Originally published on Medium.

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

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

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

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TL;DR

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

# # #

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

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

Capital Markets Enter a More Disciplined Era

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

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

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

Valuation Models Face a Reality Check

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

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

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

Energy Availability Is Reshaping Infrastructure Strategy

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

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

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

Development Economics Continue to Evolve

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

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

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

Regional Markets Continue to Follow Different Paths

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

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

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

The Next Phase of Infrastructure Investment

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

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

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

The post International Finance Forum 2026 Examines How Risk Is Being Repriced Across Digital Infrastructure appeared first on Data Center POST.

By Mike Hodge, AI Solutions Lead, Keysight Technologies

TL;DR

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

# # #

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

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

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

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

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

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

The Economic Shift from Training to Inference

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

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

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

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

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

The Real Cost of Waiting

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

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

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

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

Inference Is Harder Than Training from a Structural Standpoint

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

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

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

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

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

Shifting Left: From Expansion to Efficiency

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

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

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

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

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

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

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

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

# # #

About the Author

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

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

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

TL;DR

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

# # #

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

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

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

The commodity trap

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

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

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

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

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

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

Engineering for the boots on the ground

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

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

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

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

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

Metrics with meaning

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

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

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

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

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

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

A change in mindset

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

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

# # #

About the Author

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

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

Originally posted on Telecom Newsroom.

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

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

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

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TL;DR

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

Originally posted on Datalec Precision Installations

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

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

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

To read the full article please click here.

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

TL;DR

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

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

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

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

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

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

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

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

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

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

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

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

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

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

TL;DR

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

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

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

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

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

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

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

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

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

TL;DR

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

TL;DR

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

# # #

Originally posted on The Kansas City Star.

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

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

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

To continue reading, please click here.

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

TL;DR

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

# # #

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

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

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

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

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

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

The Operational Visibility Assumption

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

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

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

The issue becomes especially visible inside temperature-sensitive environments.

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

The monitoring system itself may remain fully functional.

The environment may not be.

Why Faster Analytics Does Not Solve the Problem

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

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

It does not.

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

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

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

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

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

Single-point sensing cannot fully represent these conditions.

The Risk of Confidently Incomplete Systems

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

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

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

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

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

Those are not the same thing.

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

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

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

 # # #

About the Author

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

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

TL;DR

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

# # #

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

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

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

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

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

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

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

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

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

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

TL;DR

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

# # #

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

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

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

This is creating demand for delivered energy solutions, such as over-the-road compressed natural gas (CNG). Certarus, the leader in mobile CNG solutions in North America, provides an integrated, scalable solution to help customers access reliable energy and move critical projects forward.

Certarus’ mobile CNG platform, anchored by the industry’s largest portable compression fleet, is purpose-built for these needs, providing scalable, turnkey natural gas delivery from early-stage project deployment through long-term operations. The recently announced Utah hub and gas supply award are the latest in a series of data center and industrial wins that reflect Certarus’ ability to accelerate access to energy across a range of applications.

In April, Certarus announced multiple contract awards, including a two-and-a-half-year gas supply agreement for a hyperscale data center project with more than $300 million of expected revenue over the life of the contract. Operations for that project are expected to begin in mid-2027.

Building on this momentum, the company is commissioning a new CNG supply hub southeast of Salt Lake City, Utah, and has been selected as the primary natural gas supplier for a 60 MW hyperscale data center project in the region.

Operations at the Utah facility – and gas supply to the data center – are expected to commence this month. The agreement will support the data center through commissioning and early operations until permanent infrastructure is in place, highlighting the role of mobile energy in bridging infrastructure gaps.

“Across both data center and industrial markets, customers are increasingly limited by infrastructure that cannot keep pace with energy demand,” said Dale Winger, President, Certarus. “Certarus provides an integrated, scalable solution to help customers access reliable energy to move valuable projects forward. The new Utah hub strengthens our growing network of strategically positioned supply points that allow us to serve customers quickly and efficiently across multiple end markets.”

Certarus brings a differentiated set of capabilities to both data center and industrial customers, including:

• The largest portable compression fleet in the industry, paired with the largest CNG transport trailer fleet in North America, enabling unmatched scale and deployment flexibility
• Proprietary high-flow pressure-reduction systems engineered for prime power and industrial applications
• An integrated gas supply and logistics platform that delivers turnkey energy solutions without reliance on fixed infrastructure
• An experienced field operations team with a proven track record of executing complex, large-scale projects safely

This combination positions Certarus as a trusted partner for customers who need to move quickly, scale efficiently, and operate reliably, whether as a primary energy source in early project stages or as a complementary solution alongside future pipeline infrastructure.

For more information, visit www.certarus.com.

The post Certarus Expands Energy Access for Data Centers and Industrial Customers with New Utah Hub and Major Data Center Award appeared first on Data Center POST.

TL;DR

• Student support: Aureon awards $12,000 in scholarships to Iowa students pursuing STEM and technology paths.

• Local impact: Focus on rural and statewide access to education opportunities.

• Industry relevance: Programs contribute to building the next generation of digital infrastructure talent.

# # #

As digital infrastructure expands, so does the need for skilled talent to support it across engineering, operations, and emerging technology fields.

That demand is becoming more visible across the industry, particularly as AI workloads, cloud adoption, and network expansion increase. Roles tied to cybersecurity, data analysis, and field operations are evolving quickly, requiring a workforce that can keep pace with more complex infrastructure environments.

In Iowa, Aureon is contributing to that effort through its annual STEM scholarship programs, awarding a total of $12,000 to nine high school students preparing to enter technology-focused fields. Rather than a single initiative, the scholarships are structured to reach students across different communities and educational paths. One program supports students from areas served by independent telecommunications providers, while another is designed for those pursuing broader technology education across colleges, universities, and trade schools within the state.

This reflects a growing recognition that workforce development needs to start early and extend beyond major metro areas. Rural communities are becoming increasingly important to the digital infrastructure ecosystem, both as locations for network expansion and as sources of future talent.

The students selected for this year’s scholarships plan to pursue disciplines that closely align with current industry needs, including computer engineering, cybersecurity, software development, and data-driven business fields. Many will remain in-state for their education, reinforcing a local pipeline between Iowa’s education system and its evolving technology landscape.

“Every year, we see Iowa students whose talent and drive will power the state’s technology future,” said George O’Neal, CEO of Aureon. “By investing in their STEM education today, we’re strengthening the communities and businesses we serve across Iowa.”

Investments in education like this are becoming an important way to support both workforce development and local communities. As networks grow and new technologies place greater demands on performance and security, companies are recognizing that long-term success depends as much on people as it does on platforms.

Aureon plans to continue the program, with the next round of applications expected to open later this year. Additional details are available in the full announcement: https://www.imillerpr.com/news/aureon-awards-12000-in-stem-scholarships-to-nine-iowa-high-school-students/

The post Aureon Invests in Future Tech Talent with STEM Scholarships Across Iowa appeared first on Data Center POST.

TL:DR

• Beyond Simple Job Counts: Communities often evaluate digital infrastructure projects based solely on the number of permanent jobs created within the facility, which causes them to overlook the massive chain reaction of economic opportunity these developments generate.
• Immediate Economic Activation: The financial impact of a facility begins long before construction starts; early planning and design phases immediately drive demand for local services, consultants, legal teams, and hospitality sectors.
• High Value, Low Community Strain: Data centers act as central nodes that stimulate massive supply chains and professional services across the region, while bringing the added benefit of placing little to no long-term stress on local resources like schools, housing, and traffic.
• A Holistic Economic Catalyst: To fully leverage the next generation of technology investment, communities must adopt greater economic literacy to see beyond narrow employment metrics and recognize digital infrastructure as a comprehensive catalyst for regional growth.

