pressure energy at the point of use. In data center applications, the recovery of this pressure energy enables operators to address two critical process needs simultaneously: generating baseload power and supplying efficient thermal management. By converting existing pressure drop into usable electricity and cooling, we provide a practical solution that improves site performance with no carbon footprint.

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

The digital infrastructure market is advancing rapidly, but many of the most pressing constraints are now infrastructure-based rather than computational. Operators are contending with limited grid availability, extended interconnection timelines, rising cooling demands, and increasing pressure to accelerate project delivery.

This environment underscores Sapphire’s product market fit. With our turboexpander platform, we are offering a practical, modular solution that can supply both power and cooling with very short equipment lead times. Turboexpander projects can be sited at the intersection of natural gas infrastructure and fiber access, creating thousands of deployment locations in the United States alone. For many operators, particularly those supporting edge, urban, and emerging AI deployments, speed is as important as scale. We see a market increasingly shaped by grid constraints, cooling requirements, and compressed project timelines, all of which drive demand for integrated solutions that can be deployed quickly and deliver immediate operational value.

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

Historically, Sapphire’s primary customer base has been in the natural gas value chain, including those exploration and production companies drilling new natural gas wells, pipeline companies operating both transmission and distribution assets, LNG facility operators, and other industrial facilities that have local power demand. This remains an important part of the business.

The data center sector has become a major area of focus over the past year. As demand for fast, behind-the-meter power solutions has accelerated, we’ve seen growing interest from data center developers, operators, and infrastructure partners seeking new ways to improve energy availability and reduce cooling load. As a result, the company’s customer base has evolved to include digital infrastructure stakeholders.

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

The primary concerns we hear from customers center on speed to power and reliability. The market needs to know how quickly a prime mover can be brought online, with what reliability the solution operates, and how it will affect their capital planning and long-term operating costs.

Our equipment packages are modularly designed so that they can be deployed quickly and integrated into existing infrastructure within months of order. One of the key advantages of turboexpanders compared to traditional power generation equipment is their dual use. Turboexpansion creates highly efficient electricity production, and it also creates instantaneous fluid cooling which can be integrated into a data center’s thermal management system through a heat exchanger. This enables operators to reduce refrigeration load while supplementing site power, creating a meaningful impact on performance metrics like power usage effectiveness.

Customers are also highly focused on uptime and maintainability. The Sapphire FreeSpin^® system was designed for the most demanding oil and gas applications. Mission-critical subsystems like magnetic bearings reduce maintenance and downtime and create long equipment life compared to conventional rotating equipment.

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

Yes. Data centers represent one of the clearest growth areas for Sapphire, particularly in edge computing and enterprise deployments that require power close to population centers or existing network hubs. The company is especially focused on projects where behind-the-meter generation and efficient cooling can materially improve the overall business case.

Beyond data centers, we continue to work to expand our offerings for the oil and gas sector. Many high-pressure natural gas wells have high concentrations of hydrogen sulfide, requiring equipment specified for these assets to have corrosion-resistant components and designs. These assets represent a sizable market, and Sapphire is developing a product offering for the application.

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

Sapphire’s product value proposition is built around a customers’ process efficiency and directly impacts sustainability metrics. By generating electricity without combustion and integrating the produced thermal cooling with existing facility processes, FreeSpin^® improves efficiency and reduces emissions exposure without fundamentally changing existing operations.

From a regulatory standpoint, we believe solutions that make better use of existing infrastructure will remain highly relevant and create attractive investment opportunities. While requirements may evolve by region, the need to lower operating costs, reduce wasted energy, and improve overall site efficiency is not going away. In data centers, in particular, sustainability is increasingly tied to practical infrastructure decisions related to power, water, and cooling. We view this as a more comprehensive approach to site efficiency, one that considers power generation, cooling, and overall campus energy use together.

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

Partnerships are central to Sapphire’s model because its technology sits at the intersection of several ecosystems. We work closely with gas infrastructure owners, data center developers, engineering teams, and electric utilities to identify sites where pressure energy recovery can create meaningful value.

In the data center market, this often requires coordination across multiple parties, including the gas company, the project developer, and the operator. Sapphire also works with strategic investors and industry partners that recognize the value of deploying energy solutions that are practical, modular, and fast to market. These partnerships help accelerate execution and bring more complete offerings to customers.

A recent example is Sapphire’s partnership with Anax Power to deploy an integrated power and cooling system for distributed data centers. Under the partnership, Sapphire is supplying its FreeSpin^® In-line Turboexpander for a co-located data center project designed to convert excess pipeline pressure into electricity and cooling. Anax will build, own, and operate the system. The collaboration reflects how Sapphire works with partners to deliver scalable infrastructure more efficiently and help customers unlock new capacity more quickly.

What are Sapphire’s core products or services?

Sapphire’s core product is FreeSpin^®, a turboexpander-generator that runs on pressure, consumes no water or fuel, and generates zero greenhouse gas emissions. Since 2021, it has been deployed throughout the energy sector to deliver reliable, clean generation.

Designed to the strictest requirements of the oil and gas industry, the turboexpander-generator contains a high-performance, high-speed permanent magnet generator with an integrated radial in-flow expansion turbine and low loss active magnetic bearings. The expansion turbine uses high-pressure gas to drive an electric generator and create a stream of cooled fluid that supplies heat exchange capacity to onsite operations.

FreeSpin® may be skid-mounted at the factory and is available in modules of 300-kilowatts electrical generation with 5 million BTU per hour cooling capacity. These systems enable infrastructure owners to rapidly add new power and cooling capacity, improve operational efficiency, reduce carbon emissions, and lower electricity costs.

What markets do you offer Sapphire’s solutions?

Sapphire offers its solutions globally to the gas infrastructure, utility, and data center sectors, and has supplied equipment for projects located in North America, Japan, Brazil, India, and Europe.

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

What is most compelling is the growing recognition that energy infrastructure and digital infrastructure are no longer separate conversations. Over the next decade, the industry is likely to move toward far more integrated site design, where operators evaluate power, cooling, land, connectivity, and resiliency together from the outset.

For Sapphire, the long-term objective is to make pressure energy recovery a standard component of site efficiency evaluation and behind-the-meter power planning. We see a meaningful opportunity to support a new class of data center deployments, particularly those that need to move quickly and operate efficiently in constrained environments. We believe that EPC companies and construction firms will adopt turboexpander systems into their standard drawing sets for natural gas-powered data center campuses.

What upcoming industry events will you be attending?

We are participating in several leading energy and digital infrastructure events this year, including Data Center World (exhibitor), Data Center Expo North America, 7×24 Exchange Spring Conference, Datacloud USA, Gastech (exhibitor), Yotta, OCP Summit, and DCD Virginia (exhibitor).

We hold active membership and participate with iMasons and AFCOM.

Is there anything else you would like our readers to know about your company and capabilities? 

What differentiates Sapphire is that the company is not approaching the data center challenge from only one angle. Turboexpanders address two of the industry’s most significant infrastructure constraints at the same time: power and cooling. Sapphire’s technology is designed to work with existing gas infrastructure, recover energy that would otherwise be wasted, and convert that into practical site-level value.

We believe there is an important role for modular, fast-deployment solutions in the market. Not every opportunity is a gigawatt-scale campus. There is growing demand for smaller and mid-sized projects that require reliable power, improved efficiency, and a practical path to operation. This is where Sapphire offers a particularly compelling solution.

Where can our readers learn more about Sapphire Technologies?  

For additional information, please visit our website, www.sapphiretechnologies.com, or contact the Sapphire Technologies team through the website contact page.

You can also learn more about our products and services through our resource library.

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About Sapphire Technologies

Sapphire Technologies develops and manufactures modular power generation and cooling solutions that convert pressure energy from gas infrastructure into usable electricity and cooling. Since 2021, Sapphire’s FreeSpin® In-line Turboexpanders have been deployed across the energy sector to deliver reliable, low-emissions power generation while recovering energy that would otherwise be wasted. Scalable from kilowatt- to megawatt-class installations, Sapphire’s systems help infrastructure owners quickly add power and cooling capacity, improve operational efficiency, lower electricity costs, reduce emissions, and create new revenue opportunities across data center, gas infrastructure, utility, industrial, and LNG applications. For more information, visit sapphiretechnologies.com.

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.

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The post Executive Profile: A Conversation with Freddie Sarhan, Chief Executive Officer of Sapphire Technologies appeared first on Data Center POST.

The data center industry faces a paradox. Operators need to modernize their power infrastructure to meet new demands – faster performance, better reliability, and stronger sustainability credentials. Yet much of the installed base of UPS systems remains anchored to an old technology: lead-acid batteries that require replacement every five to seven years and introduce significant operational and financial friction with each refresh cycle.

ZincFive^® is directly addressing this challenge with the announcement of its new NiZn Retrofit Kit, a turnkey upgrade designed to bring modern battery chemistry to existing infrastructure without the cost and complexity typically associated with power system overhauls.

The challenge is real. As data center power demands escalate – driven by AI workloads, edge computing, and cloud expansion – operators face mounting pressure to reduce lifecycle costs and improve reliability simultaneously. However, retrofitting existing UPS systems has historically meant choosing between a rock and a hard place: embrace cutting-edge lithium-ion technology with its attendant regulatory and safety complexities, or accept another cycle of short-life lead-acid replacements. Lithium-ion options remain difficult to deploy in retrofit scenarios due to infrastructure constraints and compliance concerns, leaving many operators feeling trapped in a costly replacement loop.

The NiZn Retrofit Kit changes that calculus.

Engineered for compatibility with common three-phase UPS architectures and legacy cabinet form factors, the kit functions as a true drop-in replacement for VRLA batteries without requiring cabinet redesign or operational disruption. What makes this significant isn’t just the engineering elegance – it’s what it enables operationally. The Retrofit Kit delivers up to 15-year battery life, effectively doubling typical replacement intervals and substantially lowering total cost of ownership.

“For the first time, operators have a practical path to extend battery life to 15 years while upgrading safety, sustainability, and performance – all within existing infrastructure,” said Tod Higinbotham, CEO of ZincFive, in the announcement.

The approach leverages ZincFive’s nickel-zinc chemistry, which avoids the thermal runaway risks associated with lithium-ion systems while sidestepping many regulatory headaches. For data center operators managing occupied or space-constrained environments, this matters considerably. The enhanced safety profile can help reduce compliance burden, while the long-life performance extends the runway between major capital expenditures.

From a sustainability perspective, the timing is noteworthy. As corporations face mounting pressure to report on environmental impact and regulatory bodies tighten emissions standards, the NiZn Retrofit Kit offers a practical avenue for improving sustainability metrics without wholesale infrastructure replacement. The kit’s use of more abundant, recyclable materials supports both operational goals and environmental objectives.

What’s particularly strategic about this announcement is the market it unlocks. ZincFive has primarily focused on new (greenfield) deployments of its BC 2 AI UPS systems. The Retrofit Kit pivots into the massive brownfield replacement cycle – the enormous installed base of aging VRLA batteries worldwide seeking alternatives. This transforms retrofit operations from expensive, one-off engineering projects into repeatable, scalable deployment models.

For data center operators tired of being squeezed by legacy infrastructure, the NiZn Retrofit Kit represents a genuine inflection point: modern performance and safety, delivered within the constraints of existing systems, without introducing additional complexity or risk.

To read the full press release, please click here.

The post Closing the Gap: How ZincFive’s New Retrofit Kit Unlocks Legacy UPS Infrastructure appeared first on Data Center POST.

For much of the past decade, cloud storage has been thought of as the inevitable future of enterprise infrastructure. The promise was simple: eliminate capital expenditures, scale infinitely and only pay for what you use. For some workloads, that model still makes sense.

But as data volumes explode and the economics of infrastructure shift, organizations are beginning to take a closer look at the long-term financial implications of relying primarily on cloud storage.

In a world where usage-based billing models and volatile component pricing introduce layers of uncertainty, the ability to forecast what storage will cost over the next five, seven or 10 years has become increasingly unpredictable.  Because of this, on-premises storage is regaining attention. It is a strategy that offers both financial clarity and long-term cost stability.

The Hidden Variable in Storage Economics

The price of data storage is influenced by more than just the service model. Underneath every storage platform, whether deployed in a corporate data center or inside a hyperscale cloud provider, are the same fundamental hardware components. Systems rely on some combination of DRAM, NAND flash, solid-state drives, hard disk drives and high-performance NVMe storage media. These components are subject to global supply and demand dynamics, manufacturing constraints and geopolitical factors.

When hardware costs rise, the effects ripple across the entire technology ecosystem. Server manufacturers, storage vendors and infrastructure providers all feel the pressure. Ultimately, those increases are passed along to customers – either through higher hardware prices or adjustments to service pricing. The difference in how those increases affect organizations depends on their storage strategy.

Locking in Costs with On-Premises Infrastructure

When a company invests in an on-premises storage infrastructure, it is making a capital purchase that establishes the cost structure for years to come. Hardware pricing is negotiated upfront, support agreements are defined in advance and the lifecycle of the system is planned as part of the procurement process.

This model provides something that is becoming increasingly valuable in modern IT budgeting: cost certainty.

Once the infrastructure is deployed, the majority of the expenses associated with storing data are known quantities. Power consumption, cooling requirements, support contracts and maintenance costs can all be estimated with a high degree of accuracy. Even future capacity expansions can be forecasted based on established procurement processes and predictable hardware pricing structures.

Over that lifecycle of an enterprise storage platform, organizations can fully amortize the original investment while continuing to use the same infrastructure. Lifespans of up to seven to 10 years allow businesses to extract more value from the systems they deploy while avoiding frequent large-scale replacements.

The result is a total cost of ownership that is easier to model and manage. Finance teams can build infrastructure budgets that extend years into the future without worrying that service pricing may change unexpectedly.

The Scalability Advantage Without the Disruption

Modern enterprise storage architectures are designed for gradual, non-disruptive expansion rather than “forklift upgrades.” Organizations can expand capacity within existing platforms without replacing core controllers or redesigning their storage environments. In some architectures, hundreds of additional drives can be integrated into the same system, allowing petabytes of new capacity to be deployed while preserving the original infrastructure investment.

This ability to scale incrementally helps organizations align storage growth with business demand. Capacity is added only when necessary, and expansion occurs within a familiar architecture that administrators already manage and maintain. Rather than start from scratch every few years, companies can organically grow their storage environments while maintaining operational continuity.

Cloud Storage’s Strengths and Trade-Offs

Cloud storage remains an important tool for many organizations, particularly when flexibility and rapid provisioning are required. Deploying new storage resources in the cloud can take minutes rather than weeks, eliminates the need for upfront hardware purchases and allows businesses to scale capacity quickly when workloads spike.

However, the financial model that enables that flexibility is also what introduces uncertainty. Cloud storage operates on usage-based billing structures that can change based on several variables, including how much data is stored, how frequently that data is accessed, how many copies exist for redundancy, and how often it is transferred across regions or out of the cloud environment entirely. API requests, transaction volumes and tiered storage access models can also affect billing.

These variables make long-term forecasting difficult. Even organizations that carefully model their expected usage patterns often find that real-world workloads behave differently than projected.

Predictability as a Strategic Advantage

For organizations that manage large volumes of long-term data such as backup archives, compliance records, medical imaging repositories, research datasets or video surveillance libraries, the ability to forecast storage costs over multiple years can be more valuable than short-term flexibility.

These types of workloads typically grow steadily and remain stored for extended periods. In such cases, the storage infrastructure becomes a foundational asset rather than a temporary service.

Owning the infrastructure that supports those workloads allows organizations to control when and how they expand capacity, negotiate hardware pricing on their own terms and avoid exposure to unpredictable service pricing changes. It also enables IT and finance teams to align infrastructure planning with broader business strategies, ensuring that storage investments support long-term data retention requirements without introducing budget volatility.

A Balanced Storage Strategy

Hybrid strategies, where organizations combine on-premises infrastructure with cloud services, are becoming increasingly common. Businesses can leverage the cloud for development environments, burst capacity or geographically distributed workloads while maintaining core storage systems within their own data centers.

The economic equation surrounding storage is changing. As data volumes continue to grow and the underlying hardware market becomes more volatile, predictability is emerging as one of the most important factors in infrastructure planning. For many organizations, owning their storage infrastructure is increasingly viewed as a practical way to achieve financial stability in an uncertain market. As data volumes continue to grow, having predictable storage costs may prove to be one of the most valuable advantages an IT strategy can offer.

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About the Author

Judy Kaldenberg, Senior Vice President of Sales & Marketing, Nexsan

Judy Kaldenberg is the Senior Vice President of Sales & Marketing at Nexsan, bringing deep expertise in developing and executing marketing and sales strategies. Prior to her current role, Judy served as Director of Marketing at Genus Technologies, and before that held the position of Manager of Channel Marketing at Kodak Alaris. Her earlier career includes account and alliance management at Avtex, a customer experience consulting and solutions provider. She holds a BA in Business Administration and Marketing from Truman State University.

The post Cloud Costs Going Through the Atmosphere? Owning Your Storage Infrastructure Can Provide Significant Financial Advantages appeared first on Data Center POST.

If community overwhelm is one of the defining dynamics shaping infrastructure decisions today, the next question becomes: how do we move from reactive project-by-project debates toward more intentional planning? Historically, the United States built foundational digital infrastructure through coordinated clustering and long-term economic logic. The current AI build cycle, however, is unfolding far more rapidly,  and often without a shared strategic vision. You can read the article in my series here, to learn more. 

The United States did not build the modern internet by accident.

Network infrastructure expanded through coordinated clustering, particularly around population centers, enterprise demand, and connectivity hubs. Cities became exchange points. Regions evolved into digital corridors. Capacity scaled in response to real economic gravity. 

There was logic. There was sequencing. There was, implicitly, a plan.

Today, we are entering a new era of infrastructure development, driven by artificial intelligence, and the pattern looks very different.  As I tell anyone that wants to understand the national challenge we have, I tell them this: We are in a global AI race for dominance: intelligence, technology, capability, all of it is at stake.

This next wave of infrastructure is unfolding at unprecedented speed. Large-scale AI training facilities, sometimes referred to as “AI factories”, are being developed wherever power availability, land access, and investment capital align. That makes sense from a deployment standpoint. But from a national competitiveness perspective, the picture is far less coordinated.

As a former elected official that served two terms in public office in Westchester County, New York, I can tell you that there is no national plan, no vision, nor any understanding of what the nationwide AI architecture ought to be. As a matter of fact, this is being dictated by your local and country jurisdictions who are responsible for making decisions about land use for their jurisdictions.

The result is a patchwork landscape. Some regions are rapidly becoming infrastructure magnets. Others are experiencing moratoria, uncertainty, or stalled projects. Investors are trying to move quickly. Communities are trying to make sense of developments that will shape their economic future for decades. And the rhetoric and sentiment literally shifts community to community – oftentimes polarizing counties themselves.

And, adding another layer of complexity to this is how governance structures operate themselves.  Federal mandates don’t mean much when governors and local jurisdictions can simply say no.

Digital infrastructure decisions ultimately happen at the state, county, and municipal levels. That means the trajectory of national AI readiness is being shaped through thousands of localized decisions, often made without long-term planning frameworks or consistent guidance.

This dynamic creates several emerging risks.

There is the possibility of overbuild in some markets and underinvestment in others. Regional competitiveness may begin to diverge. Businesses that depend on advanced digital infrastructure may feel pressure to relocate toward areas with greater capacity and connectivity. Communities that fail to plan proactively risk being left behind,  not because they chose to reject opportunity, but because they lacked the tools to evaluate it strategically.

We have seen similar cycles before. In earlier phases of telecommunications and broadband expansion, infrastructure was sometimes built ahead of demand. Over time, innovation caught up. Capacity was absorbed. New services emerged. Entire economic ecosystems formed.

AI infrastructure may follow a similar trajectory, but the scale and speed of investment today raise important questions about coordination and long-term vision.

This is one of the motivations behind the work of the Digital Infrastructure Framework Committee (DIFC). Via the OIX Association and the Digital Infrastructure Framework Committee (DIFC), we are  working to create practical guidance that helps communities evaluate digital infrastructure within their broader economic vision, not project by project, crisis by crisis. 

The DIFC thesis is built around this simple concept: What if we created a framework that helps communities master plan digital infrastructure for their 20- or 30-year future?

The intention is not to prescribe where facilities should be built or how individual jurisdictions should regulate development. The goal is simply to tell communities how to do it, and guide them through what to think about for their own future vision community goals. 

Master planning introduces discipline into complex decision environments. It helps communities align infrastructure considerations with economic development goals, land use priorities, sustainability objectives, and workforce planning.

Perhaps most importantly, it introduces continuity. For example, master planning transcends election cycles. It creates continuity so projects are not constantly reset by politics.

As AI continues to reshape industries, supply chains, and public services, the question is not whether digital infrastructure will expand, trust me, it will. The question is whether expansion will be intentional, coordinated, and inclusive enough to support long-term national competitiveness.

History shows that infrastructure built with foresight becomes a foundation for growth.

Infrastructure built without it can create fragmentation.

The opportunity before us is not simply to build faster, but to build smarter. 

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 America Built the Internet with a Plan. We Are Building AI Infrastructure Without One. appeared first on Data Center POST.

The global containerized data center market was valued at USD 16.29 billion in 2025 and is projected to reach USD 114.7 billion by 2035, rising at a CAGR of 22.2% over the forecast period (2026–2035).

Containerized Data Center Industry Demand

Containerized data centers are modular, pre-fabricated data center units (often built inside ISO-style or customized containers) that house IT equipment, power, cooling, and management systems. They are engineered for rapid deployment, standardized manufacturing, portability, and plug-and-play integration with existing infrastructure. These systems can serve as primary facilities for edge and remote applications or as temporary/expandable capacity units for hyperscalers, telecoms, and enterprise customers.

Why demand is rising (core benefits):

• Cost-effectiveness: Lower capital outlay versus constructing brick-and-mortar facilities, reduced civil-construction timelines, and predictable manufacturing costs.
• Speed & ease of deployment: Factory-built units allow rapid rollout (weeks to months), ideal for urgent capacity needs (5G, disaster recovery, temporary events).
• Operational simplicity & modularity: Standardized modules simplify scaling, maintenance, and logistics while enabling consistent performance across sites.
• Long shelf life & resilience: Ruggedized enclosures, standardized cooling and power designs, and simplified transport make containerized units durable and suitable for harsh or remote environments.

Request a sample here.

Containerized Data Center Market: Growth Drivers & Key Restraint

Growth Drivers – 

1. Rapid Edge & 5G Rollouts:
   The push for edge computing and 5G coverage requires distributed, low-latency compute capacity close to users. Containerized modules are ideal for edge sites because they can be rapidly placed at cell towers, substations, or roadside micro-hubs.
2. Need for Fast, Cost-Efficient Capacity Expansion:
   Hyperscalers and enterprises face long lead times for traditional data centers. Containerized units let organizations meet surges in demand, seasonal peaks, or temporary needs without multi-year construction projects.
3. Sustainability & Energy Optimization:
   Many containerized solutions incorporate efficient cooling (liquid/AHU/immersion options), modular power systems, and optimized airflow — making them attractive for organizations focused on PUE improvements and lower operational emissions.

Restraint – 

Although modularity is a strength, highly customized enterprise requirements, regulatory/site permitting, network interconnect constraints, and integration complexity at certain brownfield sites can slow adoption. Additionally, long-haul transport and site-prep costs can reduce near-term ROI in some geographies.

Containerized Data Center Market: Segment Analysis

Segment Analysis by Container Type 

• 20-Foot Containers: Compact and nimble; favored for constrained edge locations and micro-data center use cases. Good for light compute or single-rack deployments, last-mile processing, and temporary/portable applications.
• 40-Foot Containers: Most common for mid-range capacity needs; support multiple racks, integrated cooling, and more robust power options. Popular where a balance of density and transportability is needed.
• Customized Containers: Tailored solutions (e.g., multi-rack immersion cooling enclosures, multi-module systems) designed for specific performance, regulatory, or environmental requirements — often used by hyperscalers, telecom operators, and defense customers.

Demand & Growth: 40-foot and customized modules are typically favored for higher-density or mission-critical deployments, while 20-foot units grow fastest for distributed edge and last-mile applications.

Segment Analysis by Organization Size (SMEs vs Large Enterprises)

• SMEs: Use containerized units to avoid heavy CAPEX, accelerate time-to-market for digital services, and adopt hybrid/edge strategies without investing in large campuses. They prefer smaller, standardized modules and leasing or managed offerings.
• Large Enterprises / Hyperscalers: Leverage containerized modules for rapid capacity expansion, temporary overflow, disaster recovery, and geographically distributed edge estates. They may also specify customized designs and integrate at scale.

By End-Use Industry 

• IT & Telecommunications: Primary adopters for edge and central deployments, especially for 5G and network densification.
• BFSI & Healthcare: Use cases focus on secure, resilient, and compliant processing near operations or in hybrid setups (e.g., backup pods, local analytics).
• Energy & Utilities / Industrial / Military: Favor ruggedized and often customized containerized data centers for remote operations, SCADA analytics, and field deployments.
• Retail & E-commerce / Media & Entertainment: Use pods for CDN, localized compute for personalization and content processing.

Segment Analysis by Ownership Type 

Ownership here refers to solution-driven use cases:

• IoT & Analytics / AI deployments: Drive demand for distributed micro-data centers to process telemetry and run on-site inference.
• AGV / RFID-driven logistics: Containerized compute near warehouses reduces latency for automation and robotics control systems
• Blockchain / Specialized compute: Some customized containers host specialized hardware for cryptographic or ledger workloads, though power and cooling design must be adapted.

Segment Analysis by Application 

• Purchase: Organizations with predictable long-term loads and the ability to manage on-site operations often buy units outright.
• Lease: Attractive for cash-constrained buyers, temporary projects, or test deployments. Leasing vendors lower adoption barriers and accelerate experiments.
• Outsource / Managed: Increasingly popular—third-party providers supply managed containerized capacity (including connectivity, power, and remote operations), ideal for SMEs and enterprises preferring OPEX models.

Segment Analysis by End-Use 

• Greenfield: Rapid roll-out for new campus or regional presence—containerized solutions shorten timelines for greenfield builds.
• Brownfield: Used to augment existing sites where space is limited or to offload capacity for renovation. Integration complexity with legacy systems is a common consideration.
• Upgrade & Consolidation: Organizations consolidate scattered racks into modular pods or use containers as a stepping stone during migration and upgrades.

Containerized Data Center Market: Regional Insights 

North America:
North America leads in adoption due to hyperscaler investments, mature cloud ecosystems, rapid 5G rollout plans, strong edge-compute initiatives, and high demand for rapid capacity expansion. Key drivers include enterprise digital transformation and cloud service expansion.  

Europe:
Europe’s growth is driven by sustainability targets, stringent data-sovereignty rules, and industrial digitization. Regulations and strong demand for energy-efficient designs push adoption of advanced cooling and power management within containerized solutions.

Asia-Pacific (APAC):
APAC shows robust growth due to telecom expansion (5G), rising cloud adoption, government digital initiatives, and rapid urbanization. The need for distributed capacity across vast geographies—plus demand from cloud providers and telcos—fuels investments in containerized data centers. Logistics and local manufacturing capability also support rapid deployment.

Top Players in the Containerized Data Center Market

Hewlett Packard Enterprise (HPE), Dell Technologies Inc., Cisco Systems Inc., IBM Corporation, Schneider Electric SE, Rittal GmbH & Co. KG, Huawei Technologies Co., Ltd., Fujitsu Limited, Vertiv Group Corp., Delta Electronics, Inc., ZTE Corporation, AdaniConneX, AIMS Data Centre, Leading Edge

Access Detailed Report here.

# # #

Contact:

AJ Daniel
Email: info@researchnester.com
U.S. Phone: +1 646 586 9123
U.K. Phone: +44 203 608 5919

The post Containerized Data Center Market Overview 2026 and Forecast till 2035 appeared first on Data Center POST.

Empire Fiber Internet, a leading provider of 100% fiber optic internet across Pennsylvania and New York, announced its expansion into the Lehigh Valley. The rollout targets more than 35,000 homes and businesses with ultra-fast, reliable connectivity. Construction is underway, and residents can sign up now for priority access and neighborhood updates.

“Lehigh Valley residents deserve internet that works as hard as they do,” said Kevin Dickens, CEO of Empire Fiber Internet. “We’re not just expanding our network. We’re giving customers a superior choice with faster speeds, better reliability, and service built for them”.

This expansion is set to accelerate Empire Fiber’s growth in high-demand Pennsylvania markets. The company already serves communities like Scranton-Wilkes Barre, Williamsport, Hazleton, Bloomsburg, and Erie. Lehigh Valley strengthens Empire’s footprint and commitment to closing the digital divide through future-ready infrastructure.

“Continued investment in high-speed internet infrastructure across the Lehigh Valley is a positive step for both our residents and our growing business community,” said Jessica O’Donnell, Executive Vice President of the Lehigh Valley Chamber of Commerce. “Strong, reliable connectivity is essential to economic growth, and efforts like these help ensure our region remains competitive, connected, and positioned for the future”.

In today’s digital economy, fiber expansions like Empire’s meet rising broadband demands. Gigabit connectivity supports remote work, business competitiveness, and community development. Empire’s approach positions the Lehigh Valley for sustained growth. To learn more about Empire Fiber Internet, visit www.empireaccess.com.

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Duos Technologies Group, Inc. (Nasdaq: DUOT), a provider of modular, reported record financial results for Q4 and full year 2025. The company generated $27 million in annual revenue, up more than 270 percent year-over-year. Growth came from services under the Asset Management Agreement with New APR Energy, edge data center hosting, and new Technology Solutions revenue.

Duos successfully deployed 15 Edge Data Center pods in Tier 3 and Tier 4 markets. It also launched a 4.8MW high-density configuration for AI workloads and secured a contract for 2,304 NVIDIA GPUs through its GPU-as-a-Service offering. These steps position the company for strong recurring revenue.

The results reflect Duos’ strategic shift toward data center infrastructure. The company raised $110 million in capital during 2025, ending with $15.47 million in cash and $22.28 million in short-term liquidity. Meanwhile, Duos Technologies Solutions generated $10 million in backlog during its first quarter.

“2025 positioned us at the intersection of AI compute and edge infrastructure,” said CEO Doug Recker. “Our $65 million capital raise and GPU-as-a-Service launch directly address growing power and compute shortages, with demand accelerating from enterprises and hyperscalers”.

Duos is capitalizing on surging AI infrastructure needs through modular edge solutions that deploy faster than traditional builds. The company maintains a $25.8 million backlog and expects 2026 revenue to exceed $50 million.

To learn more about Duos Technologies Group, Inc., visit www.duostechnologies.com. 

The post Duos Technologies Group Reports Record 2025 Results, Driving Momentum in AI and Edge Infrastructure appeared first on Data Center POST.

Sabey Corporation is underscoring its long-standing commitment to veterans with a new national honor: the 2025 Gold HIRE Vets Medallion Award from the U.S. Department of Labor. This recognition places Sabey among a select group of employers whose practices for recruiting, employing, and retaining U.S. military veterans meet the highest federal standards.

Presented under the Honoring Investments in Recruiting and Employing American Military Veterans Act of 2017, the HIRE Vets Medallion Program is the only federal-level award that specifically recognizes employers for their support of veterans in the civilian workforce. Earning Gold status signals that Sabey goes beyond hiring, focusing on creating an environment where veterans can grow, lead, and build meaningful long-term careers.

This recognition reflects Sabey Corporation’s broader vision across its real estate and digital infrastructure portfolio, including Sabey Data Centers, its data center development arm. By intentionally integrating veterans into teams that build and operate mission-critical facilities, Sabey is helping shape a workforce that is both technically strong and grounded in service-driven values. The company emphasizes inclusive hiring practices and strong employee retention efforts as central to its talent strategy.

Sabey’s leadership views veteran employment as a long-term investment in both business performance and community impact. As one of the largest privately owned multi-tenant data center owners, developers, and operators in the United States, Sabey Data Centers relies on operational maturity, reliability, and teamwork. This alignment is helping set a higher benchmark for veteran inclusion in the data center industry and beyond, demonstrating how purpose-driven leadership can strengthen workplace culture while opening new pathways for veterans to thrive.

The post Gold Standard for Service: Sabey Corporation Earns 2025 HIRE Vets Medallion for Advancing Veteran Careers in Digital Infrastructure appeared first on Data Center POST.

Originally posted on Datalec LTD.

Data centre leaders left ExCeL London earlier this month with one message ringing loud and clear: AI‑driven growth is accelerating, power is tight, and the choice of infrastructure partner is now business‑critical, not optional.

Against a backdrop of rapid hyperscale and colocation expansion, constrained power availability and rising energy scrutiny, the conversations at Data Centre World London 2026 underscored that operators need partners who can help them plan power‑first, deploy at speed, and operate reliably in high‑density environments.

For Datalec Precision Installations (DPI), DCW London was an opportunity to demonstrate exactly that kind of integrated, global capability, from modular data centre solutions through to facilities management, consultancy and lifecycle services. The questions operators brought to the stand were remarkably consistent, whether they were building in the UK, expanding in the Middle East, or planning their next phase of growth in APAC.

Below, we revisit three of the most important questions AI‑driven operators were asking in London and why they will matter even more as the industry converges on Singapore for DCW Asia later this year.

1. How quickly can you take me from secured power to live, AI‑ready capacity?

If there was one common theme at DCW London, it was that power availability has become the primary constraint on new data centre builds, not demand. Once operators have secured land and grid, the urgent requirement is simple: how fast can we safely turn that capacity into revenue‑generating, AI‑ready infrastructure?

This is where modular, pre‑engineered solutions dominated the conversation. Many visitors to the DPI stand wanted to understand how modular white space, plant and service corridors could compress design and construction timelines without sacrificing resilience or compliance. DPI’s next‑generation Modular Data Centre Solutions attracted strong interest because they are designed precisely for this challenge. They help clients move from planning to live halls at speed, whether that’s a new campus in a European hub, a hyperscale expansion in the Middle East, or an edge or colocation site in a fast‑growing APAC market.

To continue reading, please click here.

The post Three Questions Every AI‑Driven Operator Should Ask Their Infrastructure Partner appeared first on Data Center POST.

Originally posted on Nomad Futurist.

At DCD>Connect | New York, the Nomad Futurist Foundation didn’t just participate in the conversation about building the future workforce — we demonstrated what it looks like to actively create it.

Through two milestone moments, we brought together today’s leaders and tomorrow’s innovators, proving that meaningful change in the digital infrastructure industry happens when ideas are backed by action.

Mana Hui: Aligning Leaders Around a Shared Mission 

After Day 1 of the conference, we gathered some of the industry’s most forward-thinking voices at the rooftop of The Knickerbocker Hotel for our Mana Hui: Leaders Connect Networking Event.

More than a networking reception, Mana Hui created a dedicated space for leaders to come together around a shared purpose: how we can collectively inspire, educate, and open doors for the next generation of digital infrastructure talent.

Conversations focused on tangible solutions, from increasing visibility into career pathways, to strengthening mentorship opportunities, to ensuring students and early-career professionals understand the real-world impact of this industry. The room was filled with decision-makers, innovators, and advocates aligned around one idea: preparing the future workforce is not a side initiative; it is a responsibility.

Mana Hui set the tone by reinforcing the power of collaboration. When leaders unite with intention, momentum builds, and that momentum must translate into action.

Powering the Next Generation: From Conversation to Impact 

On Day 2, that momentum became measurable impact through our Powering the Next Generation Student Workshop.

Students and emerging professionals joined us for an experience designed not just to inform, but to connect. Industry leaders shared authentic stories about their career journeys, including challenges, pivots, and lessons learned, providing students with transparent insight into opportunities across the digital infrastructure landscape.

Rather than a traditional panel format, the workshop fostered dynamic dialogue. Students actively engaged, asked thoughtful questions, and contributed their own perspectives, creating an environment rooted in collaboration and curiosity.

A defining highlight came when a group of students from New York University presented a live demonstration of one of their own projects, offering a powerful reminder that the next generation is not waiting for opportunity. They are already building the future.

We were proud to welcome students representing an exceptional range of institutions, including Harvard Law School, Columbia University, Cornell University, Dartmouth College, University of Notre Dame, Stevens Institute of Technology, and more. Many of these students are preparing to enter the workforce within months and are eager to contribute meaningfully to the industry.

Following the workshop, members of the Nomad leadership team continued the experience with a visit to the iconic 60 Hudson Street building for a tour of the NYI and Hudson Interxchange facilities, led by Ambassador Arthur Valhuerdi. For even some of our own members, it was their first time inside a live data center environment, making it a meaningful extension of the day’s learning and a powerful reminder of the infrastructure behind the digital world.

To continue reading, please click here.

The post Turning Conversation into Action: Nomad Futurist Foundation at DCD>Connect | New York appeared first on Data Center POST.

In a strategic move underscoring the shift toward modular infrastructure, Compu Dynamics Modular (CDM), a Chantilly, Virginia-based specialist in prefabricated data center solutions, has acquired a majority stake in R&D Specialties, an Odessa, Texas, manufacturer of UL-certified control panels and modular electrical systems. Announced today, the deal expands CDM’s manufacturing footprint to 120,000 square feet, with room for growth on a 15-acre campus, positioning the company to meet skyrocketing demand for AI-ready, high-density deployments from hyperscalers, colocation providers, and enterprises.

This acquisition arrives at a pivotal moment. AI and high-performance computing (HPC) workloads demand unprecedented speed, density, and scalability – challenges traditional builds struggle to match. Modular solutions, once niche, are now the default for rapid, repeatable deployments.

“Modular infrastructure is where efficiency meets innovation,” said Ron Mann, vice president of CDM. “For decades, we’ve delivered solutions that solve real engineering challenges in high-stakes environments. Joining forces with R&D Specialties allows us to bring that expertise to the next generation of AI data centers at scale.”

Steve Altizer, president and CEO of Compu Dynamics, emphasized the market imperative: “This investment is about building the capabilities and capacity the market is demanding right now. AI infrastructure requires a different approach; one that delivers faster, scales smarter, and performs better. R&D Specialties brings the engineering depth and manufacturing precision that align perfectly with where this industry is headed.”

R&D Specialties, founded in 1983, excels in custom-engineered systems for mission-critical settings, complementing CDM’s vendor-neutral, end-to-end services – from design and liquid-cooled IT platforms to commissioning and maintenance. Brad Howell, president of R&D Specialties, noted the synergy: “Through joining forces with CDM, our growth opportunities for the combined teams have expanded even further. Being part of the AI infrastructure revolution and building what’s next is exciting.”

For data center operators, this signals broader ecosystem maturation. CDM’s turnkey modules accelerate time to market while integrating high-density power, low-latency networking, and sustainability features. With an extensive North American partner network, the combined entity can deploy campus-scale solutions anywhere, anytime – critical as AI power needs strain grids and supply chains.

This deal exemplifies how strategic M&A is fueling modular dominance, helping the industry navigate AI’s compute explosion with agility and reliability. Learn more at cd-modular.com.

The post CDM Acquires Majority Stake in R&D Specialties to Power AI Modular Data Center Surge appeared first on Data Center POST.

Artificial intelligence is a tool designed to power innovation, but it’s important to understand its primary fuel: data. Data is required not only for the outputs of AI algorithms but also for their training and operation. Because of this, in sectors where innovation has become driven by technologies like artificial intelligence, data has essentially become fuel for innovation, and it’s important to ensure the safety and quality of this data to stimulate it.

Understandably, many critics have expressed concern over the use of artificial intelligence in healthcare settings, considering the private, sensitive nature of the data used in the field. Patient personal information is not only highly sensitive but also protected by law, meaning there are strict regulations and guidelines dictating how entities in healthcare can use artificial intelligence with regard to patient data.

Why strong data governance is essential for AI in healthcare

However, that doesn’t mean artificial intelligence shouldn’t be used in healthcare whatsoever. Instead, it means there is a need for strong data governance, as this is an essential step in enabling safe and ethical AI use in any industry, particularly ones such as healthcare where the stakes are high. In addition to ensuring compliance with any applicable regulations, strong data governance helps create greater transparency and trust that inspires patient confidence.

It’s important to remember the reason why the healthcare sector wants to deploy artificial intelligence technology in the first place: AI can accelerate innovation and lead to improved patient outcomes. For example, innovators in the healthcare industry have used AI to accelerate drug discovery, conduct more accurate diagnostics, and streamline operations in a way that significantly improves efficiency. But to achieve these outcomes, systems must have access to accurate, well-managed data.

The key to this is creating compliance frameworks that reduce and mitigate the risks of artificial intelligence while still supporting scalable healthcare solutions. Of course, the core of any compliance framework in healthcare is data security and privacy, but these guidelines can also help control other risks, such as algorithmic bias and “black box” risks, ensuring that all decisions and recommendations made by an artificial intelligence are fair and explainable.

Enabling the responsible deployment of AI in healthcare

Ultimately, data governance isn’t about gatekeeping but about collaboration and enabling the responsible and ethical deployment of artificial intelligence. The mindset with which we approach AI shouldn’t be about limiting how we can use the technology, but instead how we can facilitate its use in a way that does not compromise data integrity or patient privacy.

Right now, the key goal of healthcare practitioners who hope to implement artificial intelligence should be to build trust and reliability in these systems. The steps required to achieve this include ensuring data quality and diversity, maintaining transparent communication, and continuous monitoring and validation.

The best way to look at AI systems in healthcare is as an analog to human employees. In healthcare, not even human employees have unfettered access to patient data. There are access controls based on the level of access an individual needs, with checks and balances and supervisory control.

The same philosophy should apply to autonomous systems. Just as approvals and access controls are required of human employees, so too should AI systems require approvals from human overseers.

Indeed, there is a world in which artificial intelligence can revolutionize the healthcare industry for the better, alleviating some of the burden on healthcare workers and contributing to improved patient outcomes. However, for this to happen, the adoption of AI must be done in a way that is responsible and ethical. With this mindset, prioritizing strong data governance, AI can become a reliable partner in patient care.

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About the Author

Chris Hutchins serves as the founder and CEO of Hutchins Data Strategy Consulting. The healthcare institutions benefit from his expertise in developing scalable moral data and artificial intelligence methods to maximize their data potential. His areas of expertise include enterprise data governance, responsible AI adoption, and self-service analytics. His expertise helps organizations achieve substantial results through technology implementation. Through team empowerment, Chris assists healthcare leaders in enhancing care delivery while reducing administrative work and transforming data into meaningful outcomes.

The post Data Governance and Clinical Innovation appeared first on Data Center POST.

ZincFive^®, a leader in nickel-zinc (NiZn) battery-based solutions for immediate power applications, has once again been recognized by TIME, earning a place on the America’s Top GreenTech Companies 2026 list for the third consecutive year. Developed in partnership with Statista, the ranking evaluates companies based on environmental impact, financial strength, and innovation, placing ZincFive among a select group shaping the future of sustainable technology.

This year, the company ranked #142 out of more than 3,500 evaluated organizations and is one of only two companies headquartered in Oregon to be included on the list.

The recognition reflects continued momentum for ZincFive’s nickel zinc battery technology, which has gained traction as an alternative to traditional energy storage options in mission critical environments. As data centers evolve to support artificial intelligence and increasingly dynamic workloads, the need for power solutions that can deliver both performance and safety has become more pronounced.

ZincFive’s approach centers on immediate power, delivering high power density in a compact footprint while avoiding the risks associated with other battery chemistries. Nickel zinc batteries are designed to provide reliable performance without thermal runaway concerns and rely on more abundant, recyclable materials, supporting both operational and environmental goals.

For ZincFive, continued recognition from TIME signals more than a milestone. It reflects a broader shift in how the industry is evaluating power infrastructure, with greater emphasis on safety, sustainability, and long term performance.

“Earning a place on TIME’s America’s Top GreenTech Companies list for the third consecutive year reflects the growing role of nickel-zinc technology in delivering safe, sustainable power,” said Tod Higinbotham, CEO of ZincFive. He emphasized the company’s “power of good chemistry” approach to balance performance, safety, and eco-friendliness.​

The company’s inclusion builds on a series of recent awards recognizing its innovation in energy storage, particularly in applications where reliability is critical. As demand for resilient and efficient power continues to grow, ZincFive’s technology is increasingly positioned to support the next generation of digital infrastructure.

For full details, read the press release here.

The post ZincFive Earns TIME GreenTech Recognition for Third Straight Year appeared first on Data Center POST.

Walk through the sales deck of almost any data center operator and you’ll find the same language: Tier III certified, N+1 redundancy, 99.999% uptime. The terminology is standardized because the underlying assumption is standardized that infrastructure is, at its core, a commodity.

That assumption is worth examining more carefully. Because what looks identical on paper can behave very differently under pressure. And the gap between a standard data center and a strategic one isn’t visible in a specification sheet. It shows up in an outage.

Engineering for Reality, Not for Ideal Conditions

MedOne, Israel’s largest data center operator with more than 25 years of experience building and managing critical infrastructure,serves some of the country’s most demanding clients , banks, healthcare providers, government agencies, defense-adjacent technology firms and large-scale enterprise platforms. These are mission-critical environments where downtime carries legal, financial and operational consequences that go well beyond a service credit. When a payment system goes dark or a hospital’s records platform becomes unavailable, the impact is measured in far more than lost revenue.

Building for that client base forced a different set of engineering questions from the start. Not “how do we achieve uptime under normal conditions?” but “how do we maintain continuity when normal conditions no longer exist?” That shift in the design brief changes almost every decision that follows.

MedOne’s facilities are built underground , not as a differentiating feature, but as a structural response to the requirement for physical isolation. Underground construction reduces exposure to environmental variables, provides stable ambient temperatures for cooling efficiency and removes a layer of external dependency that surface-level facilities carry by default. For mission-critical clients operating under strict regulatory and continuity requirements, physical hardening is not optional; it’s a baseline expectation.

Redundancy vs. Independence: A Difference That Matters

Most data centers are built around redundancy. Redundant power feeds, redundant cooling circuits, redundant network paths. Redundancy is valuable  but it operates on a specific assumption: that external systems are available, and that a backup path exists when the primary one fails.

Independence operates on a different assumption entirely: that external systems may not be available at all, and that the facility must be capable of sustaining itself regardless.

MedOne’s facilities are designed to operate independently for up to 72 hours without relying on external power or water infrastructure. This means on-site fuel reserves, independent power generation and self-sufficient cooling systems, the entire physical stack, sustained without input from the national grid or municipal utilities.

“Redundancy still assumes external systems are available somewhere in the chain,” says Eli Matara, chief commercial officer at MedOne. “Independence means we can continue operating even when they aren’t. For mission-critical clients -that’s not a philosophical difference. It’s the difference between staying operational and explaining an outage.”

The engineering logic becomes clearer when you think in layers. Modern infrastructure is a dependency chain: power feeds cooling, cooling enables compute, compute supports network, network delivers applications. Each layer inherits the risk of the layer beneath it. Redundant components within a single layer don’t eliminate risk if those components share an upstream dependency, a common substation, a shared conduit, or a single utility provider. Standard infrastructure is designed to recover when a layer fails. Strategic infrastructure is designed so that failure of an external input doesn’t cascade through the layers above it in the first place.

Connectivity Is Infrastructure, Not a Feature

For mission-critical clients, a facility that is running but unreachable is still down. That’s why MedOne treats connectivity not as a managed service sitting above the infrastructure layer, but as a core part of the architecture itself.

MedOne operates as one of Israel’s primary carrier-neutral interconnection hubs. Carrier neutrality means that multiple competing telecommunications providers, global carriers, regional operators and local fiber networks  all terminate directly inside MedOne’s facilities. Clients are not locked into a single provider and can choose, combine or change carriers without physical migration or dependency on a single network operator. In a region where geopolitical conditions can affect routing availability, that freedom is not a commercial convenience, it’s a risk management tool.

The connectivity architecture extends to direct cloud on-ramps, submarine cable landing stations and Israel’s core fiber backbone  all designed to avoid the hidden convergence points where redundant-looking network paths physically meet and paper diversity collapses into a single point of failure.

“A data center that’s operational but unreachable is still down from a customer’s perspective,” Matara says. “Path diversity and true interconnection aren’t add-ons. They’re part of the same design logic as power and cooling independence.”

Starting With Infrastructure, Not With Cloud

The prevailing assumption in enterprise infrastructure planning has been that cloud resilience is sufficient  that hyperscaler uptime guarantees translate into genuine continuity. MedOne’s model challenges that directly. With more than 15 years of experience supporting high-performance computing environments, the company brings a depth of technical understanding that extends well beyond standard enterprise workloads  and that shapes how it thinks about the relationship between physical infrastructure and the services built on top of it.

Cloud services are only as resilient as the physical infrastructure they run on. Starting with hardened, sovereign, physically isolated infrastructure — and building cloud and managed services on top of it  produces a fundamentally more resilient architecture than layering cloud on top of a standard facility and relying on the SLA to cover the gaps.

For mission-critical clients in regulated industries, this distinction carries additional weight. Data sovereignty, regulatory compliance and audit requirements often demand infrastructure that can be physically verified, locally governed and operationally isolated; a carrier-neutral, underground, autonomy-designed facility answers those requirements in a way that a hyperscaler availability zone cannot.

Meeting Sovereign and Regulatory Standards

For banks, insurers and payment providers in Israel, enforceable data sovereignty is now a hard regulatory expectation, not marketing language. MedOne’s underground, carrier-neutral facilities are designed to support Israeli privacy and data-security requirements, including strict controls over physical access, operations and data flows that enable financial institutions to demonstrate compliance and satisfy supervisory scrutiny.

The Real Test

Infrastructure decisions made under stable conditions tend to look similar. The divergence happens when conditions change.

Israel’s ongoing conflict with Iran brought missile alerts, physical security responses and disruptions to civilian utilities  creating operating conditions where continuity could not be assumed and where the difference between facilities designed for stability and those designed for disruption became impossible to ignore. MedOne’s facilities continued operating throughout. Not because the engineering was lucky, but because the architecture was designed from the ground up for exactly that scenario: external disruption as a baseline assumption, not an edge case.

That is the core argument for the strategic model. Resilience built into the architecture from the start performs differently than resilience added as a layer on top of a standard design. For organizations that cannot afford to find out which kind they have at the worst possible moment, the engineering choices made before a facility is ever switched on are the ones that matter most.

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About the Author

Eli Matara is Chief Commercial Officer at MedOne, Israel’s leading provider of underground, carrier-neutral data centers and a central connectivity hub linking Israel to global networks.

With more than 20 years in enterprise sales, Eli leads the company’s commercial strategy across colocation, cloud, and connectivity. He works closely with Israel’s largest enterprises, global S&P 500 companies, and mission-critical organizations, helping them secure long-term infrastructure partnerships built for resilience, scale, and AI-driven workloads.

The post Not All Data Centers Are Built the Same — Inside MedOne’s Infrastructure Strategy in Israel appeared first on Data Center POST.

In my last article, I wrote about the need for calm, evidence-based leadership in an increasingly polarized infrastructure environment. One of the realities that continues to surface in communities across the country is that what we often interpret as resistance to development is something more nuanced. In many cases, communities are not pushing back out of ideology, they are responding to complexity, uncertainty, and the absence of trusted frameworks to guide long-term decisions.

Across the United States, digital infrastructure projects, namely data center developments, are encountering growing community resistance.

Too often, this pushback is quickly labeled as anti-growth sentiment, environmental activism, or resistance to technology. But in many cases, that interpretation misses the deeper reality.