# # #

Understanding infrastructure architecture is critical, but so is recognizing how economic value actually materializes. Much of the public conversation still evaluates digital infrastructure through narrow employment metrics, overlooking the broader chain reaction of opportunity these developments activate. To plan effectively, communities need greater economic literacy around how infrastructure investment shapes regional growth over time. This is the final article in my eight-part series exploring the convergence of industry and governance to solve the digital infrastructure build-out dilemma.  You can read the previous posts in my series here, to learn more.

When communities evaluate digital infrastructure projects, the conversation often centers on a single question: How many permanent jobs will this facility create?

It is an understandable question. Local leaders are accountable for economic development outcomes, and employment metrics are familiar, tangible indicators of value. But when digital infrastructure is assessed primarily through job-count comparisons, an enormous portion of its economic impact can be overlooked.

Because the economic story begins long before a facility is built.

Economic activity begins the moment a digital infrastructure project is conceived. Local vendors are engaged, consultants are hired, impact studies are commissioned, and hospitality and service sectors immediately feel the benefit. A data center doesn’t just create jobs inside the facility; it activates an entire ecosystem of opportunity across industries.

From the earliest stages of planning, projects generate demand for a wide range of local services. Developers engage research firms to assess feasibility. Environmental consultants evaluate land and resource considerations. Architects and engineers begin design work. Legal teams structure transactions. Lobbyists and policy advisors navigate regulatory environments. Activists raise funds and the ecosystem designed to bring us technology becomes an interchange of dollars, even to those who don’t want them there.

Even basic logistical needs create ripple effects. Before a project even goes in front of a planning board, developers are already hiring local printers, using local hotels and restaurants, bringing in consultants, commissioning impact studies: economic activity starts the moment a project is conceived.

As development progresses, the ecosystem expands further. Skilled trades such as electricians, plumbers, construction specialists, become essential. Security providers, transportation firms, and equipment suppliers play critical roles. Connectivity providers, chip supply chains, and energy innovation partners contribute to the broader infrastructure landscape.

Yet many traditional impact assessments remain narrowly focused. Impact studies are often too narrow. They focus on permanent jobs, maybe 100 or 150 roles for a large data center, but during construction there can be thousands, and even that still misses the broader economic activity.

This gap between perceived and actual impact can shape public sentiment. When residents see a large facility but hear relatively modest employment figures, questions naturally arise about whether development aligns with community priorities.

And remember, the inverse is also happening. The stress on schools, housing, traffic for a long-haul large-scale development is low to no impact locally. When structured effectively, these large facilities provide incredible economic benefits to communities without the long-term strain on resources.

What is often less visible is the multiplier effect. People look only at the building, they don’t understand that digital infrastructure development builds entire local economies.

A data centers function as a node within a complex network of industries. A data center sits at the center of an entire ecosystem where computer chips, networks, professional services sit. Expanding off of that there are many more layers of economic opportunity. These economic opportunities span the country or world.

For example, consider that professional services firms expand. Hospitality businesses experience increased demand. New suppliers enter regional markets. Workforce development programs evolve. Adjacent technology investments may follow. Think of all of the consultants,  lawyers, lobbyists, and the associations that benefit from these businesses. The direct, indirect and tertiary benefits of these large scale deployments can reach well beyond a community’s immediate needs for local jobs.

Understanding this broader economic landscape is increasingly important as communities navigate infrastructure decisions in a rapidly digitizing world. Evaluating projects through holistic economic literacy, rather than isolated metrics , can help align development outcomes with long-term strategic goals.

This is one of the central objectives of iMPR’s proprietary Groundswell™ engagement  approach.

By helping communities identify where value is created across the full lifecycle of infrastructure development, stakeholders can move beyond transactional debates toward more informed planning conversations. The focus shifts from whether development creates jobs in a single facility to how it contributes to regional competitiveness, business attraction, and ecosystem growth.

Digital infrastructure is not simply a building. It is an economic catalyst.

Communities that understand this dynamic are better positioned to participate in the opportunities emerging from the next generation of technology investment.

Those that do not may underestimate the scale, and timing, of its impact.

Learn more about what we are doing at iMiller Public Relations to bridge the gap between industry and community for the digital infrastructure sector, go to www.imillerpr.com.

For information about the OIX DIFC, visit www.oix.org/standards-and-certifications/oix-dif-standard.

The post The Hidden Economy of Digital Infrastructure appeared first on Data Center POST.

TL;DR

• Quantica Infrastructure filed interconnection applications with NorthWestern Energy tied to future power generation capacity for its Big Sky Digital Infrastructure Campus in Montana.
• The filing begins a formal review process that takes place years before construction and is intended to support potential long-term customer demand.
• The proposal includes renewable generation, firming generation, and battery storage.
• Quantica says it would fund the additional power infrastructure rather than passing costs to local ratepayers.

Quantica Infrastructure has taken another step in the development of its Big Sky Digital Infrastructure Campus in Montana by filing interconnection applications with NorthWestern Energy tied to future power generation capacity for the project.

The filing supports Quantica’s 1,100 MW Big Sky Campus in Yellowstone County and is intended to help meet potential long-term customer demand while supporting regional grid reliability. According to the company, additional capacity would be delivered in multiple phases over several years and would remain aligned with customer commitments and regulatory approvals.

The filing also marks the beginning of NorthWestern Energy’s formal interconnection review process, which occurs years in advance of construction for projects of this scale.

As proposed, the applications cover a mix of renewable generation, firming generation, and battery storage representing up to 7,235 MW of maximum additional capacity. Quantica noted that renewable generation output would be materially lower than maximum nameplate capacity and that generation proposals of this scale undergo extensive review processes intended to maintain system reliability.

A central component of the announcement is Quantica’s position that the company would be responsible for the cost and construction of the proposed additional generation infrastructure.

“Quantica will pay for the additional power capacity for the Big Sky Digital Infrastructure Campus in Montana. NorthWestern Energy’s ratepayers will not be responsible for the cost of the power. As a Billings resident, I appreciate this approach and it’s important to me that my neighbors don’t foot the bill for our project,” says Charlie Baker, Chief Accounting Officer of Quantica Infrastructure.

“Developed by Montanans and grounded in local priorities, this project is designed to advance statewide economic opportunity while responsibly safeguarding communities and minimizing negative impacts to Montana’s citizens.”

Quantica also stated that Big Sky Digital Infrastructure has engaged in preliminary discussions with the Montana Department of Environmental Quality regarding permitting requirements for the campus and associated generation infrastructure, including firming power options such as natural gas, geothermal, and other potential sources.

The company framed the filing as part of broader planning for long-term infrastructure needs.

“Data center companies are looking for places that can deliver power, connectivity, and building capacity at scale. By investing in additional capacity now, we plan to address what we’re seeing in terms of power demand from data center companies. This expansion significantly increases our total investment in Montana, and the additional power capacity would result in even more economic opportunity, construction jobs over several years, and strengthen the State’s power grid,” says John Chesser, CEO of Quantica Infrastructure.

The Big Sky Campus spans 5,100 acres approximately 30 miles north of Billings and is positioned adjacent to major infrastructure including a substation, highways, and rail access. Quantica says the site is designed to support multiple data center buildings and accommodate the proposed increase in power capacity without expanding the campus footprint.

The company expects the first building to become operational in 2029. Quantica also plans to connect the campus through hundreds of miles of new fiber-ready underground conduit intended to link the site with additional U.S. markets and support regional connectivity.

Read the full release here: https://www.imillerpr.com/news/quantica-files-interconnection-applications-to-expand-power-generation-for-its-big-sky-digital-infrastructure-campus/

The post Inside Quantica’s Plan to Prepare Big Sky Campus for Future Power Demand appeared first on Data Center POST.

TL;DR

• New high density inventory at 60 Hudson: Hudson InterXchange (Hudson IX) plans to bring a second 1 MW data hall online in July 2026, creating additional deployment opportunities inside one of New York City’s most interconnected carrier hotel environments.
• Supporting AI and next generation workloads: The new space is designed for high density cabinet deployments capable of supporting air cooled loads of 45kW and beyond, enabling organizations to accommodate AI, cloud, HPC, and compute intensive applications.
• Long term growth underway: Following the successful launch of its first 1 MW data hall, Hudson IX continues progressing toward a larger vision of delivering more than 10 MW of total capacity at 60 Hudson Street.

As artificial intelligence workloads, cloud ecosystems, and high performance computing environments continue reshaping digital infrastructure requirements, operators in major metropolitan markets are encountering a growing challenge: securing available power and deployable space in highly connected locations. In New York City where both remain at a premium, the ability to bring new inventory online has become increasingly valuable.

Hudson IX is continuing its growth at 60 Hudson Street with plans to bring a second 1 MW data hall online in July 2026. The expansion follows the successful launch of the company’s first 1 MW data hall, which is already supporting customer deployments and represents another step toward Hudson IX’s broader roadmap to exceed 10 MW of total capacity at the site. As AI, hyperscale platforms, and cloud environments continue driving demand, operators in mature urban markets are increasingly facing space and power constraints. 

Hudson IX remains among a limited number of providers able to deliver new contiguous space and surplus power within a highly connected New York City facility, an increasingly rare advantage in today’s constrained market. 

Connectivity remains a defining advantage at 60 Hudson Street which provides access to more than 300 carriers, cloud providers, exchanges, and service providers. As one of the world’s most network dense facilities, the ecosystem offers organizations meaningful benefits for latency sensitive and heavy interconnection environments. 

By making additional resources available inside this ecosystem, Hudson IX is offering more than physical deployment space. Customers gain entry into a deeply established connectivity environment that supports growth, performance, and operational efficiency at scale.

Atul Roy of Hudson IX emphasized the company’s ongoing commitment to serving customer requirements and strengthening its presence at 60 Hudson Street. He noted that Hudson IX continues investing aggressively to meet market demand while providing customers with rare access to scalable power resources, flexible deployment models, and dense interconnection opportunities.

Beyond this deployment, Hudson IX continues advancing a roadmap designed to expand its footprint beyond 10 MW at 60 Hudson Street, reinforcing a long term commitment to scalable growth in one of New York City’s most connected facilities. 

As digital transformation initiatives continue accelerating and demand for compute resources grows, developments like these underscore a larger reality: unlocking new opportunities within established infrastructure ecosystems may become one of the most important differentiators in constrained metro markets.

For organizations evaluating options in New York City, the continued buildout at 60 Hudson Street represents more than another facility enhancement. It creates access to one of the market’s most significant digital crossroads.

The post Hudson IX Continues 60 Hudson Growth with Second 1 MW Data Hall and Roadmap Beyond 10 MW appeared first on Data Center POST.

TL;DR

• Kasi Cloud commissioned West Africa’s first hyperscale-ready, AI-capable, carrier-neutral data center campus in Lagos, Nigeria.
• The Lekki campus is strategically located near major subsea cable landing stations and is expected to scale to approximately 100MW of IT capacity.
• LOS1 gives Nigerian enterprises, financial institutions, and government agencies a sovereign, in-country cloud and AI infrastructure alternative aligned with Nigeria’s National Cloud Policy 2025.
• Leaders across Lagos State, the Federal Government, and NSIA say the project positions Nigeria and Lagos as a major digital and AI gateway for Africa’s future growth.

# # #

Kasi Cloud Datacenters has officially commissioned West Africa’s first hyperscale-ready, AI-capable, carrier-neutral data centre campus in Lagos, marking an important step in Nigeria’s shift from digital consumer to digital owner. The recent flag-off ceremony for its Lekki campus signals the move of Kasi LOS1 from construction into operational readiness, opening up a sovereign, world-class cloud and AI infrastructure option for Nigerian enterprises, financial institutions, and government agencies.

Located across roughly four hectares in the Maiyegun area of Lekki, the campus sits next to six subsea cable landing stations, including Equiano and 2Africa. This strategic positioning strengthens Lagos’s role as a digital gateway for the continent. Once completed, the campus is expected to scale to around 100MW of critical IT capacity. LOS1 is built to support high-density AI and accelerated computing environments, alongside enterprise cloud and connectivity services, with sub-50ms latency for in-country workloads.

Keeping Nigeria’s data and value at home

Nigerian enterprises currently spend an estimated $850 million each year on foreign cloud infrastructure, sending significant capital offshore and placing data under foreign legal jurisdictions. With LOS1, Kasi is introducing the country’s first institutional-grade, AI-ready alternative built on Nigerian soil. This also aligns with Nigeria’s National Cloud Policy 2025 (NCP2025), which requires in-country hosting for sensitive government and financial data.

By providing a sovereign, enterprise-grade cloud and AI platform locally, Kasi ensures that data and the value it generates remain within Nigeria and under Nigerian jurisdiction. In practical terms, this allows enterprises, financial institutions, and government agencies to run critical workloads locally while meeting stricter compliance, data residency, and regulatory requirements.

Built for the AI era

The commissioning of LOS1 represents both a milestone in infrastructure and the delivery of a long-held mission.

“Kasi was founded on the belief that Africa deserves world-class sovereign digital infrastructure built for the AI era,” said Johnson Agogbua, Founder and CEO of Kasi Cloud Datacenters. “For too long, Africa’s data has powered someone else’s economy. Today, that changes. This flag-off marks the transition from development into commissioning and operational readiness — as we deliver world-class sovereign cloud and AI infrastructure, built in Lagos, for Africa’s digital future.”

Agogbua noted that the milestone reflects close collaboration with leaders at both state and federal levels. “We are honoured to celebrate this milestone with His Excellency Governor Babajide Sanwo-Olu of Lagos State, the Honourable Minister of Finance and Coordinating Minister of the Economy Taiwo Oyedele, and Dr. Segun Ogunsanya, Chairman of NSIA — partners and champions whose belief in Nigeria’s digital future made this moment possible” said Agogbua.

Lagos State’s long-term digital vision

The commissioning of LOS1 also reflects Lagos State’s ongoing commitment to building its economic future on strong digital infrastructure. Governor Babajide Sanwo-Olu, Executive Governor of Lagos State, returned to the Kasi Lekki Campus as Special Guest of Honour to officiate the flag-off ceremony for West Africa’s first hyperscale-ready, AI-capable data centre campus, having also presided over its groundbreaking in 2022.

His presence at both milestones reflects a continued partnership between Lagos State and Kasi Cloud, grounded in a shared belief that sovereign digital infrastructure is essential to the city’s future. He has consistently emphasized the importance of infrastructure in sustaining Lagos’s growth, stating: “If Lagos is to sustain its Centre of Excellence status in Nigeria, vital infrastructural development is critical to achieving human capital development. The economic impact that infrastructure improvement has on nation-building cannot be overemphasized.”

In December 2024, the state government publicly committed to hosting world-class data centres in Lagos. With LOS1 now commissioned, that commitment is beginning to take physical form and signals Lagos’s intention to lead Nigeria’s digital transformation.