What is often labeled as opposition is actually overwhelm.

Communities are being asked to make decisions about infrastructure that will shape their economic future for decades; without the tools, context, or trusted guidance to evaluate those decisions confidently.

Digital infrastructure, particularly large-scale or hyperscale data centers and supporting connectivity systems represents a new class of development. These projects intersect simultaneously with power infrastructure, water resources, land use planning, tax policy, and even national competitiveness. That level of complexity is unprecedented for many local decision-makers.

As a former elected official in Westchester County, New York, and after serving two-terms I know for a fact that most elected officials did not run for office to evaluate hyperscale infrastructure proposals. They ran to address zoning disputes, improve roads, manage school budgets, and respond to everyday civic concerns. When faced with proposals involving megawatt-scale energy demand, unfamiliar technical terminology, global technology narratives, and uncertain long-term impacts, decision paralysis is a natural outcome.

In that environment, saying “no” can feel like the safest and most responsible choice. And for me, this is the crux of the matter. If elected officials don’t know what they are saying no to, it could have dire consequences on the future of their communities – and country.

Further fueling this sentiment are the political dynamics across our country. Local leaders operate within short election cycles and highly visible public scrutiny. Approving a controversial project can feel like a personal political gamble,  particularly when the information landscape is polarized and the benefits are difficult to quantify in near-term terms. And, let’s be honest, you have to live with your neighbors and their emotional reactions to things they too don’t understand.

Trust gaps also play a role. Communities observe large incentive packages (community benefit plans), opaque project branding (project names rather than company brands), and rapid land acquisitions that may span 100’s of acres or more. This can create perceptions of imbalance:  imbalance of information, imbalance of power, and imbalance of benefit. Even when development intentions are positive, the process can feel accelerated and asymmetric from the community’s perspective.

There is also a fear of irreversibility. Digital infrastructure is often perceived as permanent, transformative, and difficult to unwind once built. And fears from past industrial builds like aluminum smelters and energy production sites have not laid an easy path for large-scale developments in our country’s future. That perception alone can drive precautionary decisions, calls for moratoria, and emotional public hearings.

From the industry side, resistance is sometimes misread as anti-technology bias or organized opposition. But frequently the underlying issue is not ideology, it is cognitive and institutional readiness. Communities are not rejecting opportunity; they are struggling to evaluate it.

This is where structured engagement models become essential.

At my company, iMiller Public Relations, we approach these efforts through an effort I call The Groundswell™ approach. The Groundswell approach reframes community engagement from persuasion to empowerment. It begins with understanding local decision dynamics; who influences outcomes, what matters most to residents, and how technical issues translate into civic implications. It emphasizes early education before formal approvals, surfaces community benefit opportunities, and builds coalition narratives that reduce fear rather than inflame it.

Informed communities make more confident decisions. They are better positioned to align development with their long-term economic vision rather than reacting project by project.

When overwhelm occurs simultaneously across multiple regions, the implications extend beyond any single development. Infrastructure deployment becomes fragmented. Investor confidence can weaken. Regional competitiveness begins to diverge. National digital readiness ultimately suffers.

Community overwhelm, therefore, is not just a local planning challenge, it is a strategic issue.

Resistance is often the first signal that institutions need new tools, governance frameworks require modernization, and engagement models must evolve. Calm, structured dialogue is not simply good community relations. It is foundational to building the next generation of digital infrastructure in a way that is both sustainable and broadly supported.

The work I am leading at the OIX Association and the Digital Infrastructure Framework Committee (DIFC), is working to create practical guidance that helps communities evaluate digital infrastructure within their broader economic vision, not project by project, crisis by crisis.

Understanding this distinction may be one of the most important steps we can take right now.

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 Community Resistance Is Often Overwhelm – Not Opposition appeared first on Data Center POST.

Originally published in the Idaho Statesman.

America’s most pressing ambitions — re-industrialization, artificial intelligence leadership, cleaner energy and thriving small businesses — are colliding with a hard reality: The nation lacks the power and energy grid infrastructure required to deliver them.

To compound the issue, local communities often oppose new data centers because, among other reasons, consumers fear that their own energy bills may rise. Nevertheless, by supporting new technologies, including a new generation of small modular reactors, or SMRs, policymakers can address America’s power needs in ways that benefit consumers.

During his State of the Union address, President Trump announced a “new Rate Payer Protection Pledge” to ensure that the tech companies, rather than consumers, bear the costs of new data centers. The pledge builds on an earlier bipartisan plan that encourages technology companies to build their own power plants. Google, Meta, Microsoft, xAI, Oracle, OpenAI, and Amazon signed the pledge in early March to “BYOP” — Bring Your Own Power — to the data center party.

As part of a comprehensive energy strategy, SMRs offer a practical path to expanding power capacity, pairing reliable power with comfortable safety margins. SMRs are compact, standardized nuclear plants built with factory-produced components that reduce construction time, lower costs and improve safety compared with traditional large- scale reactors. Unlike conventional nuclear plants that require massive, decade-long construction projects, SMRs can be prefabricated and deployed incrementally, making them ideally suited to today’s energy, AI and grid demands.

Idaho’s Role in SMR Development

SMRs’ potential provides another reason to watch the Idaho National Laboratory and its National Reactor Innovation Center. Last May, the White House issued four executive orders that significantly expanded the Department of Energy’s authority to regulate new advanced reactors and could encompass a prototype reactor for powering a data center.

One of these Orders directs DOE to approve at least three new reactors. DOE subsequently accepted 11 applicants into its reactor pilot program.

In fact, the need for data centers to provide their own power is a problem tailor-made for the NRIC, whose mission is to “bridge the gap between concept, demonstration, and commercialization of advanced nuclear technology.” NRIC recently announced its Nuclear Energy Launch Pad in response to this high private sector interest. The Launch Pad initiative is the new vehicle to test and operate these trailblazing technologies in partnership with private nuclear technology developers, with an eye toward eventual commercial deployment and proof of DOE’s plans to expand the private sector’s ability to obtain DOE Authorization.

In conjunction with the Launch Pad, the Department of Energy and the Nuclear Regulatory Commission should continue to pursue regulatory reforms that could significantly speed the growth of all nuclear power, including SMRs. One of the recent executive orders directed the Nuclear Regulatory Commission to modernize its regulations. Proposed revised regulations, which should prioritize safety, speed, and cost, are expected soon.

To continue reading, please click here.

The post These Nuclear Reactors Can Benefit Idaho, Power America’s Ambitions appeared first on Data Center POST.

Duos Technologies Group, Inc. (Nasdaq: DUOT), a provider of modular, colocation Edge and AI data centers and technology infrastructure solutions, has scheduled its fourth quarter and full year 2025 earnings call for Tuesday, March 31, 2026 at 4:30 p.m. Eastern Time.

Based in Jacksonville, Florida, Duos Technologies Group is focused on modular data center colocation facilities and infrastructure solutions through its Duos Edge AI and Duos Technology Solutions subsidiaries. The company continues to expand its digital infrastructure platform to support AI, enterprise computing, and edge deployments across Tier 3 and Tier 4 markets.

During the call, Duos management will discuss financial results for the quarter and full year ended December 31, 2025, followed by a question-and-answer session. The company said it will release its financial results prior to the call through the Investor Relations section of its website.

A live audio webcast will also be available online, with a replay posted after the event. Investors joining by phone can use the U.S. dial-in number +1 877 407 3088 and confirmation number 13759531, while international participants can access the call through the company’s dial-in matrix.

To learn more about Duos Technologies Group, Inc., visit www.duostechnologies.com.

The post Duos Technologies Group Schedules March 31 Call to Review Fourth Quarter and Full Year 2025 Results appeared first on Data Center POST.

Originally posted on Nomad Futurist.

Happy International Data Center Day! Today, we shine a spotlight on an industry that quietly powers our modern world. Behind every video call, online class, cloud application, and AI breakthrough is a network of infrastructure that most people never see — but rely on every single day: the data center industry.

This day is about more than celebrating technology; it’s about celebrating the people who make it all possible. From engineers and technicians to sustainability leaders, network specialists, and innovators, data centers are driven by talented professionals shaping the future of technology and connectivity.

Yet, one of the biggest challenges remains awareness. Many students and educators still don’t know that these careers exist, or the incredible opportunities they offer.

At the Nomad Futurist Foundation, we know that exposure changes everything. When students step inside a data center, meet the people behind the operations, and see the technology up close, curiosity transforms into possibility. Experiencing these environments firsthand opens doors to careers that are not only in high demand but essential to powering our digital future.

To continue reading, please click here.

The post Celebrating International Data Center Day: Inspiring the Next Generation of Tech Leaders appeared first on Data Center POST.

The AI revolution is pushing the data center industry toward gigawatt-scale campuses. But the real question today is not how large a facility can be built. The real question is how quickly power can be converted into revenue.

Consider a 1 gigawatt data center project. One gigawatt equals one thousand megawatts of capacity. In today’s market, typical infrastructure costs for large data centers range between 8 million and 12 million dollars per megawatt for standard facilities. That places the infrastructure cost of a 1 GW campus between 8 billion and 12 billion dollars.

In many U.S. markets, developers are seeing costs closer to 10 to 14 million dollars per megawatt, which would place a 1 GW campus between 10 and 14 billion dollars. AI optimized data centers can be even more expensive due to high density racks, liquid cooling systems, and larger electrical infrastructure. Those facilities can reach 15 to 20 million dollars per megawatt, pushing a 1 GW campus to 15 to 20 billion dollars in infrastructure alone.

Once servers, GPUs, networking equipment, and storage are installed, the total project value can easily exceed 30 billion dollars. But capital cost is no longer the biggest constraint, energy is.

According to the International Energy Agency, global data center electricity consumption reached roughly 415 terawatt hours in 2024, representing about 1.5 percent of global electricity demand. That number is projected to approach 800 terawatt hours by 2030 as AI adoption accelerates. At the same time, power infrastructure is struggling to keep up. The United States interconnection queue alone now exceeds 2 terawatts of generation capacity waiting for approval, and in many regions new grid connections can take three to six years. This creates a major financial challenge for traditional hyperscale development.

Large buildings are often constructed years before sufficient power becomes available. Hundreds of megawatts of capacity can sit idle while developers wait for substations, transmission lines, and utility upgrades. On a one gigawatt campus that could mean billions of dollars tied up in infrastructure waiting for power.

Now compare that with a modular campus strategy.

Instead of constructing massive buildings designed for the full gigawatt from day one, the campus can be deployed incrementally as power becomes available. A one gigawatt campus could begin with a 20 megawatt deployment. Using the same industry pricing ranges, that first deployment would require between 160 and 240 million dollars at eight to twelve million dollars per megawatt, or up to 300 to 400 million dollars if the facility is designed for high density AI workloads. What makes this model powerful is how quickly revenue can begin.

In many markets AI capacity is leasing between 150 thousand and 250 thousand dollars per megawatt per month depending on location and density. A 20 megawatt deployment can therefore generate roughly 3 to 5 million dollars per month, or approximately 36 to 60 million dollars per year, while the rest of the campus continues expanding. Instead of waiting years for a massive hyperscale facility to be completed, the project can begin generating revenue within 12 to 18 months.

As additional power becomes available the campus grows from twenty megawatts to one hundred megawatts, then several hundred megawatts, and eventually the full one gigawatt capacity. By the time the campus reaches full scale, the project may already be generating hundreds of millions of dollars annually.

There is also another strategic advantage that is becoming increasingly important: mobility of infrastructure.

If power availability changes, new energy sources come online, or grid constraints shift to another region, modular facilities can be redeployed where energy exists. Massive fixed hyperscale buildings cannot move.

This dramatically changes the risk profile.

Traditional hyperscale development concentrates 10 to 20 billion dollars into a single permanent structure. Modular campuses distribute capital across infrastructure that scales directly with available power.

In a world where energy has become the limiting factor for digital growth, the future of hyperscale development may not be one giant building. It may be gigawatt scale campuses built from modular infrastructure designed to grow with power.

# # #

About the Author

Kliton Agolli Co-Founder, Board Member & Director of Global Growth Northstar Technologies Group | Naples, Florida.

Kliton Agolli is a senior security and international business development executive with more than 35 years of experience operating at the intersection of national security, executive protection, counterintelligence, and global commercial expansion. His career spans military service, law enforcement, VIP and diplomatic protection, healthcare and hospitality security, and cross-border business development in complex and high-risk environments.

At Northstar Technologies Group, Mr. Agolli leads global growth strategy, international partnerships, and strategic market expansion. He plays a key role in aligning advanced security and infrastructure technologies with government, defense, healthcare, and mission-critical commercial clients worldwide. His work focuses on risk-informed growth, regulatory compliance, and building long-term strategic alliances across Europe, the Middle East, and the United States.

The post The 1 Gigawatt Data Center Dilemma appeared first on Data Center POST.

Originally posted on Compu Dynamics.

Discover how AI is transforming mission‑critical infrastructure: From modular data center design and liquid cooling to extreme power density to purpose‑built AI facilities, Steve Altizer, President and CEO of Compu Dynamics, covers these topics in this recent conversation.

At PTC 2026 in Hawaii, Isabel Paradis of HOT TELECOM held a discussion with Altizer to discuss how AI is reshaping the way modular data centers are designed now and in the future.

AI Is Rewriting the Rules of Data Center Design

AI is transforming data centers. While many are still trying to shoehorn AI workloads into traditional designs, that approach is only going to last a few more years. Hyperscalers are leading the way into an AI‑centric future, where liquid cooling – once a specialty – is now becoming standard across the industry.

Retrofitting conventional colo or cloud facilities for AI is not ideal. It’s not as cost effective as doing something that’s purpose built, yet building AI‑only facilities also carries risk, because repurposing that heavy investment later is difficult. The industry is therefore moving toward modular infrastructure, which allows for hybrid, purpose‑built AI facilities that remain flexible enough to serve a range of customers.

To continue reading, please click here.

The post Purpose-Built for AI: The Shift Toward Modular Data Center Infrastructure appeared first on Data Center POST.

By Mike Hodge, AI Solutions Lead, Keysight Technologies

It’s the heart of the AI gold rush, and everyone wants to capitalize on the next big thing. Large language models, multimodal systems, and domain-specific AI workloads are moving from experimentation to production at scale. Across industries, enterprises are building their own proprietary models or integrating pre-trained ones to power applications spanning from video analytics to highly specialized inference services.

This shift has triggered a new wave of infrastructure investment. But while GPUs and accelerators dominate the conversation, scaling AI platforms has produced a less obvious constraint: front-end network performance. In increasingly distributed, multi-tenant AI environments, the ability to move data efficiently into (and across) platforms has become just as critical as raw compute density.

New AI platforms mean new expectations for infrastructure

AI infrastructure is no longer the exclusive domain of a handful of hyperscalers. A growing class of service providers has begun offering end-to-end AI platforms where compute, storage, networking, and orchestration are delivered as a service. Their value proposition is straightforward: customers bring data and models, while the platform handles the complexity of building, operating, and maintaining large-scale data center deployments.

Service models like these, however, place extraordinary demands on networking. Unlike traditional cloud workloads, AI jobs are defined by massive, sustained data movement and tight coupling between data pipelines and compute utilization. GPUs cannot perform at peak efficiency unless data arrives on time, in the right order, and at predictable speeds.

As a result, network performance is now one of the primary determinants of training, inference, and infrastructure efficiency.

The eye of the storm is moving from the fabric to the front end

AI infrastructure discussions often focus on back-end fabrics. Think about things like high-bandwidth, low-latency interconnects between GPUs, for example. However, while these fabrics are indeed essential, they are only part of the picture.

Before training or inference ever begins, data must first traverse the front-end network. This occurs in several ways, but some of the most common paths include:

• From remote object stores or on-premises repositories into the data center
• From ingress points into virtual machines or containers
• From storage into GPU-attached hosts

This is where north-south traffic (external to internal) intersects with east-west traffic (host-to-host and service-to-service). And in AI environments, these flows are not occasional spikes. They are sustained, high-throughput, latency-sensitive streams that run continuously throughout the lifecycle of a job.

When front-end networks underperform, the consequences are costly and immediate: idle accelerators, elongated training windows, unpredictable inference latency, and poor multi-tenant isolation.

Why traditional network validation falls short

Most cloud networks were designed around general-purpose workloads. Think about things like web services, databases, and transactional systems with relatively modest bandwidth demands and fluctuating traffic patterns punctuated by the occasional spike.

AI workloads, on the other hand, break these assumptions. On the front end, AI traffic is characterized by:

• Extremely large data transfers, often using jumbo frames
• Long-lived connections, sustained over hours or days
• Millions of concurrent sessions in multi-tenant environments
• Tight latency and jitter tolerances to avoid starving accelerators

Conventional network testing approaches — such as synthetic benchmarks, isolated link tests, or small-scale simulations — are unable to replicate this behavior. As a result, many issues only surface once customer workloads are already running, which also happens to be when the cost of remediation is highest.

The need for realistic workload emulation

Optimizing front-end AI networks requires the ability to reproduce real workload behavior at scale. That means emulating both north-south and east-west traffic patterns simultaneously, across distributed environments and under sustained load.

For north-south paths, this includes verifying that large datasets can be reliably pulled from diverse external sources into local storage. Moreover, the network must also be able to do so with consistent throughput, predictable latency, and no silent data loss. Transfers like these are essential, as any inefficiency propagates directly into longer training times and underutilized GPUs.

For east-west paths, the challenge shifts to connection density, latency, and scalability. Once workloads are running, virtual machines and services exchange data continuously. Sometimes within the same host, sometimes across racks, and sometimes across geographically separated data centers. Modern AI platforms increasingly rely on SmartNICs and offload technologies to make this feasible, so these components must also be validated under realistic connection rates and protocol behavior.

Without large-scale, workload-accurate testing, subtle bottlenecks — such as rule-processing limits, connection-tracking inefficiencies, or unexpected latency spikes — can remain hidden until production traffic exposes them.

Front-end optimization is a competitive differentiator

In response, the most advanced AI platform operators are shifting left: validating their front-end networks before customers ever deploy workloads. Along the way, their proactive approach is changing the economics of AI infrastructure.

Stress-testing networks under real-world conditions offers a range of benefits for network operators:

• Identifying performance cliffs at high line rates
• Understanding how different layers of the stack interact under load
• Resolving scaling limitations in NICs, virtual networking, or storage paths
• Delivering predictable performance across tenants and geographies

It’s not just about improving peak throughput. It’s about building confidence that platforms perform as expected under peak pressure. And in a market where AI workloads are expensive, time-sensitive, and strategically important, this confidence becomes a differentiator. Customers may never see the network directly, but they feel its impact in faster training cycles, lower inference latency, and fewer production surprises.

Looking ahead: front-end networks and the next generation of AI

AI workloads continue to evolve. Microservices-based architectures, distributed inference pipelines, and increasingly stateful services are placing even more emphasis on low-latency, high-availability front-end connectivity. At the same time, data is becoming more geographically distributed, pushing platforms to span multiple regions and network domains.

In this environment, front-end networks are no longer a supporting actor. They are a core component of AI system design. That means they must be engineered, validated, and optimized with the same rigor applied to compute and accelerators.

The lesson is clear: operators cannot optimize AI infrastructure by focusing on GPUs alone. The performance, efficiency, and reliability of tomorrow’s AI platforms will be defined just as much by how well they move data as by how fast they process it.

The post AI’s Overlooked Bottleneck: Why Front-End Networks Are Crucial to AI Data Center Performance appeared first on Data Center POST.

Capacity LATAM 2026, held March 17-18 in São Paulo, Brazil, made it clear that Latin America’s digital infrastructure market is no longer defined by potential, but by execution. As demand for cloud, AI, and connectivity accelerates across the region, the conversation has shifted from future opportunity to immediate deployment where power, capital, and collaboration must align to keep pace with growth.

Across the event, the narrative moved well beyond subsea routes and international traffic flows. Instead, speakers focused on how Latin America is becoming a destination for data creation, processing, and storage. With the region’s data center market projected to nearly double by 2030, investment is accelerating across Brazil, Mexico, Chile, and Colombia, while emerging markets are beginning to play a more strategic role in regional infrastructure planning.

Collaboration emerged as a central theme, particularly as infrastructure deployments become more complex and capital-intensive. During the “From Fiber to Facility” keynote, Gabriel del Campo, Data Center Vice President at Cirion Technologies emphasized that scaling data centers and networks across Latin America requires tighter alignment between operators, fiber providers, and hyperscalers. That coordination is increasingly necessary to navigate supply chain challenges and accelerate time to market in a region where demand is rising quickly.

Investment momentum continues to build, with the “LATAM’s $100B Digital Surge” keynote framing the scale of capital entering the market. Rodolfo Macarrein, Partner at Altman Solon highlighted how shifting political and regulatory dynamics are influencing where and how capital is deployed while reinforcing that long-term demand fundamentals remain strong. Key markets such as São Paulo, Santiago, and Querétaro are emerging as focal points for AI-ready capacity, driven by hyperscale expansion and enterprise demand.

AI infrastructure is already beginning to shape the next phase of development. In the AI keynote, Ivo Ivanov, CEO at DE-CIX pointed to the rise of next-generation digital hubs designed for high-density compute, where power availability, connectivity, and scalability must be considered from day one. José Eduardo Quintella, CEO at Terranova reinforced this by highlighting how speed to deployment and execution are becoming critical differentiators, particularly as new facilities are being delivered on accelerated timelines to meet demand.

Connectivity remains the backbone of this transformation. The subsea keynote highlighted new systems such as Firmina and Humboldt that are expanding capacity and reducing latency between Latin America and global markets. Peter Wood, Senior Research Analyst at TeleGeography emphasized the strategic importance of these routes in supporting cloud expansion and future AI workloads, particularly as latency-sensitive applications become more prevalent across the region.

Energy is quickly becoming one of the most important variables in the region’s growth trajectory. As discussed throughout the energy and infrastructure sessions, access to reliable and sustainable power will ultimately determine how quickly Latin America can scale to meet demand. Renewable energy partnerships, evolving grid strategies, and new power procurement models are all playing a role in shaping where future capacity will be built.

What stood out most across Capacity LATAM 2026 was the level of alignment between stakeholders. Operators, investors, and policymakers are increasingly focused on the same challenge: how to scale infrastructure quickly while addressing constraints around power, supply chains, and regulatory complexity. The shift toward AI-ready infrastructure, combined with sustained cloud demand, is accelerating timelines and raising the stakes for execution.

As the event concluded, the broader message was clear. Latin America is no longer simply part of the global network, it is becoming a critical region where infrastructure must be built to support both local demand and international data flows. The next phase of growth will depend on how effectively the region can translate investment into deployable, scalable infrastructure.

Upcoming Capacity events will continue to spotlight the trends shaping digital infrastructure worldwide, from AI-driven demand to evolving connectivity models. Explore the full event calendar at www.capacityglobal.com/events to see where the industry is heading next.

Dates for Capacity LATAM 2027 are not yet available, for information please visit www.capacityglobal.com/events.

The post Capacity LATAM 2026 Signals a New Era of AI, Cloud, and Data Center Growth Across Latin America appeared first on Data Center POST.

AI workloads are pushing data centre infrastructure towards higher rack densities, new cooling strategies and greater power demand. Jamie Darragh, Data Centre Director, Europe, at global data centre engineering design consultancy Black & White Engineering, examines the design implications for the next generation of facilities.

AI and high-performance computing are placing new demands on data centre infrastructure. Rack densities are increasing; facilities are being delivered at larger scale and operators are under pressure to support workloads that consume far greater levels of power and generate far higher heat loads than conventional cloud environments.

Independent forecasts underline the pace of expansion. Gartner estimates global data centre electricity consumption will rise from around 448TWh in 2025 to roughly 980TWh by 2030, driven largely by AI-optimised computing infrastructure. Within that growth, AI servers alone are expected to account for close to 44% of data centre power consumption by the end of the decade.

For our engineering teams, these workloads are altering the practical limits of traditional infrastructure design. Rack densities exceeding 100–200kW are now appearing in project specifications, particularly where large AI training clusters are planned. These loads influence every part of the building environment, from electrical distribution and cooling capacity to structural loading and cable management.

Designing for extreme density

Under these conditions, air cooling alone becomes difficult to sustain across entire facilities. Liquid cooling is therefore increasingly included in the baseline design of new data centres rather than introduced later as a specialist solution. This cooling method is becoming increasingly favourable due to its higher specific thermal capacity compared with air, which enables more efficient heat transfer and removal. Direct-to-chip and rack-level systems are being designed alongside air cooling so facilities can accommodate different densities and equipment types across the same site.

The introduction of liquid systems requires careful coordination between disciplines. Facilities must manage environments where air and liquid cooling operate together, supported by monitoring platforms, safety controls and operational procedures capable of supporting both approaches.

Some IT chips require different liquid cooling temperatures than those used in air-cooling systems, creating technical hurdles for the overall heat rejection system and requiring precise control of the cooling circuit temperature. Another engineering challenge lies in integrating these systems with power distribution, control platforms and maintenance strategies rather than selecting one cooling method over another.

Higher density also narrows operational tolerance. Commissioning becomes more demanding and redundancy strategies require more detailed modelling. Infrastructure must be capable of supporting peak compute demand while maintaining efficiency when loads are lower, placing greater emphasis on flexible electrical and mechanical systems.

The scale of development is also increasing. Buildings that once delivered a few megawatts of capacity are now part of campus-scale developments where multiple data halls contribute to facilities delivering hundreds of megawatts. data centres are increasingly planned and delivered as long-term infrastructure assets rather than individual projects.

This environment encourages repeatable design and industrialised delivery methods. Developers and investors expect predictable construction schedules and consistent performance across multiple sites. As a result, engineering teams are placing greater emphasis on modular infrastructure systems and digital design methods that allow mechanical and electrical systems to be configured and deployed repeatedly.