Federal government’s Renewed Hope Agenda

At the federal level, the Honourable Minister of Finance and Coordinating Minister of the Economy, Taiwo Oyedele, also attended the flag-off ceremony, reinforcing the Federal Government’s recognition of digital infrastructure as a key pillar of Nigeria’s economic diversification strategy. The commissioning of Kasi LOS1 aligns with the Renewed Hope Agenda, which places technology and digital infrastructure at the center of growth, innovation, and job creation.

By enabling an AI-ready, sovereign platform in Lagos, Kasi supports national goals around economic resilience, innovation, and employment, helping ensure that investment in cloud and AI infrastructure translates into local value creation.

NSIA: backing sovereign digital infrastructure

The Nigerian Sovereign Investment Authority (NSIA) has played a foundational role in supporting Kasi’s vision. Also present at the flag-off was Mr. Aminu Umar-Sadiq, Managing Director and Chief Executive Officer of NSIA, one of Kasi Cloud’s foundational investors and a long-standing advocate for digital infrastructure as a driver of long-term economic transformation.

NSIA has described Kasi Cloud as a strategic asset, noting in its 2025 Annual Report that the platform is “advancing Nigeria’s digital infrastructure” as an indigenous hyperscale data centre. “We target high-impact projects that transform critical sectors of economic growth — including initiatives like Kasi Data Center. We congratulate Kasi on this momentous milestone. NSIA believes in the potential of digital infrastructure to serve as an enabler and accelerator for innovation,” Mr. Umar-Sadiq said. “We expect that the transformative impact of this infrastructure on the domestic tech space will reposition Nigeria. The Board and Management of the Authority is proud to be associated with this development.”

With LOS1 now AI-ready and open for business, that shift is already underway.

Africa’s next digital gateway

From an investor perspective, the Lekki campus is about much more than a single facility.

“Africa represents one of the most compelling long-term digital infrastructure growth markets globally,” said Mark Adams, Co-Founder of Kasi Cloud Datacenters. “As global cloud, AI, and content platforms continue expanding into emerging markets, Nigeria — and Lagos specifically — is uniquely positioned to become the strategic digital gateway for the continent. Kasi LOS1 is the infrastructure that makes that possible.”

The campus is designed to support that future, serving both global platforms expanding into Africa and regional enterprises seeking access to world-class infrastructure.

Read the full press release here.

The post Kasi Cloud Commissions West Africa’s First Hyperscale-Ready, AI-Capable Campus in Lagos appeared first on Data Center POST.

TL;DR

• DC BLOX expanded its green financing facility to $850 million, more than tripling its original October 2024 loan.
• The funding will accelerate hyperscale-ready data center and digital infrastructure growth across the Southeast.
• DC BLOX continues to strengthen regional connectivity through cable landing stations, dark fiber networks, and new hyperscale campuses.
• Company leadership says the investment supports long-term economic growth and rising cloud and AI demand throughout the region.

# # #

DC BLOX is taking another major step in its mission to build the digital backbone of the Southeast with a significant expansion of its green financing. The company has increased its Senior Secured Credit Facilities loan to $850 million, more than tripling the original $265 million facility secured in October 2024. This infusion of capital will accelerate the development of hyperscale-ready digital infrastructure across one of the fastest-growing data center regions in the United States.

The expanded green loan provides DC BLOX with greater flexibility to fund both current projects and a robust pipeline of new hyperscale data center developments. These include multiple investment-grade, preleased hyperscale facilities across the broader Southeast, where cloud and AI demand continue to rise. The financing reflects confidence in DC BLOX’s ability to consistently deliver complex, large-scale projects for hyperscale customers on time and to specification.

“Our best-of-breed financing terms and execution with our finance partners speaks volumes of our track record of execution and our strong customer composition,” said Melih Ileri, Chief Investment Officer of DC BLOX. “We were able to further develop our finance relationships with this loan and set ourselves up for accelerated growth. This financing also validates our development and operational capabilities, such as our ability to secure powered land, deliver projects on time, and meet the requirements of hyperscale customers.”

DC BLOX has focused on building the foundational digital infrastructure that enables sustained economic growth in the Southeast. The company’s cable landing stations in Myrtle Beach, South Carolina, and Palm Coast, Florida, bring global connectivity to the region, while its dark fiber network across South Carolina and Georgia provides a high-capacity backbone for regional hyperscale data centers. In parallel, DC BLOX continues to expand its footprint of edge and hyperscale campuses in markets including Alabama, Georgia, South Carolina, Tennessee, and Florida.

Leadership at DC BLOX views this financing as a catalyst not only for the company, but for the communities it serves. “DC BLOX is proud of our role in positioning the Southeast for future growth,” said Jeff Uphues, CEO of DC BLOX. “Data centers and the networks that connect them are vital for economic growth and we are thankful to our financing partners, local government leaders, customers, development partners, communities, and employees for sharing the vision and for the tremendous, sustained effort it takes to realize it.” The facility is backed by funds managed by Future Standard, a global alternative asset manager with $93 billion in assets under management and a long track record of investing in transformative infrastructure.

To learn more about DC BLOX’s expanding digital infrastructure platform across the Southeast, read the full press release here.

The post DC BLOX Secures $850 Million Green Financing to Accelerate Hyperscale Infrastructure Growth in the Southeast appeared first on Data Center POST.

TL;DR

• Driven by AI and High-Speed Fabrics: Data centers are increasingly adopting high-density fiber platforms to meet surging bandwidth demands from AI, distributed storage, and migrations to 400G/800G networks without expanding their physical footprint.
• Maximizing Rack Capacity: These platforms boost port density by utilizing very small form factor (VSFF) connectors, multifiber interfaces, and pre-terminated trunks, which simplify deployments and provide the massive connectivity required by modern GPU clusters.
• The Crucial Role of Cable Management: While high density saves space, it introduces operational risks like congested pathways and bend radius violations; successful deployments require meticulous horizontal and vertical cable management to ensure safe and efficient routine changes.
• Strategic Density Placement: The absolute highest density is not always the smartest choice. Operators should right-size their approach by deploying ultra-dense modules in stable cross-connect zones while preserving more working room in high-change areas to prevent accidental disconnects and simplify maintenance.

# # #

U.S. data centers are being pushed to deliver more bandwidth (cloud, streaming, enterprise SaaS, and support for AI) while holding the line on space, cost, and uptime. High-density fiber platforms (modular patch panels, optical distribution frames (ODFs), and pre-terminated trunk/harness ecosystems) help by packing more fiber terminations into less rack space. However: cable management and day-to-day serviceability determine whether density is an advantage or a liability, and the densest build is not always the best build.

Why port density matters now

Traffic patterns have shifted toward east–west flows inside the data center, driven by distributed storage, microservices, and GPU clusters. At the same time, fabrics are migrating from 100G/200G toward 400G and 800G, and guidance on these transitions often calls out higher port density and the rise of GPU-accelerated clusters as key design pressures. In the U.S. colocation market—where cabinets and cross-connects are billable units—packing more connectivity into fewer racks can materially impact cost and deployment speed.

High-density platforms typically increase capacity in three ways:

• More adapters per rack unit: ultra-dense 1U fields can land very large numbers of ports. High port density supports up to 120 ports per unit.
• More fibers per connector: multifiber interfaces (MPO/MTP and newer Base-16 variants) carry parallel lanes efficiently, simplifying 400G/800G breakouts and reducing the number of individual jumpers required.
• Smaller connector formats (VSFF): very small form factor connectors such as SN and CS shrink the interface itself. Use of VSFF connectors can increase fiber count to as much as 3456 in a 1U space.

The net effect is clear: significantly higher bandwidth per cabinet, and fewer racks dedicated purely to patching and distribution.

How high density supports the practical needs of deployments. 

Faster migration cycles are available at higher speeds. Modular panels and cassette-based systems make it easier to reconfigure a fiber field when switching generations (e.g., LC to MPO breakouts, Base-8/12/16 changes, single-mode expansion), without rebuilding entire rows. This matters as 400G/800G becomes common in new pods and expansions.

You get far more links per “hot” rack. AI racks can require many high-speed connections per rack position. There’s a clear link between rising connector density and GPU growth, with VSFF connectors playing a significant role in providing connectivity for increasing numbers of GPUs.

Easier labor and repeatability make execution fast and simple. Pre-terminated trunks and harnesses can reduce on-site termination work and improve consistency—valuable when schedules are tight and change windows are limited. Pre-assembled trunks and harnesses reduce installation time and labor costs while minimizing errors associated with manual termination and splicing.

Cable management: the hidden cost of maximum density

The tighter the fiber field, the easier it is to create congested pathways, exceed bend radius, or make routine MACs (moves, adds, changes) risky. Horizontal and vertical cable management is critical for maintaining bend radius and strain relief, and exceeding bend radius or placing strain can degrade performance or cause failures. A commonly cited bend-radius rule of thumb in fiber standards guidance is ~20× cable diameter while under pulling tension and ~10× when unloaded.

So “high density” must include the management ecosystem: adequate horizontal/vertical managers, front-access routing, slack storage that doesn’t crush fibers, clean labeling, and clear overhead/underfloor pathways. Dense panels often succeed or fail based on whether technicians can safely trace and dress cords without obstructing airflow or bending cords around sharp edges.

Why “not the absolute highest” can be the smartest choice

Chasing the maximum ports-per-U can increase operational risk if the environment changes frequently. A practical rule is to choose the highest density that still allows technicians to patch, trace, and dress cords without violating bend radius, blocking airflow, or turning every change into a high-risk task. Many operators right-size density based on how the area will be used:

• High-change zones where frequent repatching takes place often benefit from more working room—even if that means fewer ports per U—because it reduces accidental disconnects and speeds work orders.
• Stable zones (structured cross-connect fields) can justify ultra-dense modules because cabling changes less often and can be governed by strict procedures.
• If multiple teams touch the same cabinets, slightly lower density can improve MTTR by making circuits easier to identify and service.

Bottom line

High-density fiber platforms can be a major advantage: they compress the physical layer, support 400G/800G migrations, and keep high-bandwidth fabrics scalable as AI drives up per-rack connectivity. The payoff, however, depends on disciplined cable management— high port counts only yield optimal benefits when daily operations are aligned!

# # #

About the Author

Paul Campos is the President of R&M USA Inc.

The post High-Density Fiber: Enabling The Port Density Gains That Power Applications Of Today And Tomorrow appeared first on Data Center POST.

TL;DR

• Lubbock goes live: Duos Edge AI is opening its newest operational Edge Data Center in West Texas.
• Built for local demand: The site adds capacity for compute, AI, network, and recovery workloads across the region.
• Another step forward: The deployment expands Duos Edge AI’s edge footprint and supports long-term growth in Lubbock.

# # #

Duos Technologies Group Inc. (Nasdaq: DUOT), through Duos Edge AI, Inc., has announced a newly operational Edge Data Center in Lubbock, Texas. The facility supports the local market with scalable, low-latency infrastructure designed to serve carriers, enterprises, education, healthcare, and the broader regional economy closer to where data is created and consumed.

The Lubbock Edge Data Center serves as a central communications hub for carriers and network providers delivering services to mobile operators and other local users. The deployment marks another step in Duos Edge AI’s continued rollout of modular edge data centers built to bring high-performance computing, resilient infrastructure, and AI readiness to underserved and high-growth markets.

“Bringing this edge data center online in Lubbock delivers low-latency, high-performance computing where it’s needed most,” said Doug Recker, CEO of Duos Edge AI and Duos Technologies Group,Inc. “This deployment also reinforces our commitment to supporting local businesses and enabling long-term digital growth across the region.”

Duos Edge AI will host a Lubbock open house on Thursday, May 28, 2026, from 11:00 AM to 1:00 PM CT at 1634 18th Street, Lubbock, TX 79401. Community leaders, partners, and industry stakeholders will have an opportunity to tour the facility and learn more about the company’s edge infrastructure approach.

To learn more about Duos Edge AI and register for the open house, visit freeevite.com/event.php?e=R7tSexY4S22Yvnzuwn2S_Q.

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

TL;DR

• AI infrastructure growth is significantly increasing global data center energy consumption and operational capacity requirements.
• Renewable and carbon-free energy adoption continues to accelerate across hyperscale data centers and colocation environments.
• AI-driven liquid cooling deployments in data centers are increasing industry focus on water consumption, closed-loop cooling systems, and water efficiency strategies.
• Data center operators are making measurable progress in operational efficiency and emissions reduction despite rising AI workloads.

# # #

The rapid expansion of AI infrastructure is reshaping the global data center industry and bringing renewed focus to sustainability, energy consumption, water usage, and operational efficiency. A newly released report from Structure Research takes a closer look at how hyperscalers and data center providers are responding to these growing environmental pressures while continuing to scale infrastructure to support AI-driven demand.

The 2026 State of Environmental Impact Report analyzes environmental data from 38 data center providers and nine hyperscale cloud platforms between 2020 and 2025. The report highlights how AI deployments and high-density compute workloads are accelerating infrastructure growth while also driving new investments in renewable energy, liquid cooling, and operational efficiency.

According to the report, data centers accounted for an estimated 1.23% of global energy consumption in 2025, up from 0.81% in 2020. Total data center energy consumption increased from 198.7 TWh in 2020 to 361.6 TWh in 2025 as hyperscalers and operators expanded capacity to support AI and cloud services.

The report also found that total operational IT capacity within the data center industry reached an estimated 80,242 MW in 2025, compared to 44,046 MW in 2020. Hyperscale self-build capacity grew at a five-year CAGR of 17.6%, reflecting the ongoing global expansion of AI infrastructure campuses and large-scale cloud deployments.

Despite rising resource demands, the report points to measurable progress in sustainability initiatives across the industry. Renewable energy usage among ESG Leaders grew at a five-year CAGR of 26.2%, significantly outpacing overall energy consumption growth. Hyperscalers sourced approximately 92% of their energy usage from carbon-free energy in 2025, while data center providers reached 69%.

As power constraints continue to impact major data center markets, the report notes that operators are increasingly exploring nuclear energy agreements, natural gas partnerships, and direct power procurement strategies to secure long-term energy availability.

Operational efficiency improvements also remain a key focus area. Average Power Usage Effectiveness (PUE) for data center providers improved from 1.44 in 2020 to 1.38 in 2025, while hyperscalers maintained industry-leading average PUEs near 1.21. Emissions intensity also declined during the same period, with average emissions per GWh of energy consumption decreasing from 328.3 mtCO2e/GWh in 2020 to 229.3 mtCO2e/GWh in 2025.

Water consumption emerged as another major theme throughout the report as AI-related liquid cooling deployments continue to expand. Total water consumption among ESG Leaders increased from 55.8 million cubic meters in 2020 to 114.9 million cubic meters in 2025. In response, operators are increasingly adopting closed-loop liquid cooling systems, hybrid cooling designs, and non-potable water strategies to improve water efficiency and reduce environmental impact.

The report also includes the updated Structure Research Sustainability Quadrant (SRSQ), a benchmarking framework designed to evaluate ESG Leaders based on transparency, renewable energy usage, and operational efficiency. The initiative aims to encourage greater consistency and transparency in ESG reporting across the digital infrastructure sector.