Power, control and operational intelligence

Power availability is also becoming a determining factor in project planning. In many regions, grid connection capacity is now one of the main constraints on new development. Gartner has warned that by 2027 as many as 40% of AI data centres could face operational limits because of power availability.

Developers are therefore engaging more closely with utilities during early feasibility stages and exploring complementary infrastructure such as on-site generation and energy storage. In some cases, data centres are also being designed to contribute to wider grid stability through demand response and energy management capability.

Artificial intelligence is also beginning to influence how facilities themselves are operated. Machine-learning systems are already being used in some environments to optimise airflow patterns, cooling plant performance and power distribution using live operational data.

The next stage will see more widespread use of integrated control platforms and digital twins capable of modelling facility behaviour in real time. These systems allow operators to simulate infrastructure performance under different load conditions, test operational changes and identify maintenance requirements before faults occur.

Environmental performance remains another constraint as compute density increases. Higher workloads place additional pressure on energy supply while raising questions around water consumption, construction materials and waste heat recovery. Planning authorities and investors are increasingly looking for measurable improvements in efficiency and carbon reporting before approving new developments. Sustainability therefore sits alongside power and cooling as a central engineering consideration rather than a secondary design feature.

Taken together, these conditions create a more complex design environment for data centre infrastructure. Higher compute densities, power constraints and new operational technologies require mechanical, electrical and digital systems to be considered together from the earliest design stages.

Facilities intended to support AI workloads must accommodate far greater performance requirements than earlier generations of data centres while remaining adaptable as infrastructure technologies and operating practices continue to develop.

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About the Author

Jamie Darragh is Data Centre Director, Europe at Black & White Engineering. He leads the delivery of complex, mission-critical projects across the region, with a focus on technical quality, design coordination and strong client relationships. A Chartered Engineer and member of CIBSE and the IET, Jamie has worked across Europe, the Middle East and the UK since 2005. He brings a clear, practical approach to engineering challenges, combining technical expertise with commercial awareness. He is committed to developing teams that work collaboratively and perform at a high level. Jamie has received several industry awards, recognising both his technical capability and his impact on the built environment including ‘Engineer of the Year’ at leading Middle East industry awards.

The post AI Workloads and the Implications for High-Density Data Centre Design appeared first on Data Center POST.

Over the coming weeks, I will be sharing a series of reflections on the realities shaping digital infrastructure development in the United States. These perspectives come from ongoing conversations with communities, policymakers, developers, investors, and industry leaders navigating one of the most consequential infrastructure build cycles in modern history. As artificial intelligence accelerates demand for computing capacity, the decisions being made today, often at the local level, will influence economic competitiveness, regional growth, and public trust for decades to come. This series is intended to create space for more calm, evidence-based dialogue about how we plan, communicate, and lead through this moment of rapid transformation.

We are living through one of the most consequential infrastructure build cycles in modern history, not dissimilar to the first industrial revolution, and yet many of the decisions shaping our digital future are being made in environments defined by urgency, fear, and ideological polarization.

Digital infrastructure, from AI-ready data centers (AI Factories) to edge computing nodes in your local stripmall, are now central to economic competitiveness, national security, innovation, and quality of life. And still, conversations about development often become binary: pro-growth or anti-growth, pro-environment or pro-industry, local control or national interest.

Reality is far more complex. We are living out a paradoxical dilemma in real-time.

What we are seeing across the United States is not simply opposition to projects. It is a collision of competing priorities: environmental stewardship versus economic opportunity, investor timelines versus civic process, national competitiveness versus local autonomy. These tensions are real. They deserve thoughtful navigation, not reactive decision-making. And when the decisions are polarizing, the complexities are at their greatest.

One of the structural challenges is governance itself. As a former elected official in Westchester County, New York, and after serving two-terms, it is clear as day that Federal policy direction does not automatically translate into local action. As I often say: “Federal mandates don’t mean much when governors and local jurisdictions can simply say no.”

This is not a criticism, it is a recognition of how our democratically designed system works. Infrastructure decisions are ultimately shaped at the state, county, and municipal levels. And many of the leaders tasked with evaluating these developments are doing so without the benefit of neutral frameworks, long-term planning guidance, or consistent industry education.

At the same time, the public narrative around digital infrastructure has become increasingly emotional. Headlines focus on water usage, energy demand, or tax incentives, often without equal discussion of the broader economic and societal value these projects create.

Because a data center is not just a building. It is a catalyst.

Data centers are not just buildings. They are an economic driver across a wide-variety of professional services, hospitality, supply chains, and innovation.

Economic activity begins long before construction starts and extends far beyond permanent on-site employment. Yet many impact assessments still rely on narrow metrics that fail to capture this ecosystem effect.

When you look at impact studies narrowly,  like counting permanent jobs, you miss the enormous economic ecosystem that infrastructure development activates.

This disconnect contributes to mistrust and polarization. Communities feel pressured. Investors feel blocked. Policymakers feel caught in the middle.

What is needed now is calm, evidence-based leadership.

Leadership that can hold multiple truths at once:

• Infrastructure development must be sustainable.
• Communities deserve transparency and engagement.
• Economic competitiveness cannot be taken for granted.

Long-term planning must transcend election cycles.

The work I am leading at the OIX Association and the Digital Infrastructure Framework Committee (DIFC), is working to create practical guidance that helps communities evaluate digital infrastructure within their broader economic vision, not project by project, crisis by crisis.

The goal is not to advocate for development at any cost.

The goal is to enable informed decision-making.

Because when stakeholders are equipped with context, data, and structured engagement models, conversations shift. Fear gives way to dialogue. Polarization gives way to planning. Urgency gives way to intentional action.

In a moment defined by technological acceleration, community leadership may simply need to be able to meet ability with reality. This will ensure that we, as a society, can move forward, together, with clarity.

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 Calm Leadership in a Polarized Infrastructure Debate appeared first on Data Center POST.

Duos Technologies Group Inc. (Nasdaq: DUOT), through Duos Edge AI, Inc., has announced the deployment of its second Edge Data Center in the Amarillo, Texas market. The new carrier-neutral, SOC 2-compliant facility is located on Potter County land adjacent to the largest colocation facility in the Texas Panhandle, further strengthening digital infrastructure for carriers, healthcare organizations, enterprises, and public sector entities across the region.​

Building on the success of its initial Amarillo deployment, this latest installation expands Duos Edge AI’s footprint in the Panhandle and adds high-density, low-latency computing capabilities for real-time AI applications, enhanced bandwidth, and secure data processing.

“We are proud to deepen our commitment to the Amarillo market with this second deployment, building on the foundation established by our initial EDC, which brought high-performance computing directly to the heart of the Panhandle,” said Dave Irek, Chief Operations Officer of Duos Edge AI. “This expansion enhances capacity and capability in the region, and by partnering on Potter County land adjacent to a premier colocation hub, we are creating a robust, carrier-neutral ecosystem designed to support innovation, attract investment, and drive long-term economic growth.”​

The company said the deployment also helps reduce dependence on data centers located in tier one cities while supporting underserved and high-growth markets across Texas. Duos Edge AI’s broader Texas expansion includes recent installations in Lubbock, Waco, Victoria, Abilene, and Corpus Christi.​

Potter County Judge Nancy Tanner added, “This collaboration with Duos Edge AI represents a significant investment in our community’s future. Positioning this advanced, carrier-neutral data center on county land next to the Panhandle’s largest colocation facility will attract new businesses, improve connectivity for our residents and schools, and position Potter County as a leader in digital infrastructure.”​

The new EDC is expected to be fully operational in the coming months.

To learn more about Duos Edge AI, visit www.duosedge.ai.

The post Duos Edge AI Deploys Second Edge Data Center in Amarillo, Texas Market appeared first on Data Center POST.

How Centralized Infrastructure Intelligence Turns Emergency Replacements into Controlled Operations

Most infrastructure professionals spend their careers building for the planned: capacity expansions, technology refreshes, migration cycles that unfold over quarters or years. And then a Monday morning email changes everything.

A government agency bans equipment from a trusted vendor. A threat intelligence report reveals that a state-sponsored actor has been inside your network switches for eighteen months. A manufacturer announces that the platform running your entire campus backbone loses support in nine months. In each case, the same question emerges: how quickly can you identify every affected device across every facility, and how fast can you replace them without breaking what still works?

For a surprising number of organizations, the honest answer is: they don’t know. That gap between confidence in steady-state operations and readiness for unplanned mass replacement is where real risk lives.

The Forces That Turn Infrastructure Upside Down

Emergency hardware replacement at scale is not hypothetical. Recent years have produced real-world triggers across four broad categories, each with distinct operational implications.

Regulatory and geopolitical mandates. The federal effort to remove Chinese-manufactured telecommunications equipment from American networks—driven by the FCC’s Covered List and Section 889 of the National Defense Authorization Act—has forced carriers and federal contractors into wholesale infrastructure replacement on compliance timelines that don’t flex for budget cycles. The FCC has estimated the total program cost at nearly five billion dollars. Any organization touching federal dollars must verify its infrastructure is clean; if it isn’t, replacement is a compliance obligation, not a planning exercise.

Security crises that outpace patching. The Salt Typhoon campaign revealed that Chinese state-sponsored hackers had penetrated multiple major US telecommunications providers, maintaining persistent access for up to two years—exploiting legacy equipment, unpatched router vulnerabilities, and weak credential management. Investigators found routers with patches available for seven years that had never been applied. For affected carriers, the response demanded physical replacement of compromised infrastructure that could no longer be trusted regardless of patch status. When an adversary achieves sufficient persistence, patching becomes insufficient. Replacement is the only reliable remediation.

End-of-life announcements. Vendor lifecycle decisions create quieter but equally urgent pressure. An organization running multiple hardware platforms faces different end-of-support timelines for each, and dependencies between them mean replacing one can cascade into forced changes elsewhere. Without a consolidated view of what is running, where, and when it loses support, these effects are invisible until they cause failures.

Architectural shifts. Zero trust adoption, SASE frameworks, and cloud-delivered security are rendering entire categories of on-premises equipment architecturally obsolete—not because they’ve failed, but because the security model has moved on. The question is not whether legacy VPN appliances and perimeter firewalls will be replaced, but how quickly, and whether the organization has the visibility to execute in a controlled manner.

Why Standard Processes Break Down

Every mature IT organization has IMAC processes: Install, Move, Add, Change. These handle the predictable rhythm of infrastructure life. Emergency replacement programs share almost none of their characteristics.

They are triggered externally. Their scope is massive—hundreds or thousands of devices across multiple sites. They arrive without allocated budgets or pre-positioned inventory, carrying compliance deadlines indifferent to resource constraints.

The organizations that handle these events well recognize them for what they are: standalone programs needing their own governance, funding, and dedicated teams—and their own information infrastructure. That last requirement is where centralized infrastructure management becomes not a convenience but a prerequisite.

What Centralized Infrastructure Intelligence Must Deliver

Four questions—answered immediately.

What is affected, and where is it? When a regulatory notice references a specific manufacturer, or a security advisory identifies a particular hardware model and firmware version, the operations team needs a definitive count within hours, not weeks. Organizations maintaining a continuously updated centralized inventory—capturing hardware models, firmware versions, physical locations, logical roles, and contractual associations—can answer by running a query. Organizations relying on spreadsheets and periodic audits cannot. The difference in response time is typically measured in weeks, and in a compliance-driven scenario, weeks are what you don’t have. Equally important is dependency mapping: understanding that replacing a core switch will affect upstream routers, downstream access switches, and out-of-band management paths. Without it, a replacement that looks straightforward on paper can produce cascading outages in execution.

What is the replacement path? A legacy switch may need to be replaced by different models depending on port density, power constraints, and compatibility with adjacent equipment. Workflow-driven execution ensures every replacement follows the same approval steps, documentation requirements, and validation procedures—preventing errors that compound in programs spanning hundreds of sites.

Where are we right now? Leadership needs a live view of progress—which sites are lagging, where tasks are stalled, which teams are hitting milestones. This enables resource reallocation, timely escalation of procurement bottlenecks, and an auditable record for regulators. It also surfaces patterns previously invisible: a region that consistently runs behind, or an approval step adding days of unnecessary latency.

What did we learn? Emergency replacements are no longer rare—any organization operating at scale should expect one every few years. Those that conduct structured post-project reviews build a compounding advantage: better scoping templates, more accurate resource models, and pre-validated replacement mappings that make the next response faster.

Building Readiness Before the Next Crisis

Emergency replacements cannot be made painless—they are disruptive, expensive, and stressful regardless of preparation. But the difference between an organization that navigates one in three months and one that takes twelve is almost entirely a function of work done before the trigger.

That preparation has three dimensions: information readiness (a continuously updated inventory with hardware identity, location, firmware status, and dependency relationships), process readiness (defined workflow-driven procedures that activate quickly rather than being reinvented under pressure), and organizational readiness (governance, budget authority, and executive sponsorship that allows an emergency program to stand up as a dedicated initiative).

The organizations best positioned for the next regulatory mandate, zero-day disclosure, or end-of-life cascade are investing in that readiness today—not because they know what the trigger will be, but because they’ve built a discipline prepared for all of them.

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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 When Your Data Center Becomes a Liability Overnight appeared first on Data Center POST.

The global data center HVAC market was valued at USD 13.7 billion in 2025 and is estimated to grow at a CAGR of 9.8% to reach USD 36 billion by 2035, according to recent report by Global Market Insights Inc.

Growth in the global data center HVAC industry is being fueled by rising computing intensity, expanding AI-driven workloads, and the continued development of hyperscale and enterprise facilities. As server densities increase and high-performance computing environments generate greater thermal loads, advanced cooling infrastructure has become essential to maintain operational stability and uptime. Research and development efforts across the HVAC industry are increasingly focused on liquid cooling technologies and next-generation thermal management systems capable of handling elevated power densities.

At the same time, stricter regulatory oversight related to energy consumption and environmental performance is encouraging operators to enhance system efficiency and reduce carbon output. ESG-focused initiatives and net-zero commitments are prompting facility upgrades aimed at optimizing Power Usage Effectiveness and lowering operating expenses. Improvements in airflow engineering, adoption of sustainable refrigerants, and integration of energy-efficient cooling architectures are reshaping infrastructure strategies. As regulatory expectations and energy costs continue to rise, demand for intelligent, high-efficiency HVAC solutions in data centers is expected to accelerate significantly.

Rising load capacities, sustainability targets, and regulatory compliance requirements are creating pressure for compact, scalable, and adaptable HVAC systems. Industry participants are responding by designing modular cooling platforms that can operate effectively across diverse geographies while maximizing space utilization and energy performance.

The data center HVAC market from solutions segment accounted for 76% share in 2025 and is forecast to grow at a CAGR of 8.9% from 2026 to 2035. Advanced monitoring tools equipped with artificial intelligence enable predictive maintenance, improve airflow management, and reduce unnecessary power consumption. Increased adoption of liquid-based cooling technologies is supporting high-density server environments while enhancing reliability and extending equipment lifespan through energy-conscious design.

The air-based cooling technologies segment held a 50% share in 2025 and is projected to grow at a CAGR of 8.8% during 2026-2035. Enhanced airflow optimization systems, variable-speed fan configurations, and intelligent environmental controls are improving thermal consistency and minimizing energy waste. Economizer-enabled designs are facilitating greater use of ambient air, while modular cooling units support scalability across both hyperscale and edge environments. Growing server power density is also accelerating interest in direct cooling and immersion-based methods supported by advanced coolant formulations that enhance heat transfer efficiency.

United States data center HVAC market reached USD 4.7 billion in 2025. Increasing cloud integration and AI-intensive applications are driving demand for more efficient cooling architectures. Investments are being supported by electrification incentives and decarbonization initiatives, encouraging broader adoption of intelligent HVAC controls and energy-optimized systems. Integration with smart building platforms and grid-responsive technologies is enabling facilities to manage peak loads, reduce demand charges, and incorporate renewable energy sources.

Key companies operating in the global data center HVAC market include Vertiv, Schneider Electric, Carrier Global, Daikin Industries, Trane Technologies, Johnson Controls, STULZ, Alfa Laval, Danfoss, and Modine Manufacturing. Companies in the global market are strengthening their competitive position through continuous innovation, strategic partnerships, and geographic expansion. Leading players are investing heavily in research and development to enhance liquid cooling efficiency, improve airflow intelligence, and integrate AI-driven monitoring systems. Collaborations with cloud service providers and data center developers are enabling customized cooling deployments for high-density environments. Firms are also expanding manufacturing capacity and regional service networks to support rapid infrastructure growth. Sustainability-focused product development, including low-global-warming-potential refrigerants and energy-efficient system architectures, is becoming a central competitive differentiator.

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As global investment in AI infrastructure, power, and advanced manufacturing accelerates, a critical constraint is coming into sharper focus—project execution.

A newly announced $25 million Series A funding round for Foresight underscores a broader industry shift: while capital continues to flow into large-scale infrastructure, delivering these projects on time and on budget remains a persistent challenge.

The current wave of infrastructure investment is unprecedented in both scale and complexity. Hyperscale data centers, energy systems, and advanced industrial facilities are being developed simultaneously across global markets, often with overlapping supply chains and tight delivery timelines.

However, execution has emerged as a systemic issue.

Research indicates that nearly 90% of large-scale infrastructure projects are completed late or exceed budget expectations. In the context of AI infrastructure, delays can have cascading effects—impacting capacity availability, increasing financing costs, and delaying revenue generation.

Industry observers note that as demand for compute continues to surge, particularly for AI workloads, the margin for error in delivery timelines is shrinking.

A Shift Toward Predictive Delivery Models

Foresight, which positions itself as a predictive project delivery platform, is part of a growing cohort of technology providers aiming to address these execution challenges through data and automation.

The company’s platform is designed to move beyond traditional project management approaches—often reliant on static schedules and retrospective reporting—by introducing continuous validation of project progress and early identification of risk factors.

According to the company, its system enables infrastructure owners to establish baseline schedules more quickly, integrate data across stakeholders, and forecast potential delays before they materialize. Early adopters report improvements in forecast accuracy and reductions in cost overruns.

While such claims reflect a broader trend toward digitization in construction and infrastructure delivery, they also point to a deeper industry need: greater predictability in increasingly complex builds.

Why Execution Matters More in the AI Era

For data center developers and operators, execution risk is becoming more consequential.

Unlike previous infrastructure cycles, AI-driven demand is both immediate and rapidly evolving. Delays in bringing capacity online can result in missed opportunities, strained customer relationships, and competitive disadvantages in key markets.

At the same time, projects are becoming more interdependent. Power availability, equipment procurement, and site development must align precisely—leaving little room for disruption.

This dynamic is prompting a reassessment of how infrastructure projects are planned and managed, with greater emphasis on real-time data, cross-functional visibility, and proactive intervention.

Expanding Beyond Data Centers

Although the initial focus is on sectors such as hyperscale data centers, the challenges associated with project execution are not unique to digital infrastructure.

Foresight plans to expand its platform into adjacent industries, including energy, defense, and advanced manufacturing—areas that share similar characteristics: large capital commitments, complex supply chains, and high sensitivity to delays.

The company’s recent funding, led by Macquarie Capital Venture Capital, reflects investor interest in solutions that address these systemic inefficiencies.

An Industry Inflection Point

The emergence of predictive project delivery tools signals a broader transformation in how infrastructure is built.

For years, innovation in the data center sector has centered on compute performance, cooling technologies, and energy efficiency. Increasingly, attention is shifting toward the process of delivery itself.

As infrastructure programs continue to scale, the ability to execute with precision may become a defining factor in project success.

In an environment where demand is high and timelines are compressed, the question facing the industry is evolving—from whether projects can be financed to whether they can be delivered as planned.

The post Foresight Raises $25M to Tackle Infrastructure Execution Risks in the AI Era appeared first on Data Center POST.

Duos Technologies Group Inc. (Nasdaq: DUOT), through Duos Edge AI, Inc., has formed a strategic partnership with Seimitsu to revolutionize digital infrastructure across Georgia. By combining Duos Edge AI’s modular, high-performance solutions with Seimitsu’s expansive high-speed fiber network, the collaboration delivers low-latency processing and high-bandwidth connectivity for businesses, municipalities, and healthcare providers statewide.

“Our mission is to bring the power of the cloud to the street corner. Partnering with Seimitsu allows us to integrate our Edge AI nodes into a robust, reliable fiber backbone, ensuring that Georgia’s industries – from the port of Savannah to Atlanta’s technology corridors – have the infrastructure they need to compete globally,” said Dave Irek, Chief Operations Officer of Duos Edge AI.

As demand for real-time data processing grows, driven by AI, IoT, and autonomous systems, infrastructure closer to end users has become critical. This partnership positions Georgia at the forefront of the Edge revolution with ultra-low latency processing, Seimitsu’s 25 terabits of low-latency fiber capacity across the Southeast, and rapid deployment of Duos Edge AI nodes in underserved and high-demand areas.

Sam Cook, CEO of Seimitsu, added, “For more than 40 years, Seimitsu has been committed to connecting our communities. This partnership with Duos Edge AI represents the next step in that journey. By integrating edge computing directly into our network, we are moving beyond simple transit services and delivering true digital transformation for our clients.”

The partnership supports Duos Edge AI’s nationwide expansion of distributed AI infrastructure through strategic fiber, power, and site partnerships.

To learn more about Duos Edge AI, visit www.duosedge.ai.

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In the rapidly evolving landscape of data centers powered by artificial intelligence, energy storage strategies are undergoing a profound transformation. ZincFive^®, a leader in nickel-zinc battery solutions, has unveiled its third annual 2026 Data Center Energy Storage Industry Insights Report, developed with Endeavor Business Intelligence. This comprehensive study, based on surveys of 150 global industry professionals conducted in early 2026, reveals how AI workloads are reshaping power infrastructure priorities.

Key Trends Emerge

The report identifies surging AI demands as a central force. Notably, 57% of respondents report that AI is driving higher power density needs and smaller footprints, a trend holding steady from 54% last year. Additionally, 52% emphasize managing AI’s dynamic power fluctuations and upholding power quality – a sharp rise from 37% in 2025 – highlighting the urgency for resilient storage solutions.

Cost and safety dominate decision-making. An impressive 84% prioritize total cost of ownership, up from 79% in 2025 and 65% in 2024, while 76% stress battery chemistry safety. AI dynamic power ranks as the second-biggest driver for technology shifts at 49%, after cost (58%). Sustainability also plays a pivotal role, with 70% factoring it into purchases and 46% achieving moderate to significant cost savings from sustainable initiatives.

Prioritizing Battery Features for AI Challenges

When addressing AI-specific power issues, professionals rank power density (38%), safety (37%), uptime (33%), and maintenance ease (32%) as top criteria for battery selection. These insights underscore the need for advanced chemistries like nickel-zinc, which ZincFive champions for its high power density, safety, and sustainability in mission-critical applications.

“As AI workloads continue to transform data center infrastructure, operators are facing new challenges around power density, power quality, and system reliability,” said Tod Higinbotham, CEO of ZincFive. “This year’s report highlights how the industry is adapting to these evolving demands while balancing cost, safety, and sustainability priorities. The findings underscore the growing need for energy storage technologies capable of delivering high power performance, operational resilience, and infrastructure efficiency in the era of AI-driven data centers.”

Implications for the Industry

This report builds on prior editions, tracking consistent yet intensifying trends amid AI’s expansion. Data center operators can download the full 2026 report, along with 2025 and 2024 versions, from ZincFive’s website to inform strategic planning. As AI continues to demand more from power systems, innovations in safe, efficient energy storage will be crucial for maintaining uptime and sustainability goals.

To read the full press release, please click here.

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Iran’s recent drone strikes across the Gulf revealed a new vulnerability in the global digital economy. For the first time, hyperscale cloud infrastructure that powers banks, fintech platforms, and digital services became a direct target of regional conflict.

According to reporting by Reuters, drone strikes during the regional conflict damaged two AWS data center facilities in the United Arab Emirates, while a nearby strike affected another in Bahrain.

The attacks disrupted power systems, triggered fire suppression systems, and forced operators to isolate affected infrastructure. Several availability zones in the AWS Middle East region went offline while engineers restored operations.

The disruption spread quickly through the regional digital ecosystem.

Banks and fintech platforms reported delayed transactions and degraded services. Consumer applications also experienced outages. Companies including Careem, Emirates NBD, Hubpay, Alaan, Snowflake, and Policybazaar UAE reported disruptions during the incident as cloud workloads failed over to backup infrastructure.

The attacks did not completely destroy the facilities, but they exposed how quickly a localized strike can ripple through a cloud-dependent economy.

Analysts say incidents of this scale typically generate tens of millions of dollars in combined operational losses when infrastructure repair, service downtime, and mitigation costs are included. Cloud operators must repair damaged equipment and restore systems, while customers absorb the cost of interrupted digital services.

A Rapidly Expanding Digital Infrastructure Hub

The Gulf has rapidly become one of the fastest-growing digital infrastructure markets in the world.

Today the Gulf Cooperation Council hosts more than 70 data centers with roughly 557–738 megawatts of live IT capacity.

Governments and technology companies have already announced more than $30 billion in new data center investments, and analysts expect Gulf computing capacity to exceed 2 gigawatts by 2030.

The region also hosts an expanding hyperscale cloud ecosystem. The Gulf currently includes around ten cloud regions operated by Amazon Web Services, Microsoft Azure, Google Cloud, Oracle, and Alibaba. These regions contain approximately 20-25 hyperscale facilities, also known as availability zones.

Saudi Arabia’s plans to build a 500-megawatt AI data center complex illustrate the scale of future expansion.

Infrastructure Concentrated in a Few Cities

Despite this growth, most computing capacity remains concentrated in a handful of metropolitan clusters.

These hubs contain roughly 80–85 percent of the Gulf’s computing capacity. This concentration means disruptions affecting only a few metropolitan areas could impact most of the region’s cloud infrastructure.