As AI infrastructure demand continues to accelerate, the report provides insight into how hyperscalers, colocation providers, enterprises, investors, and policymakers are navigating the environmental realities tied to next-generation digital infrastructure growth.

Read more in the press release and download the report here.

The post Structure Research Examines the Environmental Impact of AI Infrastructure Growth in New ESG Report appeared first on Data Center POST.

TL;DR

• Lightpath is expanding its NYC metro fiber infrastructure to support more than 2,400 macro cell tower locations across the Northeast.
• The deployment includes 265 new route miles of fiber construction across CT, MA, NY, and NJ.
• The expansion strengthens wireless backhaul capacity and network densification while supporting multi-tenant commercialization opportunities.
• Customers in expansion markets gain access to Lightpath’s full portfolio of AI-grade connectivity solutions, including optical transport, dark fiber, Ethernet, and dedicated internet access.

###

As demand for mobile data, AI-enabled applications, and high-capacity connectivity continues to accelerate, wireless service providers are placing increasing pressure on the fiber infrastructure supporting macro cell tower deployments. Scalable, resilient backhaul networks have become essential to maintaining performance, supporting densification, and enabling future wireless growth.

To help meet these evolving infrastructure demands, Lightpath has announced a major expansion of its NYC metropolitan fiber network to support deployments for leading national wireless service providers across more than 2,400 macro cell tower locations throughout Connecticut, Massachusetts, New York, and New Jersey.

The deployment includes 265 new route miles of fiber construction, extending and densifying Lightpath’s expansive 12,100 route mile network footprint. The infrastructure leverages Lightpath’s existing high-capacity backbone to deliver scalable 100 Gbps and 400 Gbps aggregation connectivity to multiple customer endpoints.

The expansion reflects Lightpath’s broader strategy of investing alongside strategic customers while building scalable infrastructure capable of supporting additional tenants and future growth opportunities. More than half of the deployed endpoints are served using existing fiber infrastructure, demonstrating the long-term value and commercialization potential of owned network assets through multi-customer adoption.

“This expansion demonstrates our ability to invest deeply in dense fiber infrastructure, in this case expanding within the NYC metropolitan area with follow-on commercialization via lease-up of those assets across multiple customer verticals and use cases,” said Chris Morley, CEO at Lightpath.

Customers within the expansion footprint will also gain access to Lightpath’s broader portfolio of AI-grade connectivity solutions, including optical transport up to 800 Gbps, Ethernet, dedicated internet access, dark fiber, and private network services.

This announcement follows Lightpath’s recent network expansions across Greater New York, Eastern Pennsylvania, Greater Miami, Phoenix, and Columbus as the company continues building scalable, low-latency infrastructure for carriers, hyperscalers, enterprises, and data-intensive applications nationwide.

Read more in the press release here.

The post Lightpath Expands Dense NYC Metropolitan Fiber Infrastructure to Support Major Wireless Providers appeared first on Data Center POST.

TL;DR

• Green Capital S.A. and Prime Capital AG are partnering to develop a 300 MW battery storage portfolio in Poland.
• The project will span multiple sites in Poland and is designed to support grid stability, renewable integration, and energy flexibility within the European market.
• The collaboration combines local development expertise and infrastructure investment experience to accelerate delivery and long-term growth.

Green Capital S.A. and Prime Capital AG are partnering to develop a 300 MW portfolio of Battery Energy Storage Systems (BESS) in Poland, marking a notable addition to the country’s growing energy storage market. The portfolio is designed to support grid stability, renewable integration, and the broader shift toward a more flexible power system.

Project Scope

The buildout is expected to span multiple sites across Poland, with one advanced-stage project to begin construction in Q2 2026. The partners will also jointly advance a second large-scale project, expected to reach Ready-to-Build status by the end of 2026, establishing a clear development path for both partners.

The collaboration combines Green Capital’s local development expertise with Prime Capital’s infrastructure investment experience. This partnership aims to move Green Capital from a developer to an Independent Power Producer, and help Prime Capital expand its battery energy storage footprint and further cement its presence in the ever-evolving European storage market.

Market Momentum

Large-scale storage is gaining traction across Europe as utilities, developers, and investors look for ways to strengthen grid resilience and support the energy transition. Poland is emerging as an increasingly important market in that shift, with projects like this helping lay the foundation for future growth.

Michał Polanowski, CEO, Green Capital, expressed, “We are delighted to welcome Prime Capital as our partner. By establishing a joint venture for the realization of a 300 MW / 1,200 MWh BESS portfolio, we are marking a transformative moment for Green Capital. Prime Capital brings proven expertise in hybrid infrastructure investment across Europe, including a strong BESS track record, and together we are the first to bring this combination of scale and institutional capital to the Polish storage market. This portfolio will play a crucial role in balancing the national grid, enabling a faster and safer energy transition.”

Company Background

Green Capital S.A. focuses on renewable infrastructure and utility-scale project development. Prime Capital AG brings experience across energy and infrastructure investment. Together, they are advancing a portfolio that is set to play a meaningful role in expanding Poland’s battery storage capacity and modernizing its energy landscape.

The post Green Capital and Prime Capital Partner on 300 MW Battery Storage Portfolio in Poland appeared first on Data Center POST.

TL;DR

• Great Plains Communications is acquiring Fastwyre Broadband’s Nebraska business, expanding its footprint across more than two dozen communities.
• Nebraska customers will gain access to GPC’s fiber network, local support, and future network upgrades.
• The deal strengthens GPC’s long-standing commitment to Nebraska and supports continued regional growth.

# # #

Great Plains Communications (GPC), the leading Midwestern digital infrastructure provider and a portfolio company of Grain Management, LLC, is expanding its Nebraska footprint through the planned acquisition of Fastwyre Broadband’s Nebraska business, a move that strengthens its position across the state and supports its long-term network growth strategy.

The transaction will bring more than two dozen Nebraska communities into GPC’s service footprint and give current Fastwyre customers access to expanded service options, future upgrades and the company’s MEF-certified 20,000+ mile fiber network. It also extends GPC’s locally rooted support model, with call centers, representatives and technicians who live and work in the communities they serve.

“Our vision has always been to expand our fiber network throughout the Midwest and beyond and acquiring Fastwyre’s Nebraska business is a strategic milestone in that journey,” said Todd Foje, CEO of Great Plains Communications. “This acquisition strengthens our position in key markets, opens new opportunities for growth and builds on our 115-year history as a trusted technology partner in Nebraska. What continues to set us apart is the strength of our high-performing network and the dedication of our high-performing people, enabling us to consistently create long-term value while delivering the superior experience customers expect and deserve.”

Following the closing of the transaction, which is subject to customary conditions including applicable regulatory approvals, GPC said it will work to ensure seamless continuity of service and a smooth transition for Nebraska Fastwyre customers. The company also plans to upgrade and integrate the newly acquired business as part of its reinvestment strategy. This investment is expected to enable both residential and business customers across these Nebraska communities to access advanced fiber-driven services, while positioning Nebraska and beyond for future growth as technology needs continue to accelerate.

Nick Wilkin, Chief Financial Officer of Great Plains Communications shared,“The financial strength of our company allows us to pursue strategic acquisitions like this while also funding the critical network upgrades that Nebraska homes and businesses need. We are well-positioned to integrate these communities seamlessly to bring GPC’s customer-first service to Nebraska Fastwyre customers. We are also excited to welcome over two dozen Nebraska-based Fastwyre employees to GPC.”

The acquisition reflects GPC’s continued focus on infrastructure investment, customer service and regional growth.

Read the full release here.

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TL;DR

• New long-haul route: Aureon and partners deliver a 100 Tb transport network across the Midwest.

• AI-driven demand: Built to support growing cloud and AI workloads, with expansion planned to 400 Tb.

• Strategic corridor: Strengthens the Midwest as a key on-ramp to major data center hubs.

As Artificial Intelligence continues to reshape the digital infrastructure landscape, the demand for high-capacity, low-latency connectivity is accelerating at an unprecedented pace. Across the United States, regional networks are playing a more critical role in supporting hyperscale growth, cloud expansion, and the infrastructure required to power next-generation workloads.

Against this backdrop, Aureon is expanding its long-haul transport capabilities with a new 100 Tb route designed to support AI and cloud-driven traffic growth.

Built alongside partners t3 Broadband, Nokia, and Midco, the route connects Ellendale, North Dakota to Chicago through a diverse fiber corridor spanning the Midwest. Designed for both performance and resilience, the network provides a direct, low-latency pathway into major data center hubs, reinforcing the region’s role as an increasingly important connectivity corridor.

The network is being brought online in phases, with initial capacity reaching 100 Tb and a clear path toward 400 Tb as demand increases. Aureon will oversee ongoing support and maintenance, ensuring consistent performance as traffic requirements scale.

“This deployment required a high level of coordination across networks, vendors, and timelines,” said George O’Neal, President and CEO at Aureon. “Thanks to the expertise and ambition of our team, and the strength of our partner relationships, we were able to deliver the solution our customer needed in the timeframe requested.”

The collaboration highlights the complexity involved in delivering high-capacity transport infrastructure at speed. The deployment also reflects how multi-vendor coordination is becoming standard for high-capacity builds, combining optical innovation, system integration, and existing fiber infrastructure to deliver performance at scale.

Together, these efforts underscore a broader industry shift. As AI workloads increase, network operators are being pushed to rethink how infrastructure is designed, deployed, and interconnected. High-density compute environments, GPU clusters, and data-intensive applications are placing new pressure on transport networks to deliver both scale and reliability without compromise.

In this environment, regional routes like Aureon’s Midwest corridor are becoming more than just connectivity pathways. They are strategic assets that enable access to compute, support data movement between markets, and help balance capacity across an increasingly distributed infrastructure landscape.

This announcement reflects a growing recognition that the Midwest is not simply a pass-through region, but a critical component of the national connectivity fabric. With access to power, land, and expanding data center ecosystems, the region is well-positioned to support the next phase of digital infrastructure growth.

As AI continues to drive bandwidth demand higher, investments in scalable, high-performance transport networks will remain essential. Deployments like this demonstrate how collaboration across operators, technology providers, and infrastructure partners can deliver the capacity needed to keep pace with that growth.

Learn more in the full release: https://www.imillerpr.com/news/aureon-and-partners-deliver-100-terabit-route-for-the-ai-era/

The post Aureon and Partners Deliver 100 Tb Midwest Route to Support AI and Cloud Growth appeared first on Data Center POST.

TL;DR

• The Shift to the Edge: While massive “AI factories” built for model training currently dominate public attention, the real economic transformation of AI will happen at the inference layer or the edge, where capabilities are deployed directly to businesses and public services.
• Beyond Isolated Projects: Communities must move away from evaluating individual hyperscale projects in isolation and instead adopt a layered infrastructure architecture that strategically interconnects centralized compute, regional data centers, connectivity hubs, and edge nodes.
• Long-Term Competitiveness: Infrastructure decisions require a decade-long outlook, as building an aligned, distributed ecosystem today will directly dictate a region’s future workforce development, business attraction, and public service modernization.
• Empowering Local Leadership: To prevent overbuilding centralized capacity and missing out on distributed innovation, municipalities need architectural awareness and strategic frameworks to confidently align their digital infrastructure with local economic, sustainability, and community goals.

# # #

In this seventh article of my series, we can see how industry and government got to where we are today. Even as trust and governance challenges evolve, there is another strategic issue communities must grapple with: understanding that digital infrastructure is not one-dimensional. The current focus on large AI training facilities risks obscuring the broader architectural transformation underway. Long-term competitiveness will depend not just on attracting hyperscale projects, but on planning for layered and distributed infrastructure ecosystems. You can read the previous posts in my series here, to learn more.

Artificial intelligence is accelerating infrastructure development at a pace few communities have experienced before.

Across the United States, large-scale AI training facilities, often described as “AI factories”, are being planned or built to support the next generation of computing demand. These projects are significant in scale, capital intensity, and resource requirements. They are also capturing the majority of public attention.

But they are only one layer of a much larger infrastructure evolution. Due to the lack of a national vision for AI factory development, there is fear that we may be overbuilding AI factories today. And, we have not yet even begun to plan for the inference infrastructure communities will need at the edge.

Training facilities represent centralized computers, the environments where massive models are developed and refined. Yet the real economic transformation enabled by artificial intelligence will increasingly occur at the inference layer, or edge, where AI capabilities are deployed closer to businesses, public services, and everyday life.

This shift will require a more distributed infrastructure landscape.

Edge nodes, regional data centers, connectivity hubs, and specialized facilities supporting robotics, healthcare innovation, smart city platforms, and industrial automation will all play a role. Communities that focus exclusively on attracting hyperscale projects without considering how these layers interconnect may find themselves unprepared for the broader digital economy.

Infrastructure strategy, therefore, cannot be defined by individual projects alone.

It must be guided by architecture.

This is particularly important because investment cycles in emerging technologies rarely unfold evenly. Periods of rapid buildout in one segment can create perceptions of overcapacity, while adjacent segments remain underdeveloped. Without holistic planning, regions may overbuild centralized capacity while failing to support distributed innovation ecosystems that ultimately drive sustained economic value.

The time horizon also matters. This is not about the next year or the next project,  it’s about where communities will be competitive ten years from now.

Infrastructure decisions made today will influence workforce development, business attraction, real estate markets, and public service modernization for decades. Yet many communities are evaluating proposals in isolation, without frameworks that help them understand how different infrastructure types contribute to long-term economic positioning.

This is one of the reasons strategic planning efforts are becoming increasingly important.

Through the work of the OIX Associations Digital Infrastructure Framework Committee (DIFC), there is growing recognition that municipalities need guidance not only on whether to support development,  but on how to think about infrastructure layering, sequencing, and regional coordination.

Digital infrastructure is not monolithic. It is an evolving system of interconnected assets that must be aligned with community priorities, sustainability considerations, and economic aspirations.

Engagement models must evolve alongside this complexity. Helping communities help themselves is the most effective engagement strategy.

When local leaders are equipped with architectural awareness, understanding the relationship between centralized compute, distributed deployment, connectivity networks, and sector-specific applications, they are better positioned to make confident, strategic decisions.

The goal is not to predict exactly how technology adoption will unfold. It is to ensure communities are prepared to participate in that evolution rather than reacting to it.

AI will not reshape only one industry or one region. It will influence how cities operate, how healthcare is delivered, how transportation systems function, and how businesses compete globally.

Communities that adopt a layered infrastructure vision will be better positioned to capture these opportunities.

Those that do not may struggle to keep pace.

Planning for digital infrastructure is no longer just about capacity. It is about architecture.

Learn more about what we are doing at iMiller Public Relations to bridge the gap between industry and community for the digital infrastructure sector, go to www.imillerpr.com.

For information about the OIX DIFC, visit www.oix.org/standards-and-certifications/oix-dif-standard.

The post From AI Factories to Edge Nodes: Why Communities Need a Layered Infrastructure Vision appeared first on Data Center POST.