Analysts estimate that up to 70 percent of Gulf data center capacity lies within areas exposed to regional conflict escalation, particularly along the Persian Gulf coastline.

A Global Digital Corridor

The strategic importance of the region extends beyond local markets.

Around 90 percent of internet traffic between Europe and Asia travels through Middle Eastern routes, supported by roughly 20 submarine cable systems and 13 active Internet Exchange Points across the Gulf.

Oman plays a particularly important role in this connectivity network. The country hosts five submarine cable landing stations and connections to more than fourteen international cable systems, positioning it as a key gateway linking Asia, Europe, and Africa.

As hyperscale cloud infrastructure and submarine cable networks continue expanding, the Gulf increasingly serves as a digital bridge between continents.

Conflict Risk Meets Digital Infrastructure

Cloud data centers are no longer just technical facilities, they have become critical infrastructure and Iran’s strikes demonstrated how modern conflicts now intersect with infrastructure that powers the digital economy.

Cloud data centers now sit alongside ports, pipelines, and power plants as strategic assets. The more the Gulf becomes a hub for cloud infrastructure, AI computing, and global internet traffic, the more regional instability can trigger international digital disruptions.

The attacks on AWS facilities therefore represent more than a regional security incident. They highlight a structural risk: a growing share of global digital infrastructure now operates inside one of the world’s most geopolitically volatile regions.

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About the Author

Matvii Diadkov is a technology investor and operator with over a decade of experience building digital infrastructure platforms across logistics, e-commerce, real estate, blockchain technologies, and AI. His work includes ecosystem-level deployments and advisory roles tied to Vision-aligned digital systems in asset-heavy sectors across Oman and the wider region, where he also an adviser to Gulf businesses on digital transformation and infrastructure development.

The post Middle East Conflict Could Put $30 Billion of Digital Infrastructure at Risk appeared first on Data Center POST.

Looking back on a career in IT, I wanted to reflect on the 20-plus years I spent working in and running data centers for Fortune 500 companies in the New York and New Jersey area. This was an exciting time leading both large and small teams through some of the most complex transformations in IT infrastructure. That included designing a trading floor infrastructure for a major bank that was implemented globally, overseeing the merger of two banks with very different IT backbones, driving a mainframe-to-open-systems modernization effort, managing a data center consolidation, and establishing global IT standards.

Today, the challenges to the job are even more profound than transitioning from mainframes to the Internet, digital, mobile, and cloud world. With the advent of AI and explosive data growth from so many more devices and applications, IT infrastructure leaders must rewrite their stories to keep pace.

After moving to the vendor side several years ago and working as a Senior Solutions Architect at Komprise, I get to work with IT leaders daily.  I see just how much the role of the infrastructure or data center director has changed. Here’s how I see the shift with some tips for IT infrastructure directors and executives to stay relevant in their organizations while navigating these cataclysmic shifts in technology and work.

A Shift Toward Complexity and Constant Adaptation

The job of managing data centers and infrastructure has become more multi-faceted. It is no longer just about uptime and physical infrastructure. Directors are now expected to understand a rapidly expanding universe of technologies. There is increased separation of duties and new responsibilities that did not exist 10 years ago. Add in constant security threats, cloud optimization demands, and the exponential growth of unstructured data which requires ensuring that it is accessible where needed, but in a safe, secure manner and the scope of the role expands fast. And while all of this happens, IT budgets are being squeezed. The mandate remains the same: do more with less.

The Unstructured Data Growth Challenge

A resounding pressure point today is storage and the relentless growth of unstructured data. Recent estimates from IDC show that over 80 percent of enterprise data is unstructured, and that volume is expected to reach 291 zettabytes by 2027.

How do you back it all up in a timely way? How do you replicate it for disaster recovery? How do you ensure protection and accessibility? How do you efficiently prepare it for AI ingestion? It has really come down to understanding that all data is not the same, and you must treat data differently so that you can be efficient in your management of the data. Knowing what data you have, where it lives, and what value it offers is now a core competency for any infrastructure leader.

Hybrid IT and Simplification as a Strategy

Over the past few years, I have seen storage and infrastructure strategies shift significantly. The old model of managing everything the same way is obsolete. My approach has always been to keep environments as simple and basic as possible to reduce unnecessary complexity. In today’s typical hybrid IT landscape, that means using tools that are vendor-agnostic, that work across on-prem, outsourced, and cloud environments, and that give you a single dashboard to make informed decisions.

AI, Cost Cutting, and Evolving Job Roles

There is a lot of noise about AI taking over roles in IT. I do not believe that infrastructure managers, storage engineers, or data center professionals should fear for their jobs. However, relying on the status quo is not a strategy. The one thing that I have seen as a necessity for IT personnel is the ability to adjust and evolve as changes have appeared in the IT arena.

One thing is certain; AI is becoming ingrained across the business, and IT must be able to support it across every function. Nearly 90% of enterprises report regular AI use in at least one business function, compared with 78 percent in 2024, according to 2025 research from McKinsey. Learning how to work with AI, understanding its use cases and business applications, and knowing how to prepare the right data for it are key new skills. Equally important is staying current with cloud technologies and security best practices.

Balancing Cost, Security, and AI Readiness

IT leaders are being asked to walk a tightrope. On one side is the need to control cost and ensure security. On the other side is the drive to make data accessible and ready for AI. Yet these demands are interlinked. Cost control and security are critical to ensure that AI ambitions don’t fail or stall. Without security, AI becomes a liability rather than an advantage. The question facing today’s IT directors is along the lines of: “How do we make data more accessible without increasing risk or cost?” Success will come from integrating these requirements, not prioritizing one at the expense of the other.

Why It Is Still an Exciting Time to Work in IT Infrastructure

There is such a tremendous amount of growth in the amount of data being generated, and data has moved from a support function to a true driver of decisions, products, and strategy. Data is now central to every organization, from predicting outcomes, automating decisions, and personalizing experiences in real-time. Add to the fact that both AI and ML have accentuated the value of data, and there’s a lot of opportunity in this area for people who want to grow their careers and remain in IT infrastructure.

The ability to efficiently and strategically manage data and build the right environment for cost control along with flexibility and innovation is a huge need for the enterprise. In our recent industry survey (link) we found that AI data management is a top desired skillset, and organizations are prioritizing hiring individuals who can confidently lead the AI infrastructure discipline.

What’s Ahead for 2026 and Beyond

Looking ahead, I expect infrastructure directors to move beyond managing infrastructure to leading transformation. This means aligning technology with business strategy in areas such as AI integration, cybersecurity, cost control, and workforce development. AI is moving beyond the hype; it’s becoming increasingly relevant in production workflows. Security will continue to be a priority and will need to be addressed. Lastly, bridging the talent gap and reskilling existing workforces should be a focus.

Five Tips for Adapting as a Modern Infrastructure Leader

1. Treat data differently
   Stop managing all data the same way. Understand what is valuable, what is redundant, what is creating undue risks, and what needs to be accessible. Prioritize accordingly.
2. Focus on vendor-agnostic tools
   Choose solutions that work across vendors, technologies and architectures and reduce lock-in. This simplifies operations, reduces cost and delivers better agility.
3. Invest in learning AI concepts
   You do not need to be a data scientist. But you should understand how AI uses data, and how to prepare infrastructure to support it with proper governance.
4. Stay current with security developments
   Security threats evolve constantly. Keep up with best practices and build security into every aspect of data and infrastructure management. Partner with the CSO.
5. Use simplicity as a guiding principle
   Complexity creates risk and inefficiency. Whenever possible, simplify tools, processes, and architectures.

Final Thoughts

The infrastructure director’s role is not what it used to be, and that is a good thing. The scope has grown, the influence has deepened, and the strategic value of IT is clearer than ever. While the challenges are many, so are the opportunities. Those who can adapt, simplify, and lead through change will continue to be essential to their organizations.

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About the Author: 

Paul Romano is a Senior Solutions Architect at Komprise. He has 25 years’ experience at Fortune 100 companies, possessing significant expertise in setting IT direction and policies, data center build outs and migrations, IT architecture, server and endpoint security, penetration testing, establishing productions support standards and guidelines, managing large IT projects and budgets, and integrating new technologies/technology practices into existing environments.

The post The New Demands on Data Center and Storage Leaders appeared first on Data Center POST.

Duos Technologies Group, Inc. (Nasdaq: DUOT), through its operating subsidiary Duos Edge AI, Inc., has executed a definitive contract with Hydra Host, advancing the previously announced plan to deploy a high-density NVIDIA GPU cluster for a leading global technology company. The GPU-as-a-Service (GPUaaS) contract is expected to generate approximately $176 million in revenue over a 36 month term, including an initial $18 million customer pre payment, with projected gross margins exceeding 80 percent and expected annual EBITDA of approximately $40 million.

The agreement establishes Duos Edge AI as an emerging provider of distributed AI infrastructure designed for large scale compute workloads. Fully funded through Duos Technologies Group’s recently completed $65 million public offering and existing hardware financing arrangements, the partnership enables deployment to commence immediately without reliance on additional equity financing.

“The initial deployment will be located at a strategic site and will consist of multiple high density modular Edge Data Centers (EDCs) which are specifically designed to support large scale AI workloads,” said Doug Recker, newly appointed CEO effective April 1st, 2026. “Manufacturing of the EDCs is currently underway, with critical power modules already ordered to support deployment timelines.”

The first phase of the project includes an initial 4.3 plus MW colocation commitment from a leading global technology company that will serve as the project’s anchor tenant. This deployment represents the largest Edge Data Center project in Company history, with additional colocation revenue expected as the site scales toward its full power capacity.

This contract provides strong commercial validation for Duos’ High Power EDC business line, purpose built for AI companies and high performance compute tenants that require premium rack space, dedicated high density power, and rapid deployment. As Duos advances its long term objective of 75MW of distributed capacity, the Company is actively evaluating additional high density deployment sites to meet accelerating demand from AI hyperscalers, NeoCloud operators, and other AI infrastructure customers.

To learn more about Duos Technologies Group, Inc., visit www.duostechnologies.com.

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Metro Connect USA 2026 brought the digital infrastructure community together in Fort Lauderdale, Florida, Feb. 23 to 25, as executives, investors and network operators gathered to discuss the evolving connectivity landscape. Over three days, conversations across keynote sessions, panels and private meetings focused on how the industry is adapting to the rapid growth of artificial intelligence, cloud services and bandwidth demand.

The 2026 event drew more than 3,700 decision-makers representing over 1,200 companies, reflecting the scale of collaboration and investment shaping the next phase of digital infrastructure development in the United States.

Artificial intelligence was a central theme throughout the conference. Industry leaders discussed how AI workloads are driving new requirements for data center capacity, fiber connectivity and power infrastructure. As AI adoption expands beyond hyperscale environments into enterprise applications and edge deployments, operators are facing increasing pressure to scale networks capable of supporting high-volume data movement and compute-intensive workloads.

Fiber infrastructure also remained a key topic. Discussions throughout the event highlighted continued investment in metro fiber expansion, long-haul backbone routes and fiber-to-the-home networks. As cloud platforms, streaming services and AI applications generate greater data traffic, fiber continues to serve as the underlying foundation supporting the digital economy.

Several speakers addressed how infrastructure and investment strategies are evolving alongside these shifts. Marc Ganzi, Chief Executive Offer at DigitalBridge discussed the continued influx of capital into digital infrastructure and the importance of disciplined investment as the sector scales. Steve Smith, Chief Executive Officer at Zayo Group highlighted the role of fiber expansion in supporting enterprise connectivity and hyperscale demand. Alex Hernandez, CEO of PowerBridge, participated in discussions focused on the growing power demands associated with AI infrastructure, including how utilities, data center developers and investors are working to expand power capacity and modernize energy delivery to support large-scale computing environments.

From the investment perspective, Santhosh Rao, Managing Director, Head of Digital Infrastructure at MUFG explored the evolving capital structures supporting infrastructure development, including structured financing and private credit solutions. Anton Moldan, Senior Managing Director at Macquarie Group shared insights into how institutional investors continue to evaluate digital infrastructure assets as a long-term growth opportunity within global infrastructure portfolios.

Beyond the formal sessions, Metro Connect remains known for its highly productive networking environment. Thousands of meetings took place across the event’s exhibit floor, private meeting rooms and curated networking gatherings, reinforcing the conference’s reputation as a place where partnerships are formed and transactions begin.

Outside the formal sessions, attendees spent much of the week engaged in meetings and informal discussions across the venue’s networking areas. Many participants noted that the event continues to serve as a gathering point for companies exploring partnerships, investment opportunities and infrastructure projects.

Looking ahead, the industry will reconvene next year as Metro Connect USA 2027 moves to a new venue. The event will take place February 8–10, 2027 at the Diplomat Beach Resort in Hollywood, Florida.

The post Metro Connect USA 2026 Highlights the Future of U.S. Digital Infrastructure appeared first on Data Center POST.

Originally posted on Hivelocity.

Artificial intelligence (AI) is driving a new wave of innovation that demands more from infrastructure than ever before. As organizations train larger models, process massive datasets, and deploy AI, performance, scalability, and cost efficiency have become even more critical. In this high-performance landscape, bare metal servers offer a clear advantage over virtualized environments, delivering the raw power and control that AI workloads require.

Bare metal servers provide direct access to dedicated hardware (CPU cores, memory, storage) without the overhead of virtualization. This architecture eliminates the “noisy neighbor” effect that is common in cloud environments, ensuring consistent, predictable performance. For AI tasks such as model training and inferencing, where compute intensity and I/O throughput are key, that consistency can translate into measurable performance gains.

Cost Predictability

While there is a common industry misconception that bare metal is more expensive than cloud alternatives, this is often not the case. In reality, long-term AI operations, especially within predictable or stable workloads, often see significant savings with bare metal infrastructure. Because resources are dedicated, costs are fixed and transparent, cutting down on the unpredictable cloud egress fees and scaling premiums that typically come with consumption-based models.

This predictability of cost allows AI teams to plan budgets more effectively, particularly for ongoing training pipelines and continuous model tuning. Hivelocity’s bare metal solutions allow customers to scale resources strategically, allowing workloads to evolve without the billing complexities that can make cloud deployments difficult to manage.

To continue reading, please click here.

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Empire Fiber Internet, a leading fiber optic internet service provider serving communities across New York and Pennsylvania, is marking continued progress on the Light Up Livingston broadband initiative across Livingston County. Service is now live in parts of Lima, Mount Morris, Dansville, and Nunda, NY, with expansion targeting thousands more homes and businesses in Springwater, Conesus, Ossian, Sparta, West Sparta, and Wayland.

Construction of the Light Up Livingston network is actively progressing, with the project’s fiber backbone largely complete and 68 miles of aerial fiber installed so far. Extending service lines to individual homes is expected to take place in the summer and fall of 2026, as crews continue running additional lines and splicing lateral cables into the main fiber ring.​

“We are proud to celebrate this milestone made possible through a strong public-private partnership,” said Shannon Hillier, Livingston County Administrator. “By working collaboratively, we’ve combined resources and a shared vision to continue expanding high-speed internet access to all communities in Livingston County. This partnership reflects what’s possible through aligning the public and private sectors around a common goal.”​

Supported by New York State’s ConnectALL Municipal Infrastructure Program and USDA ReConnect grant program, this multi-million-dollar effort partners Empire Fiber Internet with Livingston County and Hunt EAS for reliable 100% fiber.

Empire State Development President, CEO and Commissioner Hope Knight highlighted the project’s role in closing the digital divide. “Under Governor Hochul’s leadership, New York is making historic investments to close the digital divide and ensure every community has access to reliable, high-speed internet. Projects like Light Up Livingston are expanding critical fiber infrastructure in rural communities, helping residents, businesses, and institutions stay connected and compete in today’s digital economy. Through strong partnerships with local governments and private providers, we are building a more connected and economically vibrant New York.”​

“We’re excited to see the Light Up Livingston vision becoming a reality for more residents every day,” said Kevin Dickens, CEO of Empire Fiber Internet. “Our team is hard at work extending our fiber network throughout Livingston County. These communities are the driving force behind our continued efforts to expand our network and deliver high-speed internet with its incredible, transformative power. We look forward to becoming part of the community and supporting residents and businesses as they connect, work, and grow.”​

Livingston County residents can check service availability by visiting www.shop.empireaccess.com and entering their address, and can also sign up to receive updates as construction continues.​

To learn more about Empire Fiber Internet, visit www.empireaccess.com.

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As artificial intelligence infrastructure continues to scale, the physical networks connecting large GPU clusters are becoming increasingly complex. Training environments for large language models and advanced machine learning workloads require massive bandwidth between compute nodes, driving a rapid increase in fiber connectivity inside modern data centers.

Telescent’s latest system addresses these operational challenges with a new high-density robotic cross connect system designed for DR4 and DR8 parallel optics interconnects used in large-scale AI training clusters. The system extends the company’s G5 robotic platform to support the extremely high fiber counts now common in AI cluster architectures.

AI Infrastructure Is Driving Massive Fiber Growth

AI workloads are reshaping the internal design of data center networks. As GPU clusters grow larger and more interconnected, operators are increasingly deploying parallel optics technologies such as DR4 transceivers to support the bandwidth required between compute nodes. While these architectures enable faster data movement across GPU fabrics, they also significantly increase the number of fiber connections that must be installed and managed.

In some environments, a single AI training cluster can include an exceptionally high number of fiber links. Managing those connections manually can slow deployment timelines and increase the risk of configuration errors or service interruptions.

Automation at the Physical Layer

Telescent’s robotic cross connect system is designed to automate physical layer management in these high-density environments. By enabling automated fiber path configuration and reconfiguration, the system allows operators to turn up new cluster resources more quickly while minimizing the manual patching work that traditionally accompanies large-scale network changes.

“The bandwidth requirements of AI infrastructure are rewriting the rules of data center fiber management. A single AI cluster can require hundreds of thousands of fiber connections, and the move to parallel optics architectures like DR4 multiplies that count significantly,” said Anthony Kewitsch, CEO and Founder of Telescent. “Our new high density robotic cross connect system gives operators a powerful automated solution to manage this complexity to ensure maximum GPU utilization and operational efficiency while future proofing the physical layer for the next wave of AI innovation.”

Supporting the Next Phase of AI Infrastructure

As hyperscale operators and AI infrastructure providers deploy increasingly dense compute environments, the operational demands of managing fiber connectivity are growing alongside them. Automation platforms that bring intelligence and remote control to the physical network layer are becoming an important tool for maintaining reliability and flexibility.

Telescent’s robotic automation platform enables software-controlled fiber connectivity across large-scale deployments, helping operators reduce manual intervention while allowing network paths to be reconfigured quickly as infrastructure requirements evolve.

Demonstration at OFC 2026

Telescent will showcase a live demonstration of the new system at the Optical Fiber Communication Conference (OFC) 2026 in Los Angeles from March 17 to 19 at Booth #607. The demonstration will highlight how robotic automation can simplify the management of fiber-dense AI clusters and help operators address the growing connectivity demands of next-generation AI infrastructure.

To learn more about Telescent’s optical automation solutions, visit www.telescent.com.

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Data Center POST had the opportunity to connect with David Wang, Founder and Chairman of BRIGHTRAY, who is leading a new paradigm in data center delivery—speed without compromise, scale with sustainability. With over 25 years of industry experience, including senior leadership at Schneider Electric and HP managing mission-critical infrastructure, Wang founded BRIGHTRAY to address the explosive AI-driven demand for rapid, high-density infrastructure.

Traditional construction can no longer keep pace. That’s why at BRIGHTRAY our strategy on proprietary Prefabrication Data Center Solutions, enabling ultra-high-density deployment at unprecedented speed. This is proven by the company’s Malaysia milestones: MY-01 (20MW) delivered in 8 months, and MY-02 (50MW) completed in just 6 months, setting new benchmarks for speed and scalability.

Looking ahead, Wang is leading BRIGHTRAY’s global expansion from our strong APAC foundation into the U.S. and Middle East markets with the vision to establish BRIGHTRAY as “Your Gateway to Excellence in Integrated IDC Services”, building a resilient, sustainable digital backbone for the AI era.

The information below is summarized to provide our readers a deeper dive into who BRIGHTRAY is, what they do and the problems they are solving in the industry.

What does BRIGHTRAY do?  

BRIGHTRAY provides prefabricated data center solutions that are designed and built off-site for faster, more efficient deployment.

What problems does BRIGHTRAY solve in the market?

The company addresses the growing demand for speed and scalability in data center infrastructure. BRIGHTRAY helps clients compress deployment timelines, reduce execution risk, and bring infrastructure online faster, enabling quicker returns and greater adaptability across different environments. The company is capable of delivering a 50MW data center in as fast as 6 months, setting a new industry benchmark

What are BRIGHTRAY’s core products or services?

Prefabrication Data Center Solutions

Full Prefabrication DC（FPD：prefab whole data center from building structure to core systems

Interior Prefabrication DC（IPD：install core modules in the pre-built shell

Containerized Prefabrication DC（CPD：infrastructure in containers

What markets do you serve?

BRIGHTRAY is deeply rooted in the APAC market and is now expanding into the U.S. and Middle East markets.

What challenges does the global digital infrastructure industry face today?

• Speed vs. Quality: Traditional construction methods take 2-3 years per project, yet AI and cloud demand deployment in months—not years.
• Sustainability Pressure: Data centers are energy-intensive, and global net-zero targets require radical efficiency improvements.
• Scalability Constraints: Supply chain bottlenecks, skilled labor shortages, and site limitations hinder rapid expansion.

How is BRIGHTRAY adapting to these challenges?

• Prefabrication Innovation: Our proprietary solutions (FPD, IPD, CPD) shift construction from on-site to factory-controlled environments, slashing timelines by up to 70%.
• Speed Records: We’ve proven our model with MY-01 (20MW in 8 months) and MY-02 (50MW in 6 months) —landmark projects in Malaysia that set new industry speed benchmarks and demonstrate BRIGHTRAY’s leadership in powering Asia Pacific’s rapidly growing digital hubs.
• Global-Ready Design: Our solutions are engineered for “global adaptability,” enabling rapid deployment across diverse environments with consistent quality.

What are BRIGHTRAY’s key differentiators?

• Proven Speed: 6-month delivery for 50MW capacity—unprecedented in the industry.
• End-to-End Expertise: Our team brings 10 years across the full lifecycle—design, construction, operations.
• Sustainability by Design: Prefabrication reduces on-site waste, carbon footprint, and energy consumption.
• Three Flexible Solutions: FPD (full prefab), IPD (interior prefab), CPD (containerized)—tailored to client needs.
• Global Vision, Local Roots: Deep APAC expertise, now expanding into U.S. and Middle East markets.

What can we expect to see/hear from BRIGHTRAY in the future?  

• Global Market Expansion: Following our strong foundation in APAC, we are actively entering the U.S. and Middle East markets. Expect announcements on new partnerships, project deployments, and local operations in these key regions.
• Next-Generation Prefabrication Solutions: We are continuously evolving our proprietary FPD, IPD, and CPD solutions to support higher densities and greater energy efficiency—purpose-built for the AI era’s demanding workloads.
• New Project Milestones: Building on our Malaysia success (MY-01: 20MW/8 months; MY-02: 50MW/6 months), we will unveil additional record-breaking deployments that further compress timelines while scaling capacity.

What upcoming industry events will you be attending? 

BRIGHTRAY will be attending Nvidia GTC in San Jose.

Do you have any recent news you would like us to highlight?

BRIGHTRAY breaks record by completing data center in 8 months.

Where can our readers learn more about BRIGHTRAY?  

You can learn more about us on our official website, www.brightraydc.com, or on our LinkedIn.

How can our readers contact BRIGHTRAY? 

You can contact us at marketing@brightraydc.com.

# # #

About BRIGHTRAY

BRIGHTRAY is redefining data center delivery through its pioneering prefabrication solutions. As hyperscale demand surges and speed-to-deployment becomes a decisive competitive edge, BRIGHTRAY empowers its clients to bring high-standard, scalable infrastructure online in just months, dramatically compressing timelines, reducing execution risk, and unlocking faster returns. The BRIGHTRAY team, comprising professionals with over 10 years of data center experience and led by executives with over 20 years of industry leadership, has collectively delivered hundreds of data center projects. The team has built end-to-end capabilities across the full lifecycle—from design and construction to operations—and leverages this deep expertise to pioneer innovative prefabricated data center solutions: Full Prefabrication Data Center (FPD), Interior Prefabrication Data Center (IPD), and Containerized Prefabrication Data Center (CPD). Each solution is engineered around three core principles—speed, resilience, and global adaptability to enable seamless deployment across diverse environments.

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.

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The post Company Profile: BRIGHTRAY’s Prefabrication Strategy for the AI Era appeared first on Data Center POST.

Originally posted on 1547realty.

AI and accelerated computing are reshaping expectations for data center infrastructure, and that shift is especially visible inside carrier hotel environments. Research from McKinsey notes that average rack power densities have more than doubled in two years, rising from 8 kilowatts to 17 kilowatts, with projections reaching 30 kilowatts per rack by 2027. Carrier hotels have long served as central meeting points for carriers, content providers, and enterprises, delivering dense interconnection in the heart of major metros. As fifteenfortyseven Critical Systems Realty (1547) has outlined in its connectivity hubs blog, these buildings keep communities and businesses online by concentrating networks and cloud on-ramps in a single, neutral location. For 1547, the focus is evolving these hubs to host modern AI workloads without compromising the connectivity advantages that make them essential.

A Shifting Infrastructure Reality

Carrier hotels were not originally built for AI. Historically, these facilities centered on abundant fiber, building-level power resilience, and space for many carriers to interconnect, with typical cabinet deployments remaining within just a few kilowatts. Dgtl Infra describes carrier hotels as highly interconnected urban facilities where carriers, cloud providers, and enterprises converge to exchange traffic and access key services. Modern GPU-based systems have pushed power density requirements into the tens of kilowatts, with infrastructure manufacturers such as Vertiv pointing to configurations exceeding 100 kilowatts per rack in advanced AI and high-performance computing environments. Instead of asking how much floor space is available, customers now want to know how much usable power can be delivered to each rack and how the facility will manage the resulting heat.

Why Increasing Power Density Creates Unique Challenges for Carrier Hotels

The same characteristics that define carrier hotels also introduce constraints that greenfield campuses do not face. Many occupy historic or mixed-use buildings in dense metro cores, where increasing utility capacity requires coordination with local utilities, municipalities, and building ownership. 1547’s Pittock Block in Portland illustrates this directly, with a century-old downtown landmark transformed into a modern carrier hotel and data center. Cooling presents a parallel challenge. Traditional air-cooled systems adequate for network gear and standard compute begin to struggle as rack densities climb, and McKinsey projects a potential supply deficit by 2030, driven by AI-ready capacity requirements that current infrastructure was not designed to meet.

To continue reading, please click here.

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At Metro Connect USA 2026, held February 22-25 in Fort Lauderdale, Marc Ganzi, Chief Executive Officer of DigitalBridge, delivered a keynote outlining how artificial intelligence is reshaping the digital infrastructure industry. In his address, “Digital Infra 3.0: Building the AI Industrial Revolution,” Ganzi described how the sector is evolving from a connectivity-focused market into a broader ecosystem that includes data centers, fiber networks, edge computing, and energy infrastructure.

Ganzi emphasized that AI has moved beyond hype and is beginning to generate measurable outcomes across industries. While much of the public discussion focuses on applications and large language models, he noted that the true monetization of AI will occur through enterprise and industrial use cases. Manufacturing, agriculture, healthcare, and transportation are already integrating AI-driven automation, robotics, and predictive analytics to improve productivity and efficiency.

These developments rely on a layered infrastructure environment. Hyperscale facilities train AI models, while edge data centers support inferencing workloads closer to where data is used. Fiber networks provide the low-latency connectivity required to move massive volumes of data between locations, and wireless systems connect devices and sensors in the physical world. Beneath all of these components sits an increasingly critical factor: power.

Power availability was a central theme of Ganzi’s keynote. As AI workloads grow, electricity demand is rising faster than grid capacity can keep pace. The digital infrastructure industry is now leasing significantly more power than the grid can bring online each year, creating a widening gap between supply and demand. As a result, developers are increasingly operating as energy strategists, exploring diversified energy approaches that may include microgrids, battery storage, solar, wind, and natural gas generation.

The search for reliable power is also influencing where new infrastructure is built. While traditional hubs such as Northern Virginia remain central to the industry, developers are exploring additional markets where grid access and energy availability make large-scale AI deployments possible. In many cases, power availability has become the deciding factor in site selection.

Despite the focus on energy, Ganzi reminded the audience that connectivity remains essential to the AI economy. The ability to move enormous amounts of data across networks continues to depend on high-capacity fiber infrastructure and low-latency connectivity. Even as AI advances in software and hardware, the underlying network infrastructure remains fundamental.

Ganzi also described the evolution of AI infrastructure in phases. The industry has moved through the early stage of training large language models and is now entering a period where inferencing and edge deployments are expanding. The next stage will involve integrating AI directly into physical environments, where intelligent systems control machines, robotics, and automated processes across multiple industries.

As the sector expands, developers face growing challenges that include power constraints, permitting delays, supply chain pressures, water usage concerns, and increased scrutiny from investors. Ganzi stressed that success will depend on operational discipline, strong customer relationships, and the ability to deliver infrastructure projects reliably and on schedule.

Ultimately, he framed the current moment as the beginning of Digital Infra 3.0, a phase in which digital infrastructure converges with traditional infrastructure to support the AI economy. As AI adoption accelerates, the companies that successfully combine power, connectivity, and compute will play a defining role in building the foundation for the next era of global digital infrastructure.

The discussion around digital infrastructure, connectivity, and AI will continue at the next major Capacity event, International Telecoms Week (ITW) in Washington, D.C., May 18-21, 2026.

To learn more about upcoming events in the Capacity Media portfolio, visit www.capacitymedia.com/events.

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The Middle East has long been described as a geographic bridge connecting Europe, Asia, and Africa. Today, however, the region is becoming far more than a transit corridor. At Capacity Middle East 2026 and Datacloud Middle East 2026, held in Dubai, February 10-12, 2026, industry leaders explored how the region is rapidly evolving into a major destination for digital infrastructure investment. Telecom operators, data center developers, investors, and technology providers gathered to discuss the next phase of growth, which includes expanding connectivity routes, scaling AI-ready data centers, and strengthening the interconnection ecosystems needed to support the region’s digital economy.

The Middle East’s Connectivity Role Is Expanding

For many years, global connectivity discussions framed the Middle East primarily as a transit hub linking international markets. Speakers at Capacity Middle East emphasized that this narrative is evolving as regional internet traffic, enterprise workloads, and cloud adoption continue to grow across the Middle East. Infrastructure strategies are increasingly focused on supporting demand generated within the region itself rather than simply facilitating global transit. This shift is encouraging greater investment in fiber interconnection between data center clusters, cross-border terrestrial routes linking neighboring markets, and internet exchange points that allow regional traffic to remain within the region. As the Middle East’s digital economy expands, more data is being generated and consumed locally, reinforcing the need for robust regional infrastructure.

Hybrid Connectivity Routes Are Gaining Momentum

Another major topic throughout Capacity Middle East was the development of hybrid connectivity routes that combine subsea cables with terrestrial fiber infrastructure. While subsea cables remain the backbone of global connectivity, geopolitical risks and congestion along traditional Red Sea routes have highlighted the need for diversified network paths between Asia and Europe. Operators are increasingly exploring alternative corridors that incorporate land-based routes across regional markets. Industry leaders noted that deploying these hybrid routes is not simply an engineering challenge. Subsea and terrestrial networks operate under different economic models and regulatory frameworks, meaning coordination across multiple jurisdictions will be required to ensure these routes remain commercially viable. Despite those complexities, hybrid infrastructure is expected to play an important role in strengthening global connectivity resilience.

Data Center Development Is Accelerating Across the Region

At Datacloud Middle East, much of the conversation centered on the region’s rapidly expanding data center ecosystem. The Middle East offers several structural advantages that are attracting global infrastructure investment, including competitive energy pricing, available land for hyperscale campuses, strong sovereign investment funds, and coordinated national digital strategies. Market insights shared during the event indicated that vacancy rates across regional data center markets remain low while a significant portion of new capacity is already pre-leased before completion. Although most existing capacity remains concentrated in the United Arab Emirates and Saudi Arabia, emerging markets such as Oman and Jordan are also advancing national initiatives designed to attract new digital infrastructure development and diversify the region’s data center footprint.

AI Is Reshaping Data Center Design

Artificial intelligence infrastructure requirements were a central theme at Datacloud Middle East. Traditional enterprise data centers typically operate at densities between 10 and 20 kilowatts per rack, but AI training clusters are already pushing beyond 100 kilowatts per rack, creating new challenges for power delivery, cooling strategies, and facility design. Because large-scale data center projects often require 18 to 24 months to build, developers must make long-term infrastructure decisions with limited visibility into future workload requirements. As a result, many operators are shifting toward flexible data center architectures capable of supporting both traditional enterprise workloads and high-density AI environments. Rather than designing facilities for a single predictable future state, the industry is increasingly prioritizing adaptability.

Industry Leaders Highlight the Region’s Momentum

Several speakers provided important insights into the trends shaping the Middle East’s digital infrastructure ecosystem. Johan Nilerud, Chief Strategy Officer at Khazna Data Centers, discussed how hyperscale demand and national digital initiatives are accelerating the development of large-scale data center campuses across the Gulf. Karim Benkirane, Chief Commercial Officer at du, highlighted the role telecommunications providers play in enabling cloud adoption and expanding regional connectivity capacity. Mehdi Paryavi, Chairman of the International Data Center Authority, explored how national initiatives such as Oman’s Digital Triangle are positioning emerging markets to compete for future AI and cloud infrastructure investment. Tahir Gok, MENA Lead at datacenterHawk, shared market insights showing continued demand for colocation capacity and strong growth across the region’s key digital hubs. Julian Barratt-Due, Managing Director at KKR, also discussed the growing interest from international investors seeking opportunities to participate in the Middle East’s digital infrastructure expansion alongside sovereign wealth funds.

Interconnection Will Define the Next Phase

A consistent theme across both conferences was the critical importance of interconnection. Data centers, cloud platforms, AI infrastructure, and enterprise networks all rely on strong connectivity ecosystems. Without robust interconnection between facilities, internet exchanges, and regional fiber routes, the full value of new infrastructure investments cannot be realized. Industry leaders emphasized that the next phase of digital infrastructure development in the Middle East will require dense fiber ecosystems, carrier-neutral exchanges, and strong regional connectivity frameworks that allow traffic to move efficiently across markets.

A New Era for Middle East Digital Infrastructure

Capacity Middle East and Datacloud Middle East demonstrated how quickly the region’s infrastructure landscape is evolving. Supported by AI demand, sovereign investment, and coordinated national strategies, the Middle East is rapidly expanding its connectivity and data center capacity. The region’s role in the global digital ecosystem is no longer limited to bridging continents. Instead, it is emerging as a strategic hub where infrastructure is being built to support both global traffic flows and a rapidly growing regional digital economy. As investment continues to accelerate, the conversations taking place in Dubai suggest that the Middle East will remain a central focus of digital infrastructure development in the years ahead.

The next Capacity event will be International Telecoms Week (ITW) in Washington, D.C., May 18-21, 2026.

To learn more about upcoming events in the Capacity Media portfolio, visit www.capacitymedia.com/events.

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AI spending is accelerating at a pace most enterprise budgets simply can’t match. While IT leaders are under pressure to deliver transformative AI capabilities, their capital budgets aren’t growing at the same rate as these AI ambitions. This mismatch is forcing difficult trade-offs: delayed projects, stretching aging infrastructure beyond its intended lifecycle, and diverting funding from other critical initiatives.

But there is another option. Increasingly, IT leaders are turning to technology leasing as a savvy strategy to help expedite AI adoption without sacrificing operational agility or financial liquidity.

AI: Thinking Through the Dollars and Sense

From my vantage point, working closely with IT leaders across industries, I hear the lament. AI infrastructure is expensive and highly concentrated, particularly GPU-based compute power. A single GPU cluster designed to support large-scale AI workloads can cost hundreds of thousands to millions. For enterprise-wide deployments, total data center investments can easily reach $150 million and as much as $500 million.

For mid-tier enterprises, challenges are even greater, as many lack the balance-sheet strength to secure traditional credit for such large capital expenditures. Some resort to private equity or high-interest lenders. But even those who can afford to purchase the infrastructure outright are frustrated by the pace of AI innovation; and the risk of technology becoming quickly outdated or obsolete.

For determined IT leaders, the question is not whether to invest in AI infrastructure, but how to fund it without compromising the broader IT roadmap. This is where the financing strategy becomes just as important as the technology strategy.

IT leasing eases these pressures in several critical ways:

• Minimizing upfront costs. Traditional purchasing requires a massive outlay of capital, sometimes forcing companies to scale back or winnow down the scope of projects despite urgent demand. Leasing converts that one-time expense into predictable monthly payments. Instead of committing $50 million upfront, an organization can structure payments over time, freeing capital for additional initiatives and allowing multiple AI projects to move forward simultaneously.
• Enhancing flexibility and reducing financial risk. Purchased technology sits on the balance sheet and depreciates over a fixed period. If business needs shift or the organization upgrades early, it can trigger book losses. Leasing – when structured properly – can classify equipment as an operating expense, keeping it off the balance sheet and enabling companies to pivot more easily without the burden of carrying these assets.

Lease the Entire AI Stack, Not Just the Hardware

IT leaders recognize today’s AI deployments extend far beyond servers. Enterprises are leasing high-performance GPU servers optimized for AI model training and inference, along with high-speed networking equipment, enterprise storage systems, integrated “rack and roll” data center solutions, firewalls, and AI-specific software.

Maintenance contracts, security tools, and embedded applications can all be incorporated into a single lease structure.

This bundling delivers administrative and compliance benefits. Hardware typically carries a residual value often 10–15% below purchase cost, amortized across the lease term. Software licenses and other “soft costs” are included in payments and expire at term end, eliminating resale complications. Clients are responsible only for the hardware at lease completion, simplifying compliance and ensuring security updates, patches, and licenses remain current throughout the lifecycle.

Combat Obsolescence Before It Becomes a Liability

One of the most common concerns I hear from executives is technology obsolescence. And given the pace of AI, where innovation cycles are measured in months, not years, that concern is justified.

Leasing naturally enforces a rigor and discipline for countering obsolescence. A three- or four-year term creates a defined decision point: extend, buy out or upgrade the technology. This prevents the “set it and forget it” ownership mindset that often leads to aging, unsupported systems and expensive, reactive refresh cycles. In AI environments, delaying upgrades can multiply total costs through inefficiencies and lost competitive advantage.

Leasing is a Budget Multiplier

Looking ahead to 2026 and beyond, IT leaders must think differently about capital allocation. No one can predict what the AI landscape will look like in three years. Owning large volumes of rapidly depreciating infrastructure can limit strategic agility.

Leaders must also factor in the full lifecycle cost of AI infrastructure, which includes equipment refreshes, secure data wiping, asset disposition, and regulatory compliance. These factors carry operational and financial burdens when assets are owned outright.

The most important priority today is building a strategy that enables AI adoption with minimal upfront cost and maximum flexibility. Leasing can act as a budget multiplier. Instead of exhausting capital on one large acquisition, organizations can deploy that same funding across predictable monthly payments, preserving liquidity while expanding total project capacity. In doing so, IT leaders maintain momentum across their complete technology roadmap, ensuring AI transformation doesn’t come at the expense of operational resilience.

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About the Author

Frank Sommers brings 30 years of experience in the IT leasing industry, working closely with global enterprise organizations to help them modernize infrastructure while preserving capital and accelerating technology adoption. Known for consistently exceeding sales targets, Frank has also developed and led numerous successful vendor financing programs in partnership with major resellers, creating flexible acquisition models that support complex IT environments. His deep expertise in IT lifecycle management, financing strategies, and enterprise procurement has made him a trusted advisor across the industry. A former collegiate soccer player at Cal Poly San Luis Obispo, Frank brings the same competitiveness and teamwork to every client relationship.

The post Desperate to Fund AI? Leasing May Be the Smartest Move IT Leaders Make in 2026 appeared first on Data Center POST.

Duos Technologies Group, Inc. (Nasdaq: DUOT), a leading provider of adaptive, modular, and scalable Edge Data Center (EDC) solutions, has closed its underwritten public offering of 8,666,666 shares of common stock, generating approximately $65 million in gross proceeds. The offering included participation from several of the Company’s largest existing institutional shareholders alongside new institutional investors, closing on March 2, 2026.

“This financing represents a strong vote of confidence from both new and existing investors, as well as our new strategic partner Hydra Host, in Duos’ leadership, strategy and growth trajectory,” said Doug Recker, incoming Chief Executive Officer. “With this capital now secured, we can pursue our $200 million LOI, while accelerating the commercialization of our high-power EDC business model. We are expanding our Edge AI platform, advancing hyperscaler-aligned AI infrastructure initiatives, and positioning the Company to scale toward our 2026 objectives. Demand for distributed AI compute and GPU capacity continues to build, and we believe Duos is strategically positioned to convert that demand into sustained revenue growth and long-term shareholder value.”

The financing directly positions Duos to pursue its approximately $200 million NVIDIA GPU hosting letter of intent with Hydra Host, with net proceeds directed toward expanding and commercializing the Company’s high-power Edge Data Center business, as well as working capital and general corporate purposes. Titan Partners, a division of American Capital Partners, acted as sole bookrunner for the offering.

To learn more about Duos Technologies Group, Inc., visit www.duostechnologies.com.

The post Duos Technologies Closes $65 Million Public Offering to Fuel Edge AI Expansion appeared first on Data Center POST.

Originally posted on CMOtech.

Every year on International Women’s Day, we celebrate women who have broken barriers, led teams, built businesses, and shaped industries. That recognition is important. However,  it only tells part of the story. What truly advances organizations and sectors isn’t simply the presence of women at the table, but how leadership functions once we’re there.

Leadership is not defined by intent or visibility alone; it is measured by accountability, consistency, and what actually gets done. Though, what truly advances organizations and sectors isn’t simply the presence of women at the table, it’s how leadership functions once we are there and after the meeting ends.

In today’s technology-driven landscape, the pace of change is relentless and the margin for execution errors is thin. Vision may get you invited into the room, but follow-through is what keeps you there.

A critical and often misunderstood aspect of leadership is who we are actually serving. While organizations exist to serve clients and customers, leaders are not successful by focusing outward alone. Strong leaders understand that their first responsibility is to serve their teams by providing them with clarity, structure, and support so that together they can serve clients well.

When leaders fail to support their teams with clear expectations, consistent communication, and accountability, the impact eventually reaches clients. Internal breakdowns always surface externally. Leadership is not about absorbing all responsibility personally; it’s about enabling others to perform at their best.

Accountability needs to be visible every day, not just during performance reviews. Technology offers no shortage of tools to support this: shared calendars, automated reminders, project management platforms, and real-time dashboards. These tools are not optional accessories. In modern organizations, managing commitments with discipline is foundational to trust.

When commitments aren’t kept, it doesn’t just slow progress, it erodes confidence. Across industries, leaders who consistently miss deadlines or fail to communicate reveal a deeper issue: a gap between how work is described and how it is executed. In an era of transparency and digital workflows, “I forgot” is no longer a credible explanation. Leadership requires intentionality.

To continue reading, please click here.

The post Beyond Visibility: How True Leadership Really Works appeared first on Data Center POST.

By Anoop Thulaseedas, Associate Director, Solutions & Consulting at Bristlecone.

Industries across technology, semiconductors, infrastructure, energy, and advanced manufacturing are entering a sustained period of structural scarcity. Explosive growth in AI workloads, electrification, defense modernization, and industrial expansion has outpaced the scaling capacity of upstream ecosystems. In this environment, planning models built on forecast accuracy and assumed supply elasticity are no longer sufficient.

Scarcity is increasingly structural in critical industrial ecosystems.

Competitive advantage now depends on recognizing supply constraints as the governing reality of the enterprise. Capacity availability, not demand projection, determines portfolio sequencing, commercial commitments, capital allocation, and revenue timing.

This shift requires rethinking planning itself. Rather than predicting demand and expecting supply to respond, organizations must deliberately govern constrained capacity across interconnected production and deployment layers.

This paper introduces a scarcity-native operating model in which allocation governance, constraint visibility, and cross-layer orchestration replace forecast-centric optimization. While illustrated through AI infrastructure ecosystems, the underlying logic applies broadly across any multi-constraint industrial environment.

Scarcity as a Multi-Constraint Ecosystem

Modern scarcity rarely originates from a single component or isolated bottleneck. Instead, effective supply is governed by a chain of constraints distributed across interconnected production and deployment layers. These layers span geographies, capital cycles, and technical disciplines — from semiconductor fabs to packaging plants, specialty materials facilities, infrastructure sites, and commissioning environments.

Scarcity today is not confined to procurement pipelines or logistics networks. It emerges across an integrated physical system in which each layer possesses independent throughput ceilings, capital intensity, and scaling timelines. Expanding capacity at one node without synchronizing adjacent constraints redistributes bottlenecks downstream.

Scarcity must therefore be understood as a layered physical system rather than an isolated material shortage. While illustrated through semiconductor and data center ecosystems, the same multi-constraint logic applies to energy systems, transportation networks, and advanced manufacturing environments.

The Constraint Chain

Layer 1: Core Component Manufacturing

This layer resides within semiconductor fabrication facilities operated by memory and logic OEMs. It encompasses wafer capacity, yield variability, production allocation decisions, and process throughput limitations. In AI ecosystems, this includes HBM memory production and the output of accelerator silicon. Cleanroom capacity, tool availability, yield ramp maturity and throughput define the production ceiling.

Layer 2: Integration and Advanced Packaging

Following fabrication, components must be integrated into deployable modules within advanced packaging and OSAT facilities. High-precision stacking, bonding technologies, and thermal integration processes convert discrete dies into functional assemblies. Packaging throughput frequently becomes the next gating constraint, independent of wafer supply, due to equipment intensity, cycle-time sensitivity, and specialized labor limitations.

Layer 3: Substrates and Interposers

Specialized substrate and interposer manufacturing is conducted in a limited number of precision materials facilities. These components form the physical interconnect between the compute, memory, and power-delivery layers. Long qualification cycles, limited supplier redundancy, and fine-line manufacturing complexity create structural bottlenecks that often surface only after upstream output expands.

Layer 4: Infrastructure Readiness

Even when integrated hardware is available, deployment depends on the physical site’s readiness. Data center campuses and supporting electrical infrastructure determine installation viability. Rack-level power density, cooling architecture, transformers, switchgear, and grid interconnections govern whether hardware can be activated. These constraints frequently delay monetization despite upstream production success.

Layer 5: Qualification and Commissioning

Final validation, integration testing, and cluster bring-up occur within integration labs and on-site commissioning environments. Skilled engineering capacity, testing infrastructure, and activation throughput determine how quickly deployed assets become operational and revenue-generating.

Orchestrating the Full Constraint System

Optimizing any single layer in isolation produces limited value. Increasing wafer output without packaging capacity, accelerating packaging without infrastructure readiness, or expanding infrastructure without commissioning throughput results in stranded capital and delayed revenue realization.

Value creation depends on synchronized decision-making across the entire constraint chain — from fabrication to live deployment.

Scarcity, therefore, represents an enterprise operating model challenge spanning Planning, Sourcing, Engineering, Infrastructure, and Finance. It cannot be managed as a downstream supply execution issue alone.

Core Differentiators of Scarcity-Native Operating Models

Scarcity-native operating models are defined by structural shifts in how planning is conducted and governed.

1. Scarcity-Native Planning vs Traditional Planning

Illustrative Case: Automotive Semiconductor Reallocation

During the 2020–2022 semiconductor shortage, several automotive manufacturers confronted an immediate collapse of forecast-driven production logic. Rather than waiting for supply normalization, some shifted to allocation-driven governance.

Ford Motor Company provides a clear illustration. With chip supply constrained, the company prioritized high-margin vehicles and new product launches over lower-margin configurations. Production schedules were aligned to confirmed semiconductor availability rather than unconstrained dealer forecasts. Non-essential features were temporarily removed from certain models to maximize yield from scarce components.

The result was not merely damage control. By deliberately allocating constrained inputs toward strategic priorities, Ford expanded its order bank and preserved margin performance in the face of systemic supply tightness.

This behavior reflects entitlement-based baselining and value-optimized deployment sequencing — core characteristics of scarcity-native operating models.

• Entitlement-Based Planning Baselines: Planning begins with confirmed supplier allocations, contracted capacity reservations, infrastructure availability, and commissioning throughput—not unconstrained demand forecasts. These entitlements define deployable reality.
• Allocation-Driven Governance: Explicit allocation logic determines how constrained capacity is distributed across programs, regions, and customers. This replaces reactive firefighting with structured prioritization.
• Value-Optimized Deployment Sequencing: Deployment decisions prioritize revenue realization, utilization efficiency, strategic commitments, and long-term platform positioning — not simply maximizing unit output.
• Continuous Replanning Cadence: Planning operates dynamically. As supplier commitments shift, packaging schedules move, infrastructure readiness evolves, and commissioning throughput fluctuates, allocation decisions are updated in near real time.

In constrained ecosystems, planning becomes less about predicting demand and more about governing capacity.

2. Internal Competition and Portfolio Trade-Off Management

Scarcity does not only constrain external supply. It creates internal competition for limited deployment capacity.

In infrastructure-intensive environments, multiple initiatives frequently compete for the same constrained resources — fabrication allocations, packaging throughput, power envelopes, commissioning capacity, or site readiness. Without centralized governance, these programs generate fragmented demand signals that dilute negotiating leverage, misalign capital sequencing, and create suboptimal capacity utilization.

Scarcity-native organizations formalize portfolio-level prioritization tied explicitly to constrained supply envelopes. Executive trade-off forums align strategic objectives with physical deployment ceilings. Capital investments, infrastructure readiness and customer commitments are sequenced deliberately rather than pursued in parallel under optimistic capacity assumptions.

Allocation decisions are evaluated across explicit dimensions — financial impact, reliability, service performance and long-term strategic positioning — ensuring scarce capacity is deployed where it creates the highest enterprise value rather than the loudest internal demand.

3. Sourcing Embedded Into Planning Decisions

In constrained ecosystems, sourcing cannot function as a downstream procurement activity. It becomes a structural input into planning itself.

Leading organizations embed supplier allocation commitments, capacity reservation agreements and qualification timelines directly into deployment roadmaps. Confirmed supplier envelopes define planning baselines. Tier-2 and Tier-3 visibility informs risk exposure and contingency design. Power equipment lead times and infrastructure component availability are treated as governing constraints rather than execution afterthoughts.

This integration shifts sourcing from transactional purchasing toward capacity governance. Structured forward visibility and commitment mechanisms provide suppliers with the economic rationale to sustain constrained production capability, reducing volatility amplification across the ecosystem.

When sourcing is embedded into planning, deployable capacity becomes a coordinated outcome rather than a negotiated surprise.

4. Engineering as a Practical Scarcity Lever

While many upstream constraints remain outside direct operational control, engineering decisions materially influence how scarcity is absorbed.

Scarcity-native organizations emphasize platform standardization to reduce component fragmentation and dependency on narrow configurations. Design-for-availability principles favor widely supported architectures. Modular infrastructure design enables flexible sequencing of deployment. Qualification of alternate equipment SKUs and suppliers increases interchangeability where feasible.

These choices do not eliminate structural constraints. They expand optionality within them.

Engineering flexibility reduces concentration risk, improves interchangeability and increases the organization’s ability to realign deployment in response to shifting constraint patterns. In constrained environments, architecture decisions become strategic levers of capacity governance.

Short-Term vs. Medium-Term Scarcity Response

Scarcity response requires distinct behaviors across time horizons. Scarcity-native operating models deliberately differentiate between near-term stabilization of constrained capacity and medium-term expansion of structural optionality.

Short-Term (0–90 Days): Stabilize Utilization

• Formal allocation governance across competing programs
• Rapid replanning cycles incorporating real-time supplier signals
• Prioritization of high-value customers and contracted commitments
• Cross-functional executive decision forums

The objective is to absorb volatility without cascading disruption.

Medium-Term (3–12 Months): Expand Optionality

• Supplier diversification and alternate sourcing paths
• Capacity reservation agreements
• Accelerated qualification of alternate SKUs and components
• Platform standardization and modular infrastructure design
• Multi-constraint scenario modeling

The objective shifts from stabilization to structural resilience within constrained ecosystems.

Operationalizing Scarcity Through S&OP and S&OE

Traditional planning architectures separate Sales & Operations Planning (S&OP) from Sales & Operations Execution (S&OE). Under structural scarcity, this separation breaks down.

Instead, S&OP and S&OE function as a closed-loop control system.

S&OP — Policy and Governance

S&OP defines allocation policy:

• Establishes entitlement baselines
• Sets guardrails based on confirmed supply envelopes
• Aligns portfolio priorities with financial and strategic tradeoffs
• Determines how scarcity is distributed across programs and regions

S&OP governs how limited capacity should be used.

S&OE — Dynamic Allocation

S&OE continuously adjusts allocation decisions:

• Reallocates constrained supply as conditions evolve
• Adjusts deployment cadence based on supplier commitments and readiness
• Protects utilization, service levels, and revenue realization

S&OE governs how limited capacity is used today.

 The Planning Logic Shift

Traditional logic:  Plan → Execute

Scarcity-native logic:  Policy → Allocate → Learn → Re-Decide

Execution feedback updates governance decisions. Governance decisions reshape execution priorities. Planning becomes a continuous decision cycle rather than a periodic balancing exercise.

This reframes planning from forecast management into enterprise-level capacity governance.

Conclusion: From Forecast Accuracy to Capacity Governance

Structural scarcity is redefining operational excellence. In constrained ecosystems, supply availability, shaped by interconnected physical bottlenecks, determines what can be delivered, when revenue is realized, and where competitive advantage accrues.

Organizations that succeed are not those that eliminate constraints, but those that govern them deliberately. Scarcity-native operating models shift the enterprise mindset from optimization to orchestration: allocating limited capacity where it creates the greatest strategic and financial impact.

Although illustrated through AI infrastructure, the same logic applies across power systems, advanced manufacturing components, transportation capacity, critical materials, and skilled labor markets. Constraint chains are becoming the defining architecture of modern industry.

The transition to scarcity-native operating models requires deliberate organizational design – from governance structures and measurement frameworks to replanning cadences and cross-functional decision rights. Organizations beginning this journey benefit from structured diagnostic assessments that map current constraint visibility, allocation governance maturity, and planning integration gaps against the target operating model.

In a constrained world, performance is no longer determined by how accurately demand is forecasted. It is determined by how effectively access to limited capacity is governed.

The post Scarcity-Native Planning: Operating Models for Constrained Ecosystems appeared first on Data Center POST.

Originally posted on Sabey Data Centers.

Following the successful full lease-up of our first data center at our Round Rock, TX campus, we wanted to share a brief construction update on SDC AustinBuilding B.
Construction is now well underway, with the primary concrete structure rising and vertical construction clearly progressing. The project is tracking to schedule, and site activity has ramped up significantly as we move through early structural milestones.

Building B Highlights:

• 54MW of total capacity, powered by an onsite substation
• Fully secured utility power for the entire facility
• Liquid cooling optimized design to support next-generation workloads
• 6 data halls, each offering 30,000 SF of space

You can view a short video of our construction progress here.

The post SDC Austin Building B Progress Q1 2026 appeared first on Data Center POST.

Rob Thornton, President & CEO, International District Energy Association (IDEA)

As the number of data centers grows, so do concerns about location, power access, and grid capacity, especially as AI and cloud computing drive surging electricity demand. Yet, data centers hold an unexpected solution: the waste heat they generate can be harnessed for community benefit.

Captured through district energy systems, this heat can be transformed into a valuable community resource that provides low-carbon warmth, improves grid stability, and redefines data centers as energy partners.

The Power Behind the Numbers

In 2023, data centers accounted for roughly 4.4% of total U.S. electricity use, a share projected to rise to as much as 12% by 2028. As utilities and developers scramble to expand clean generation and transmission, waste heat reuse offers an immediate, scalable way to reduce carbon intensity and ease grid stress.

How Heat Reuse Works

Servers generate heat, which can be captured and directed into district energy networks—insulated pipes transporting hot or chilled water—supplying heat to nearby buildings. This approach reduces the electricity needed for heating and cooling, improving overall efficiency and cutting emissions. In essence, the data center becomes part of a shared local energy ecosystem.

Some add combined heat and power (CHP) systems that produce electricity and heat simultaneously. CHP can increase efficiency for large or urban centers. Two deployment models stand out:

• Urban data centers (10–20 MW): Linked to city energy networks for efficient heat export.
• Large, remote sites (100 MW–1 GW): Feature CHP-based microgrids to serve multiple facilities.

Cities Leading the Way

Areas with dense data center development, such as Northern Virginia’s “Data Center Alley,” are exploring new district heating networks to link excess data center heat with community energy needs. Several pioneering projects in Canada illustrate the potential.

• Markham, Ontario: An Equinix data center retrofitted for heat recovery now warms local condos, a university, schools, and recreation facilities, creating community benefits.
• Toronto, Ontario: Enwave Energy connects Telehouse Canada’s data centers to its system using deep-lake water cooling and waste-heat recovery. This model reduces resource use, enhances cooling, and supports city climate goals.

From Grid Burden to Energy Partner

Heat reuse fundamentally shifts the purpose of data centers from major power consumers to vital contributors in a circular energy economy. By sharing surplus heat, these facilities support decarbonization, reliability, and resilience, and these solutions can be achieved faster than large-scale infrastructure investments.

How Operators Can Get Started

For operators and planners evaluating heat reuse, three clear steps can set the foundation for success:

• First, thoroughly assess the site-level heat export potential for both new builds and retrofits by analyzing available waste heat, proximity to potential heat users, and compatibility with local district energy infrastructure.
• Second, proactively engage municipalities and district energy providers early. This means initiating discussions to align on infrastructure design needs, available incentives, and long-term energy offtake agreements.
• Third, explore hybrid system options—such as pairing CHP, thermal storage, and advanced cooling technologies—for maximum operational flexibility, especially when grid interconnections may be delayed. Evaluate each technology’s potential to complement site-specific requirements and constraints.

As the data economy grows, speed, sustainability, and resilience must move forward together. Waste heat has the potential to be much more than a byproduct; it can become a resource that positions data centers as active agents in community well-being. In the era of AI, shared energy is truly smart energy.

# # #

About the Author:

Rob Thornton is President & CEO of the International District Energy Association (IDEA), a global nonprofit founded in 1909 that advocates for efficient, resilient, and sustainable district energy systems. Under his leadership, IDEA works with public and private partners worldwide to advance energy efficiency, decarbonization, and community-scale thermal networks.

The post From Server Heat to City Warmth: Data Centers’ Hidden Energy Advantage appeared first on Data Center POST.

Duos Technologies Group, Inc. (Nasdaq: DUOT), a leader in intelligent technologies and digital infrastructure, has signed a non-binding letter of intent (LOI) with Hydra Host to deploy a high-density NVIDIA GPU cluster for a leading global technology customer. The project supports a GPU-as-a-Service (GPUaaS) partnership expected to generate approximately $176 million in revenue over a 36-month term, with gross margins exceeding 80% and projected annual EBITDA of more than $40 million.

“We are thrilled to partner with the Duos team on this opportunity,” said Aaron Ginn, CEO and Co-Founder of Hydra Host. “Their ability to deliver immediate access to power combined with an industry-leading deployment speed makes them a standout in the market. We see significant runway ahead as we look to expand our collaboration around colocation and Duos’ High-Power EDC model, which we believe is purpose-built to address a market where demand for AI compute capacity is fundamentally outpacing the speed at which traditional data center supply can be delivered.”

Complementing this milestone, Duos has appointed Doug Recker as Chief Executive Officer, effective April 1, 2026, as the company accelerates its transformation into a focused Edge AI and digital infrastructure platform. Mr. Recker succeeds Chuck Ferry, who will continue to serve on the board of directors.

“This initial customer marks a pivotal step in accelerating the buildout of Duos Edge AI,” said Doug Recker, Chief Executive Officer. “We are now entering an exciting phase of execution, further reinforced by our recently announced LOI with Hydra Host, which underscores growing third-party demand for our distributed AI infrastructure model and validates the scalability of our platform. With secured power, rapid deployment capabilities, and expanding strategic partnerships, we believe Duos is well positioned to pursue high-value infrastructure opportunities. Our focus remains on disciplined expansion, capital-efficient growth, and delivering sustainable long-term value for our shareholders.”

Beyond GPUaaS revenue, the collaboration creates a pathway for approximately $25 million in incremental colocation revenue over the same term, validating Duos’ High-Power Edge Data Center (EDC) business line. The company has also signed a non-binding LOI for a ground lease in Iowa with access to up to 10MW of utility power, advancing its long-term goal of building up to 75MW of distributed capacity.

To learn more about Duos Technologies Group, Inc., visit www.duostechnologies.com.

The post Duos Technologies Signs ~$200M LOI and Appoints Doug Recker as CEO appeared first on Data Center POST.

CloudKleyer Frankfurt GmbH, a German IT service provider, has completed an international project involving the relocation of a client’s server infrastructure from data centers in Stockholm and London to Frankfurt am Main. The project was delivered as a fully managed turnkey solution under the coordination of the CloudKleyer team.

The data center-to-data center (DC-to-DC) migration required the safe transfer of active production equipment while preserving uninterrupted service availability. Acting as the sole responsible contractor, the company supervised all phases of the project — from initial preparation to the controlled commissioning of systems.

Project implementation stages

1. Structured planning and risk assessment
2. Professional shutdown of operating equipment
3. Secure transportation with full insurance coverage
4. Coordination of access and on-site logistics
5. Equipment placement (rack & stack), cabling and integration
6. Testing, verification of operability and controlled launch

Centralized coordination ensured synchronization of technical and logistical activities and reduced risks commonly associated with infrastructure relocation. The project was completed within the scheduled timeframe and complied with established data center standards and security requirements.

Company representatives observe a growing number of infrastructure modernization initiatives across Europe, as businesses relocate workloads to modern facilities to improve reliability, scalability and regulatory compliance.

CloudKleyer intends to further expand its infrastructure transformation services and continue supporting clients in both domestic and international migration projects.

Find more information here.

# # #

About CloudKleyer Frankfurt GmbH

CloudKleyer Frankfurt GmbH is an IT infrastructure provider with more than ten years of experience in the European data center market. The company offers colocation services, IT equipment rental, Remote Hands technical support, high-speed internet connectivity and direct connections to major cloud platforms.

The post CloudKleyer Frankfurt GmbH Announces Completion of Cross-Border IT Infrastructure Migration appeared first on Data Center POST.

By Bob Walicki, Ecolab Senior RD&E Program Leader

The rapid evolution of artificial intelligence has moved from a software trend to a massive physical infrastructure challenge. While headlines often focus on the gigawatt-scale builds of hyperscalers, a significant portion of the AI boom is occurring in the “mid-market” -enterprise data centers, regional colocation hubs, and edge facilities. For these small-to-mid-scale (SMS) operators, the challenge of hosting high-performance graphics processing units (GPUs) and AI accelerators exceeding thermal design powers of 1,000 watts is even more acute. Unlike hyperscalers with dedicated research teams, SMS players must find ways to adapt existing “brownfield” infrastructure to manage unprecedented heat without the luxury of starting from scratch.

The Mid-Market Liquid Cooling Transition

For decades, air cooling was the “flat and boring” standard for the computer centers found in banks, universities, and regional hosting firms. However, as rack densities climb from a traditional 5 kW toward 50 kW or even 100 kW, traditional air-conditioning methods are reaching a physical ceiling. In fact, 2026 is seeing a surge in retrofit activity as colocation sites struggle to let mixed densities coexist efficiently.

The primary hurdle for SMS operators is not just the cooling capacity itself, but the operational complexity and capital investment required for a liquid-cooled transition. Many operators are now moving toward integrated cooling platforms that bridge the building’s traditional chilled-water loop and the new high-density server racks.

The CDU as a Bridge for Existing Facilities

At the center of this shift is the Coolant Distribution Unit (CDU). For a mid-market operator, the CDU acts as a critical thermal “bridge.” A liquid-to-liquid CDU effectively isolates the facility’s existing water loop from the sensitive, high-value electronics via a secondary fluid network (SFN).

This isolation is particularly valuable for colocation and enterprise sites because it allows managers to precisely control the fluid chemistry, flow rate, and temperature for a specific “GPU-heavy” cluster without needing to overhaul the entire building’s plumbing. In-rack CDUs, in particular, offer targeted cooling with a smaller footprint and simplified deployment, making them ideal for the edge or regional high-density setups where floor space is at a premium.

Reliability Through Precision Chemistry

For smaller teams with fewer on-site cooling specialists, the coolant formulation itself becomes a strategic reliability factor. Standard water or traditional glycols often lack the long-term material compatibility required for modern direct-to-chip, where incompatible metals can trigger galvanic corrosion.

SMS operators are increasingly adopting next-generation coolants that match high-performance specifications while offering a lower carbon footprint. To manage these complex fluids, advanced telemetry – such as Ecolab’s 3D TRASAR™ technology – can now be built directly into smart CDUs. This “connected coolant” approach monitors pH, conductivity, and glycol concentration in real-time, allowing smaller teams to shift from reactive maintenance to proactive adjustments. By automating these checks, operators can extend maintenance intervals and significantly reduce the risk of early-life failures.

Stewardship as a Strategic Requirement

As data centers increasingly embed themselves in metro and suburban locations to support low-latency AI, they face rising community scrutiny regarding resource use. Small-to-mid-scale operators must now balance Power Usage Effectiveness (PUE) with Water Usage Effectiveness (WUE) to maintain their social license to operate.

A roadmap for this shift is visible in programs like Microsoft’s Community-First AI Infrastructure initiative, launched in early 2026. This framework commits to five core pillars, including concrete promises to minimize operational water consumption and replenish more water than facilities withdraw. For SMS players, following these stewardship best practices is not just about ethics; it is about securing permits and ensuring long-term operational resilience in power- and water-constrained regions.

Future-Proofing with “Cooling as a Service”

To overcome the “high CapEx” barrier of liquid cooling, many operators are turning to service-led models like Cooling as a Service (CaaS). These models convert complex thermal management stacks into predictable, auditable outcomes. By leveraging specialized vendors who handle commissioning, fluid analysis, and real-time monitoring, SMS data centers can scale their AI capabilities as quickly as the platforms change, without over-engineering their facilities for an uncertain future.

Ultimately, the transition to liquid cooling is not just for the giants of the industry. By integrating smart hardware, precision chemistry, and service-based models, small-to-mid-scale operators can bridge the density gap and reliably host the next generation of mission-critical AI workloads.

# # #

About the Author

Bob Walicki is an innovation leader with nearly 20 years of experience in research, development and engineering at Ecolab, a global leader in water and infection prevention solutions. He is currently responsible for driving innovation for Ecolab’s Global High Tech Data Centers segment. Most of Bob’s career has been oriented to solving customer problems related to industrial water treatment and utilization in many industries, including Mining and Mineral Processing through application of novel chemistries as well as intelligent automation and digital solutions. He holds a Bachelor of Science degree in Chemistry from the University of Notre Dame as well as a Master’s of Science and a PhD in Physical Chemistry from the University of Chicago.

The post Bridging the Density Gap: The Shift Toward Integrated Cooling for the Mid-Market appeared first on Data Center POST.

PTC’26 in Honolulu brought together global leaders shaping the future of connectivity and digital infrastructure. Amid conversations about scale, capacity and next-generation networks, one theme stood out: the growing need to align infrastructure development with the communities it serves. Among the event’s luscious backdrop in Hawaii, Ilissa Miller, founder of iMiller Public Relations and editor-in-chief of Data Center POST, shared how that challenge is shaping her work, and a new industry initiative designed to address it head-on – the OIX Digital Infrastructure Framework Committee. Onsite at PTC ’26, Miller spoke with Isabelle Paradis of Hot Telecom to share how communities are navigating the rapid expansion of digital infrastructure and why a more structured planning approach is urgently needed.

As data centers and digital infrastructure projects proliferate, municipalities are increasingly encountering developments that are far more complex than traditional commercial or residential projects. Power requirements, water usage and long-term resource planning often raise questions and concerns at the community level, leading to hesitation or pushback when local leaders lack clear context or planning tools, slowing projects and complicating conversations with the community.

Drawing on 30  years of experience working at the intersection of infrastructure development and public engagement, Miller explained that the challenge is not opposition to technology itself, but uncertainty and change. For example, digital infrastructure developments, such as data centers, do not impact communities in the same way as housing, or even industrial developments. Yet, many municipalities are being asked to evaluate projects without a framework that reflects those differences. That gap, she noted, is where the industry must do more to educate, engage and partner with local decision-makers in order to be effective.

In response, in September 2025 Miller announced  the Digital Infrastructure Framework Committee through the OIX Association, a nonprofit organization serving the broader digital infrastructure ecosystem of network, cloud and data center operators. The volunteer-led committee is developing a practical planning framework intended specifically for municipalities and city planners. Rather than reacting to individual project proposals, the framework encourages communities to define a long-term vision for technology infrastructure in their communities, assessing what they have today, what will be required to support governments and businesses tomorrow, and how technology can enable sustainable growth over time.

Miller emphasized that the initiative is built around collaboration and real-world expertise. The committee meets every other week and regularly brings in industry specialists to inform the framework, ensuring it reflects how digital infrastructure is actually designed, financed and deployed. The goal is to deliver a draft to market by early summer, giving municipalities a tangible resource at a time when infrastructure decisions are becoming increasingly consequential.

At PTC’26, where global connectivity, data centers and digital ecosystems take center stage, Miller’s message resonated clearly: the future of digital infrastructure depends not only on innovation and investment, but on trust, transparency and alignment with the communities that host it. By helping municipalities better understand what they are evaluating, initiatives like the Digital Infrastructure Framework aim to move the industry toward a more collaborative, sustainable model for growth.

Save the dates for PTC’27 which will take place in Honolulu, Hawaii from January 17-20, 2027.

You can find the full interview here.

The post PTC’ 26: Ilissa Miller on Building a Community-Centered Digital Infrastructure Framework appeared first on Data Center POST.

Originally posted on Datalec LTD.

In a digital economy where uptime is non-negotiable, effective critical facilities management (FM) is becoming a primary lever for managing outage risk in high‑density, AI‑driven data centres. As infrastructure grows more complex and AI-driven compute places unprecedented strain on power and cooling systems, operators face escalating risks, making the cost of getting FM wrong higher than ever.

Evolving Pressures, Escalating Risks: The New Reality for Data Centre Operators

Despite steady year-on-year improvements in resilience, the industry continues to operate under significant pressure. According to Uptime Institute’s 2025 Outage Analysis, outages are occurring less frequently but are becoming more complex and more expensive when they do happen. Power-related failures remain the leading cause of impactful incidents, accounting for 54% of major outages, while 53% of operators reported at least one outage in the past three years, even as overall rates decline.

This challenge is amplified by the rapid rise of AI and the high-density compute requirements. AI workloads are now “straining existing infrastructure, especially around power and cooling,” creating new categories of risk that simply didn’t exist a decade ago. Staffing shortages across the sector add further pressure, reducing the availability of experienced professionals capable of managing mission-critical environments.

The financial implications are equally significant. More than 54% of organisations reported that their most recent outage exceeded $100,000 in cost, and 20% experienced losses above $1 million. For large enterprises, downtime can reach $540,000 to well over $1 million per hour, depending on sector and workload criticality.

This is the operating landscape that data centre leaders must now navigate, where even small procedural missteps can cascade into business-critical failures.

To continue reading, please click here.

The post Why Effective Facilities Management Is Essential for Today’s Data Centre Operators appeared first on Data Center POST.

By Kevin Dickens, CEO at Empire Fiber Internet

Reliable, high-speed Internet access is essential for economic growth, education, and online engagement in today’s rapidly evolving digital landscape. However, many communities in Northeastern Pennsylvania struggle with limited access to affordable broadband options and are often stuck with suboptimal methods such as traditional cable. These factors restrain business and residential users in their ability to fully utilize the modern Internet which has evolved into an essential utility and bedrock of digital business. This leaves rural areas behind their urban counterparts, creating the digital divide. The deployment of fiber optic network infrastructure in these communities has the potential to stimulate economic growth and development while improving bandwidth performance and Internet access for residential users, resulting in substantial benefits on a multitude of levels.

While other Internet technologies exist, fiber is the gold standard. As the CEO of Empire Fiber Internet, a local provider, I understand how these technologies work and affect communities like Bloomsburg. Fiber networks are inherently more reliable and secure than other methods because the cables are installed underground, making them less susceptible to physical damage and weather-induced events. Fiber optic technology is made from glass and transmits data through the network by sending pulses of light which travel at the speed of light, unmatched by any other Internet transport medium. This allows home users to more seamlessly connect to educational resources, streaming services, and online gaming without worrying about buffers and lag time, while businesses can improve their overall efficiency and drive higher levels of customer satisfaction.

Bloomsburg and the surrounding area is receiving major investments in technology through the development of data centers. These secure facilities store and manage Internet data. They support a stronger digital infrastructure by keeping data local, which enhances performance and reliability for nearby users. But how do we get the most out of it? Fiber connects buildings directly to the infrastructure backbone laid out by data centers, which reduces latency (improves Internet speeds), making it the technology of choice.

Fiber optic Internet improves the online experience for residents with significantly faster speeds and better reliability compared to traditional cable and copper facilities. With multi-device functionality, multiple users can simultaneously connect to home Wi-Fi without experiencing significant speed drops, whereas cable Internet users may suffer from lag and connectivity issues during high-usage time. Additionally, if a user needs higher speeds, such as to support work-from-home demands, fiber offers built-in scalability. Speed adjustments are easy to make as needs evolve, thanks to fiber’s ability to accommodate changes without requiring infrastructure upgrades.

While businesses already operating in Northeast Pennsylvania can become more efficient leveraging the superior performance capabilities of fiber, the presence of enhanced performance fiber infrastructure will also attract new businesses. Fiber allows companies to transfer data faster, conduct virtual meetings with quality video, and drive digital business. These are especially relevant for retail, healthcare, manufacturing, professional services, and high-tech businesses, which are major drivers of today’s markets. Fiber can also lead to cost savings for businesses because it is future-proof and scalable, meaning as businesses grow, their Internet needs can be easily met. The impact of stronger and new business ventures can create jobs and increase tax revenue to these communities, stimulating economic growth.

Unlike cable Internet, fiber optic technology provides unparalleled scalability, reliability, security, and speeds. These qualities make fiber the ideal choice for businesses looking to gain a competitive advantage, and for residents who want faster and more consistent services. By embracing the benefits of fiber-based Internet with local providers who strive to bridge the digital divide, Northeastern Pennsylvania can better utilize the full power of the modern Internet.

The post The Impact of Fiber Internet on Northeast Pennsylvania appeared first on Data Center POST.

Datalec Precision Installations (DPI) has introduced its next-generation Data Centre Modularisation Solution, targeting operators that need to add capacity quickly without sacrificing control, reliability or lifecycle value.

Developed in response to surging demand for rapid capacity expansion, the new solution is designed to compress delivery timelines while maintaining full flexibility over configuration, performance and long-term scalability. Each system is precision engineered and manufactured by Datalec to ensure compatibility across structural, mechanical and electrical systems, helping to reduce onsite risk and integration challenges.

Datalec’s modular approach combines pre-engineered design principles with tailored manufacturing, enabling customers to adapt deployments to specific site conditions, operational requirements and growth strategies, including AI-intensive workloads. By shifting more work offsite into a controlled manufacturing environment, the solution minimises disruption associated with traditional construction-led projects and supports safer, more succinct installations and a faster speed to market.

“With organisations under pressure to scale quickly while managing capital expenditure and quality, this launch marks a pivotal shift in how data centre capacity can be delivered,” said John Lever, Director of Modular Solutions at Datalec. “Our modular solution brings these priorities together, giving customers the confidence and agility to develop at the pace their business requires.”

By emphasising reliability, engineering excellence and lifecycle value, Datalec’s new Modularisation Solution reinforces the company’s role in delivering robust, scalable infrastructure for today’s data-driven enterprises and AI-led digital transformation. More information on Datalec’s modular critical infrastructure solutions is available at www.datalecltd.com/critical-infrastructure/modular.

The post Datalec Unveils Next-Generation Modular Data Centre Solution to Accelerate Deployment appeared first on Data Center POST.

While power dominates the headlines in AI infrastructure, water is the silent arbiter of project viability. Investors and developers obsess over megawatts and grid capacity, but the reality is that cooling systems are tethered to a resource that is often less predictable and more politically charged. When water or wastewater capacity hits a ceiling, the fallout moves beyond engineering. It triggers permitting stalls, operational interruptions, and structural impairment of asset value.

Across the U.S., municipalities are no longer just providing service; they are becoming the ultimate ‘gatekeepers’ for high-volume users. For instance, Tucson now requires any new or expanding large water user expecting more than 7.4 million gallons per month to submit a conservation plan, undergo public review, and secure City Council approval before accessing Tucson Water.

Marana’s policy further states that Marana Water will not supply potable water to data centers for cooling and requires documentation of an alternate source. In Chandler, the city council unanimously rejected a proposal to rezone land for a 422,000-square-foot AI data center campus after public opposition emphasized water use, noise, and limited local benefit.

Strategically positioned between engineering and financial close, these water policies represent a major ‘blind spot’ for developers. Late-stage discovery of water limitations results in stranded capital and protracted entitlement delays. For modern investors, such water risk is now a primary underwriting variable that can dictate the viability of an entire transaction.

Why Power Is Only Half the Constraint

Power determines how much IT load can be energized, but cooling determines whether that load can operate within temperature limits on peak summer days. Cooling design also determines whether the site depends on local water, meaning the true constraint is rarely singular.

Data centers typically rely on one of two primary heat rejection approaches.

Evaporative systems, such as cooling towers, remove heat through water evaporation. This requires continuous makeup water to replace evaporative loss and generates blowdown to control mineral concentration. Blowdown becomes a wastewater stream, tying the facility to sewer capacity, discharge regulations, and pretreatment requirements.

Dry systems, such as air-cooled chillers and dry coolers, reduce direct on-site water consumption but increase electrical demand as outdoor temperatures rise, particularly during summer peaks. That shift moves the constraint toward grid capacity and power pricing during the very hours when electricity is most expensive and constrained. In both configurations, the constraint does not disappear but shifts, and each approach carries a distinct exposure profile that must be evaluated at the basin and grid level.

Inside the Water Footprint of AI Data Centers

Water exposure extends beyond the visible intake line and is often more complex than initial site reviews suggest.

In tower-based systems, make-up water demand rises as ambient temperatures increase because more heat must be rejected during peak hours. Blowdown volumes also rise, increasing steady wastewater discharge. In many jurisdictions, wastewater capacity determines viability before raw water supply does. Dissolved solids and treatment chemistry can trigger pretreatment mandates or exceed plant acceptance thresholds, creating operational bottlenecks that were not modeled at the outset.

The true water footprint of an asset is often obscured by ‘siloed’ diligence. While a facility might minimize on-site usage, it remains tethered to the water intensity of the local energy mix—a dependency that creates a hidden risk during peak demand. Because most models consider water, power, and wastewater as isolated variables, the full scale of the water-energy nexus is rarely consolidated. This leaves the project exposed to systemic failure points that only become visible late in the development cycle.

Why Water Risk Is Frequently Mispriced

The assumption that water is a stable, predictable utility is a significant blind spot in traditional underwriting. Standard diligence often stops at a letter of intent from a provider, ignoring regulatory contingencies—such as recycled water mandates or peak-heat restrictions—that govern high-intensity facilities. Failing to account for these municipal requirements leads to Capex volatility and structural delays, turning a simple utility expense into a primary threat to projected returns.

At a portfolio level, aggregated corporate reporting can obscure localized exposure. Average water intensity metrics do not reveal whether specific assets sit in basins facing physical scarcity or wastewater systems operating near capacity. Valuations that assume perpetual expansion can fail at the local level when additional allocation is unavailable, undermining long-term growth assumptions embedded in underwriting models.

From Environmental Constraint to Financial Exposure

Water risk tends to accumulate over time, moving through operations, regulation, and local politics until it becomes a real constraint on performance.

For operators, the first pressure points are often summer peaks, when supply limits tighten and water quality can swing at the exact moment cooling systems are working hardest. This dilemma then leads to emergency operational changes that pull maintenance forward, or take short outages. Ultimately, the revenue impact of those decisions is usually disproportionate to the duration of the disruption.

For developers, on the other hand, regulatory shifts can trigger midstream redesigns. A project engineered around potable water may be required to transition to reclaimed supply, adding infrastructure, storage, and treatment complexity after capital has already been committed.

Public opposition at the local level introduces political friction that stalls approvals and compounds reputational risk. Contentious infrastructure upgrades can derail project schedules and force unfavorable cost-sharing renegotiations. Collectively, these municipal factors feed into underwriting through increased delay risk, Capex volatility, and a diminished capacity for long-term expansion.

What Needs to Change in Infrastructure Planning

Water must be evaluated at the same stage as power during site screening and early design.

A simple confirmation of water availability is no longer sufficient. Basin-level allocation rules, drought contingency plans, wastewater capacity, discharge quality requirements, and embedded grid water intensity must be assessed before engineering assumptions are finalized.

Every investment memo and design review should include a transparent water balance that identifies source type, volume requirements, discharge pathways, and regulatory triggers under peak conditions. This allows engineering and underwriting teams to evaluate exposure in parallel rather than sequentially.

Water limits are now shaping asset values in a direct, measurable way. Resilience starts with expansion plans that can hold up under tighter supply caps, and with capital that funds backup sourcing options and protection against shifting rules. Financing and insurance need to move to basin-by-basin risk models, because water availability is already the deciding factor in approvals and the constraint that most reliably dictates whether an asset can keep performing over time.

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About the Author

Dr. Vian Sharif is the Founder and President of NatureAlpha, an AI-first fintech platform delivering science-based environmental risk insights across nearly $3 trillion in assets under management. With 20 years of experience at the intersection of finance, technology, and sustainability, she also serves as Head of Sustainability at FNZ Group and is a global advisor on nature-aligned investing. She holds a PhD in Environmental Behavior Change and was recognized with a 2025 Fin-Earth Award for Natural Capital and Biodiversity.

The post Why Water Risk Is the Missing Variable in AI Infrastructure Planning appeared first on Data Center POST.

On the waters off O‘ahu, a growing digital infrastructure tradition is quietly helping shape Hawai‘i’s next generation of IT professionals. fifteenfortyseven Critical Systems Realty (1547) recently hosted its 3rd Annual Aloha Charity Fishing Tournament: Fishing for Futures, raising $40,000 to support technology education and workforce development across the islands. Held on January 17, 2026, ahead of the Pacific Telecom Council’s annual PTC’26 conference, the event highlighted how industry collaboration can directly advance technology education and workforce development across the islands.

All proceeds from the tournament will benefit the Chamber of Commerce Hawai’i’s Information Technology Sector Partnership Program, helping to expand technology education, training, and career pathways for students and jobseekers statewide. The initiative aligns with 1547’s ongoing investment in Hawai‘i through its local operations, including DRFortress and AlohaNAP, the state’s premier multi-tenant, carrier-neutral data centers that serve as key hubs in the region’s digital infrastructure ecosystem.​

This year’s tournament also reinforced 1547’s commitment to supporting the local economy by partnering with Hawai‘i-based vendors for catering, hospitality, and charter services. Event catering was provided by Aloha Culinary Group and Fin’s Bagels, while Whipsaw Sportfishing, a local O‘ahu-based charter, coordinated the fleet and donated a charter experience to the tournament winner. Additional local charter operators participating in the tournament included Golden Dragon, Limitless, Magic, Mattie, Play N Hooky, Reel Life, Renegade, Ruckus (Five Star Sportfishing), Ruckus (Ruckus Sportfishing & Diving), and Sea Hawk.

The tournament’s fundraising success was driven by the generous support of sponsors across the digital infrastructure ecosystem, including Allianca Group, Connect Data Centers Powered by Oppidan, DLA Piper, DRFortress, Harrison Street, Hawaiian Telcom, Holt Construction Mission Critical, Oberle Law, Stillwell-Hansen, TPK Consulting, Trane, Competitive Telecoms Group, iMiller Public Relations and WTEC Their contributions will directly support technology education and workforce development programs that help prepare the next generation of IT professionals in Hawai‘i.

“The 1547 Aloha Charity Fishing Tournament is a powerful expression of the Spirit of Aloha, uniting our industry around a shared purpose of investing in Hawai‘i’s future,” said J. Todd Raymond, CEO & Managing Director at 1547. “When we come together as a community, we can do more than build networks; we can open doors for the next generation of technologists, innovators, and leaders across the islands.”​

Building on the momentum of the first three tournaments, which together have raised tens of thousands of dollars for Hawai‘i communities, the Aloha Charity Fishing Tournament has become a highly anticipated tradition ahead of the annual PTC conference, blending industry networking with philanthropy. Looking ahead, 1547 plans to expand the event’s reach and impact, with the 4th Annual Aloha Charity Fishing Tournament scheduled for Saturday, January 16, 2027, followed by an awards presentation and barbecue at Ala Moana Regional Park in Honolulu. Those interested in participating in the 2027 tournament or learning more about 1547, AlohaNAP, and the company’s community initiatives can visit 1547’s website for additional information.

To read the full release, please click here.

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A veteran forensic consultant’s patent-pending platform is exposing the hidden scheduling failures that silently destroy value across every major infrastructure project in America.

Every year, billions of dollars in construction value are destroyed; not by bad materials, not by incompetent workers, not even by unforeseen site conditions. They are destroyed by scheduling failures that nobody caught in time.

Ricardo Hinojos has spent more than two decades in the field, from underground utilities to hyperscale data centers serving some of the most demanding clients on the planet. In project after project, he kept seeing the same quiet crisis: schedules that looked clean on paper but were riddled with deficiencies invisible to the human eye — missing logic ties, resource conflicts, unrealistic durations, and cascading risks that would not surface until millions of dollars were already committed.

The industry accepted this as normal. Mr. Hinojos refused to.

The Data Tells a Brutal Story

In forensic work analyzing over $3.2 billion in construction projects, RHSS found that more than 70 percent of construction schedules contain critical deficiencies; errors significant enough to compromise project delivery, inflate costs, and expose owners to litigation. These are not minor formatting issues. These are logic gaps that cause downstream collapse. Duration assumptions that defy physics. Resource allocations that exist only on paper.

For hyperscale data center construction, where a single day of delay can cost hundreds of thousands of dollars in lost revenue, this is not merely an operational problem. It is a financial crisis in slow motion. Amazon, Google, Microsoft, and the broader hyperscale ecosystem are racing to bring capacity online against unprecedented demand, with the margin for error shrinking every quarter.

Why Traditional Scheduling Tools Are Not Enough

Primavera P6. Microsoft Project. Oracle. These are powerful platforms. But they are instruments, not intelligence. They record what you tell them. They do not question whether what you told them is right. The gap between a schedule that looks compliant and one that is defensible has always required a seasoned expert to bridge. Until now, that meant expensive consultants, weeks of review, and subjective judgment calls that did not always hold up in court or in client meetings.

The construction industry has been waiting, perhaps without realizing it, for something categorically better.

A New Paradigm: Predictive Schedule Intelligence

The platform developed by Ricardo Hinojos Scheduling Solutions represents what the firm calls predictive schedule intelligence, an AI-powered validation system purpose-built for the complexity of hyperscale infrastructure projects. The patent-pending system achieves 91 percent accuracy in identifying schedule deficiencies before they become field problems. It does not merely flag errors; it predicts cascading impacts, generates litigation-grade documentation, and produces defensible forensic analysis at a fraction of the time and cost of traditional methods.

“This is not a bolt-on feature for an existing platform,” Mr. Hinojos said. “It is a ground-up rethinking of how construction intelligence should work. The industry has accepted preventable failure for too long.”

What RHSS Delivers

• Automated Schedule Validation: Quality checks against DCMA 14-Point analysis, contract specifications, and industry standards, completed in hours rather than weeks.
• AI-Driven Resource Loading: Manpower forecasting and crew productivity analysis tied to real-world RS Means labor data across all construction disciplines.
• Forensic Delay Analysis: Court-ready documentation and defensible delay analysis built to withstand litigation, arbitration, and regulatory scrutiny.
• Earned Value Integration: Real-time project health visibility through EVM metrics calibrated for hyperscale data center construction workflows.

The Bigger Picture

We are entering an era where the organizations that build the fastest, most reliably, and most cost-effectively will not simply be the ones with the best labor or the best materials. They will be the ones with the best intelligence systems. RHSS was built precisely for this moment, and for the clients, partners, and technology companies that recognize what is at stake in the race to deliver the infrastructure that powers the modern economy.

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About the Author

Ricardo Hinojos is a Certified Forensic Construction Consultant (CFCC) with 20+ years in construction project management and forensic consulting. He specializes in hyperscale data center construction scheduling, forensic delay analysis, and AI-powered project intelligence. He holds a patent-pending AI schedule validation system achieving 91% accuracy across $3.2 billion in analyzed projects and serves as an expert witness in construction delay litigation and arbitration.

The post The Construction Industry Has a $500 Billion Problem — And AI Is Finally Ready to Solve It appeared first on Data Center POST.

Originally posted on DāSTOR LLC.

Healthcare organizations are under increasing pressure to protect patient data while maintaining uninterrupted clinical operations. Ransomware activity continues to target hospitals, regulatory scrutiny is rising, and years of accumulated unstructured data have made security and compliance more difficult to manage. At the same time, many organizations are being asked to modernize infrastructure and prepare for cloud adoption with limited internal resources.

As a strategic technology partner to the New Jersey Hospital Association (NJHA), DāSTOR is working with member hospitals to bring unstructured data under control, strengthen security, and build a more reliable foundation for future AI and analytics. This collaboration focuses on giving hospitals a clearer view of their data so they can reduce risk, curb costs, and move forward with confidence.

Unstructured Data Risk in Healthcare

Much of a hospital’s most sensitive information lives in unstructured form, including clinical documents, imaging files, shared drives, and historical records. These files often remain accessible long after their primary use has ended, increasing storage costs and expanding the attack surface for ransomware and other threats.

When teams lack a complete inventory of this data, several challenges follow:

• Limited visibility into where sensitive patient data resides
• Greater exposure during ransomware and breach events
• Compliance risk from over-retention and inconsistent classification
• Rising storage and backup costs driven by low-value data

Many hospitals already invest in security tools, yet still lack visibility into the data those tools are meant to protect.

To continue reading, please click here.

The post Securing Healthcare Data Without Disrupting Care appeared first on Data Center POST.

As organizations modernize infrastructure, expand cloud environments, and support hybrid workforces, cybersecurity strategies are evolving alongside them. While investments in network security, data center resilience, and endpoint protection continue to grow, one constant remains: people are often the first line of defense against phishing and social engineering threats.

To address this reality, Aureon has introduced a new Security Awareness Training platform designed to help organizations reduce preventable incidents through continuous, behavior-focused education. The solution combines realistic phishing simulations, adaptive learning modules, and executive-level reporting to support measurable improvement over time.

Moving Beyond Check-the-Box Training

Traditional security awareness programs frequently rely on annual compliance-based training. While important, that approach alone may not reflect the pace at which threat actors adapt their tactics.

“Security awareness has to move beyond annual check-the-box training,” said Rhiannon Thompson, Product Manager, Managed Services at Aureon. “With Aureon Security Awareness Training, customers get continuous, adaptive education tied to real-world threats, along with executive-level reporting that helps organizations demonstrate measurable impact.”

Aureon’s platform incorporates multi-vector phishing simulations built around realistic, AI-driven scenarios. These simulations provide employees with practical exposure to common attack techniques, helping reinforce recognition and reporting behaviors in real-world contexts.

Adaptive microlearning modules further tailor content based on role, department, and individual risk exposure. By aligning education with job function and industry requirements, organizations can deliver more relevant training while strengthening overall security culture.

Executive Visibility into Human Risk

In addition to end-user training, the platform provides leadership teams with actionable insight. Human risk dashboards track reporting rates, risky behaviors, and improvement trends, offering a clearer view into how employee behavior evolves over time.

This level of visibility enables organizations to demonstrate progress internally and support audit readiness through policy acknowledgments, attestations, and structured reporting. For regulated industries in particular, tying awareness initiatives to measurable metrics can simplify governance efforts.

“Organizations don’t just need awareness, they need resilience,” said Joseph Johnson, VP Product Development at Aureon. “Our training helps make security an everyday habit, reducing preventable incidents and strengthening security culture across teams.”

Managed Support for Sustainable Impact

Beyond the technology itself, Aureon provides managed program support that includes implementation, campaign oversight, and ongoing reporting. This approach is designed to ensure that security awareness remains consistent and adaptive rather than a one-time initiative.

As digital infrastructure grows more complex, strengthening security posture requires attention not only to systems and networks but also to the individuals interacting with them daily. Continuous education, realistic simulations, and executive-level insight together form a framework that supports long-term organizational resilience.

For more information about Aureon’s Security Awareness Training solution, visit www.aureon.com/landing/what-is-security-awareness-training.

The post Aureon Strengthens Security Culture Through Continuous Awareness Training appeared first on Data Center POST.

Originally posted on Compu Dynamics.

The data center industry is entering a new phase — one defined less by generic flexibility and more by purpose-built design. For years, operators relied on large, adaptable white-space shells to support a wide range of workloads. That model served the cloud era well. But the rise of AI and high-density computing is reshaping infrastructure requirements, pushing the industry toward more integrated, modular, and performance-driven environments.

In a recent QTS podcast with David McCall, Steve Altizer, CEO of Compu Dynamics, shares his perspective on how prefabrication and modular white-space design are becoming foundational to building data centers ready for the AI era.

Why the White Space Is the New Frontier for Modular Innovation

As AI workloads push power density to new extremes, long-standing assumptions about how data centers are designed and built are being challenged. White space, once treated as a static and custom-built environment, is rapidly becoming the next frontier for modular innovation.

Why Density Changes Everything

AI workloads aren’t just hotter, they’re architecturally different. When you’re deploying GPU arrays that demand 100kW per rack today and 600kW tomorrow, you’re not simply installing servers; you’re building a machine. The sheer volume of structural steel, high-pressure liquid cooling pipes, power distribution, and network infrastructure required to support these dense deployments creates an entirely new opportunity: factory assembly.

Traditional cloud data centers were too light and airy to justify prefabrication – components would literally fall apart in transit. But modern AI infrastructure is robust, dense, and highly engineered. It’s perfect for modular construction. Think of it as building a motherboard rather than a room. Every element – power, cooling, network – works in precise coordination to support the chips doing the computational work.

To continue reading, please click here.

The post Rethinking Data Center Construction In The AI Era – The QTS Experience Podcast appeared first on Data Center POST.

PTC’26, held January 18–21 in Honolulu, Hawaii, brought together thousands of leaders across telecommunications, data centers, subsea networks, cloud, and investment to examine the rapidly evolving future of global connectivity. As one of the industry’s most influential annual gatherings, the conference served as a central forum for exploring how artificial intelligence is reshaping infrastructure strategy, workforce planning, and international collaboration.

This year’s agenda reflected a pivotal moment for the digital ecosystem. Discussions throughout the week made clear that AI is no longer an emerging trend, it is a core driver of network design, capital investment, and operational transformation. From subsea capacity planning to power availability and edge computing, nearly every conversation pointed to a shared reality: the infrastructure required to support AI is redefining how the industry plans, builds, and partners.

The AI Era: Technology Accelerated, People Essential

A recurring theme across the conference was the evolving relationship between AI tools and human expertise. One of the most talked-about sessions, “The Future of Recruiting: Powered by AI, Perfected by People,” captured this balance directly.

The panel featured a diverse group of industry leaders: Matt DeMartino, Partner for Competitive Telecoms Group; Phill Lawson-Shanks, Chief Innovation Officer of Aligned Data Centers; Jennifer Parkhill, Senior Director of Strategy Execution/Program Management for Verizon Partner Solutions; Aidan Walker, Founder and CEO, Infraviva; and was moderated by Rhys Morgan, Partner, Infranovus.

The panel highlighted how automation is improving résumé screening, candidate sourcing, and scheduling, while emphasizing that leadership evaluation, cultural alignment, and strategic hiring decisions still require human judgment. The takeaway resonated far beyond HR teams: AI can enhance speed and efficiency, but people remain central to innovation, leadership, and long-term success.

Industry Voices at the Center 

Throughout PTC’26, the interdependence of compute, power, and connectivity shaped nearly every major discussion. Sessions focused on subsea systems, global network capacity, and AI-ready infrastructure reinforced how deeply interconnected the ecosystem has become.

Many companies contributed to these discussions. Assured Communications’ CEO Joel Ogren and Chief Growth Officer Tim Parker shared their insights through poster sessions and lightning talks examining subsea cable capacity, edge computing, and AI inference at scale. Their perspectives highlighted both the opportunities and challenges of meeting surging AI-driven demand, particularly around resilience, regulatory complexity, and global system integration.

A major highlight of the week came with the annual PTC awards ceremony. A number of companies went home with pride of being recognized as a stand out contributor among many categories of submissions, including Duos Edge AI a subsidiary of Duos Technologies Group, which received the Outstanding Innovation Award at PTC’26, one of the conference’s most prestigious honors. The award celebrated Duos Edge AI’s pioneering modular Edge Data Center platform, designed to bring AI-ready compute closer to end users through secure, scalable, and rapidly deployable infrastructure. By localizing computing power at the edge in underserved communities, Duos Edge AI enables real-time AI processing and supports use cases like telemedicine, digital learning, and municipal services.

Beyond formal sessions and awards, hundreds of private meetings and informal discussions echoed the same message: success in the AI era will require closer coordination between carriers, data center operators, technology providers, and investors than ever before.

The Road Ahead

PTC’26 emphasized a powerful reality: the future of digital infrastructure will be built at the intersection of AI, energy, connectivity, and human expertise. While technology is advancing at unprecedented speed, long-term success will depend on collaboration, adaptability, and strategic clarity.

As organizations prepare for the next wave of AI-driven demand, the conversations and relationships formed at PTC continue to serve as a foundation for progress.

For 2027, we expect the event to be as well attended as this year. Strategic support is available, particularly for companies new to the sector or seeking to differentiate and gain greater exposure. Data Center POST’s parent company, iMiller Public Relations provides industry-leading public relations and community engagement programs along with event and trade show marketing packages that help propel and differentiate brands. Companies can learn more by visiting www.imillerpr.com.

In the meantime, SAVE THE DATE for PTC’27 at the Hilton Hawaiian Village in Honolulu, HI: January 17-20, 2027.

To learn more about the Pacific Telecommunications Council and upcoming events, visit www.ptc.org.

The post Inside PTC’26: AI Infrastructure, Edge Innovation, and the Power of Human Expertise appeared first on Data Center POST.

The digital landscape is undergoing a fundamental shift as computing power moves closer to the source of data generation. Distributed edge data centers are becoming the backbone of smart cities and critical infrastructure, providing the low latency and high bandwidth required for real-time applications. However, this decentralized model introduces a significant operational challenge. Unlike traditional centralized facilities, these edge sites are often small, unmanned, and located in diverse environments prone to temperature fluctuations and humidity.

A recent milestone in this sector highlights how large-scale organizations are addressing these complexities. A major Mexican municipality recently implemented a Smart IoT data center solution to oversee its growing network of facilities. This initiative serves as a blueprint for how urban centers can maintain resilient infrastructure without the need for constant on-site personnel. By adopting a proactive management strategy, the municipality ensured that its critical data services remain operational regardless of environmental stressors.

The Imperative for Remote Oversight

Data centers of all sizes require perfect working order to support cloud services and business operations. When facilities are distributed across a wide geographic area, the risks associated with equipment failure or unauthorized access increase. Traditional manual inspections are no longer sufficient or cost-effective. An ideal solution must instead rely on a network of sensors that monitor environmental conditions and potential risks in real time.

Environmental factors such as excessive heat, moisture, or even dust can lead to catastrophic hardware failures. Without automated oversight, a minor leak or a failing cooling fan can escalate into a major outage before it is even detected. Consequently, the industry is moving toward a framework that prioritizes predictive maintenance and real-time visibility.

Core Components of a Modern Monitoring Framework

To achieve true resilience, an ideal remote management system should integrate several key technological pillars.

First, connectivity must be both reliable and simple to deploy. Utilizing Long Range Wide Area Network (LoRaWAN) technology allows for long-range, low-power communication between sensors and the IoT gateway that delivers the data to and from the management platform. This approach eliminates the need for complex wiring or extensive new network infrastructure, significantly reducing setup costs and operational overhead.

Second, the sensor array must be comprehensive. Monitoring temperature and humidity is a baseline requirement, but true protection involves detecting a broader range of anomalies. Effective systems incorporate water leak detectors to protect liquid cooling systems and prevent moisture damage. They also utilize vibration sensors to identify mechanical failures in fans or servers before they cease functioning. Air quality and dust sensors are equally vital for maintaining the integrity of cooling systems over the long term.

Third, physical security must be integrated into the environmental monitoring platform. Automated access control sensors and motion detectors allow for the tracking of authorized personnel while immediately alerting operators to unauthorized entries.

From Data Collection to Actionable Intelligence

The value of an IoT solution lies in its ability to transform raw data into immediate action. A centralized dashboard should provide a clear overview of all conditions across the infrastructure. Rather than overwhelming users with information, alerts should be categorized by severity to allow for the quick resolution of the most critical issues.

Customizable thresholds enable users to define the exact parameters for their specific hardware requirements. When these limits are exceeded, the system should trigger instant notifications, allowing for an incident response that prevents impact on operations. Furthermore, maintaining detailed logs of all events is essential for troubleshooting and ensuring compliance with industry regulations.

Ultimately, the goal of modern data center management is to create a system that is as scalable as the data it processes. As organizations expand their footprint, they should be able to integrate additional sensors and facilities seamlessly into their existing monitoring architecture. This intelligent, proactive approach is the future of maintaining reliable and efficient digital infrastructure.

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About the Author

Bjørn Bæra is RAD’s IoT solution manager. In his networking and Industrial IoT career, he served as a product manager for Nvidia’s Spectrum silicon and prior to that as a solution engineer at Cisco, specializing in internet, switching, routing, and management.

The post The Evolution of Remote Data Center Management: Insights from a Modern Municipality appeared first on Data Center POST.