TL;DR

• The AI Inflection Point: Artificial Intelligence is driving a massive surge in the digital infrastructure industry, requiring an unprecedented scale of technology, capital, and energy resources.
• Sovereign AI: The European market is focusing heavily on data privacy and “sovereign AI,” leading to the rise of homegrown “neoclouds” to reduce reliance on US-based hyperscalers.
• Curated Networking: Structure Research’s upcoming infra/STRUCTURE Summit (Oct 6-8, 2026, in Las Vegas) is focusing on a “quality over quantity” approach, emphasizing manageable attendance sizes and curated “Hyperscale and Neocloud one-on-ones”.

# # #

The digital infrastructure industry is experiencing a massive paradigm shift, driven by the unprecedented demands of Artificial Intelligence. In a recent episode of NEDAS Live!, host Ilissa Miller sat down with Phil Shih, the Founder and Managing Director of Structure Research, to discuss the rapidly evolving landscape of data centers, hyperscale platforms, and global connectivity.

With both iMiller Public Relations and Structure Research celebrating their 15th anniversaries in 2026, their conversation in episode 65 offered a unique look back at how far the industry has come, and a critical look forward at the macro trends shaping its future.

The AI Inflection Point and the “Crypto Pivot”

According to Shih, the industry is currently in the midst of a major inflection point. The technology, resources, and capital required to support AI infrastructure represent a massive step function higher than the cloud boom that preceded it. Interestingly, this capacity crunch is creating unexpected industry crossovers.

Shih noted that a significant wave of cryptocurrency and Bitcoin mining companies, many holding vast portfolios of land and energy resources, are actively moving into the data center infrastructure sector to support hyperscale platforms and AI models. Because these crypto firms are already experienced in navigating community pushback and strict jurisdiction legislation regarding power and water usage, they are uniquely positioned to execute successful leasing deals and transition their purpose-driven data centers into AI factories.

Global Markets: Sovereign AI and Geopolitical Impacts

The conversation also ventured into international territory, specifically touching upon Shih’s recent insights from the European market. As the global race for AI dominance continues, Europe is heavily focused on “sovereign AI” and data privacy. To reduce reliance on US-based hyperscalers, Europe is steadily developing its own homegrown “neoclouds” to deliver localized computing infrastructure.

Shih and Miller also discussed the sobering reality that data centers are increasingly viewed as critical infrastructure targets amidst global geopolitical conflicts. Recent events in the Middle East, and historic drone threats to major cloud facilities, have shed a light on the vital importance of business continuity and proactive disaster recovery planning.

Looking Ahead: The infra/STRUCTURE Summit 2026

To help industry leaders make sense of these complex data points, Structure Research continues to champion collaboration through its marquee annual event, the infra/STRUCTURE Summit. Returning to the Wynn Las Vegas from October 6-8, 2026, for its seventh installment, the summit prides itself on a “quality over quantity” approach.

Unlike massive, overwhelming trade shows, the infra/STRUCTURE Summit is a highly manageable experience capped at a curated number of attendees. This year, the event is expanding its highly successful private meeting spaces to include “Hyperscale and Neocloud one-on-ones,” ensuring that operating companies, real estate firms, and energy providers can maximize their time and forge meaningful relationships.

As the industry navigates the complexities of AI demand, global conflicts, and power constraints, making data-driven decisions has never been more critical.

To learn more about Structure Research and their latest reports, visit structureresearch.net. To secure your spot at the upcoming event in Las Vegas, head over to infrastructuresummit.io.

To listen to the full conversation, please click here.

The post Navigating the AI Inflection Point and the Future of Digital Infrastructure appeared first on Data Center POST.

TL;DR

• Communities are becoming a critical factor in digital infrastructure deployment as public understanding, permitting, and local governance increasingly influence the success of AI, data center, and connectivity projects.
• AI infrastructure is evolving beyond hyperscale facilities into distributed edge deployments, creating new opportunities and planning challenges for municipalities, public safety agencies, and underserved markets.
• Local governments are being asked to make highly technical decisions about AI, sovereign AI, cybersecurity, bandwidth, and infrastructure ownership without adequate education, staffing, or strategic guidance.
• The OIX Digital Infrastructure Framework Committee (DIFC) is working to provide communities with practical planning frameworks that help city leaders evaluate digital infrastructure responsibly while supporting long-term economic growth and competitiveness.

# # #

At Connected America 2026, which focus on strategy, business models and innovation fo telecom operators, government bodies and their partners, one message became abundantly clear: the future of AI, connectivity, and economic competitiveness will depend not only on technology itself, but on whether communities are prepared to understand, evaluate, and plan for digital infrastructure responsibly.

During a fireside chat titled From Resistance to Readiness: Why Communities Need a Digital Infrastructure Framework, Ilissa Miller, CEO of iMiller Public Relations and as the Chair of the OIX Digital Infrastructure Framework Committee (DIFC), joined Peter Murray, CEO and President of Dense Networks, for a candid discussion about the growing disconnect between infrastructure deployment and public understanding. The conversation explored everything from AI infrastructure and sovereign AI to edge deployments, municipal readiness, public trust, and the urgent need for education and engagement.

The discussion was grounded in a simple but increasingly urgent reality: digital infrastructure is no longer optional. It is becoming foundational to economic growth, government operations, public safety, and national competitiveness.

The AI Infrastructure Race Has Already Begun

Miller opened the conversation by framing the broader geopolitical implications behind the surge in data center and AI infrastructure development. “We’re in the global race for AI dominance. That means that countries are out there trying to attract investment, innovation on that front line, and that also means countries are working against us.”

As communities across the United States confront proposals for new data centers, edge deployments, and fiber expansion, Miller emphasized that much of the public conversation is being driven by misunderstanding, oversimplification, and fear. “Not all data centers are created equal,” Miller explained. “You’ve got edge data centers, commercial enterprise data centers, cloud data centers, AI data centers, data centers sitting at the edge of a cell tower. They’re all called data centers, but nobody’s asking the right questions.”

That lack of clarity, she argued, is creating resistance rooted not necessarily in opposition to technology itself, but in uncertainty and lack of empowerment.

Municipalities Are Being Asked to Solve Problems They Don’t Yet Understand

Throughout the discussion, Murray reinforced the challenges local governments face as AI adoption accelerates faster than public sector planning capabilities.

“Most municipalities don’t have an innovation person,” Murray noted. “It really does take someone with the knowledge of the technology beyond the day-to-day to look at the overall environment and how the incentives are there for industry and growth.”

One of the key themes explored was the emergence of “Sovereign AI”, which is the need for governments and public safety agencies to securely manage and control sensitive data and AI systems internally.

Murray explained that municipalities are increasingly confronting difficult questions around bandwidth, security, compliance, and infrastructure ownership as AI becomes embedded into police, emergency response, transportation, and government systems.

“The municipalities are seeing high usage now taking place on their chatbots and internal uses of AI,” Murray said. “But on the other end of it, they have these critical applications that have regulations that require that they control their information and the data isn’t leaked or corrupted in any way.”

Miller emphasized that communities are not being given sufficient guidance on how to navigate these increasingly complex decisions.

“Nobody’s telling them how to do this, why they need to be doing it, how to navigate it, what questions to ask,” she said. “They need to be empowered with the information, the data points, and the ability to implement this in a very complex environment.”

Edge Infrastructure Will Shape the Next Wave of Community Development

The conversation also explored how AI infrastructure is evolving beyond hyperscale facilities into distributed edge deployments closer to population centers and public services.

Miller described what she called the “edge inference problem,” the challenge of deploying smaller, localized digital infrastructure environments that can support next-generation AI applications in cities and municipalities.

“Edge deployments will empower cities, municipalities and businesses with a competitive advantage,” Miller said, “if we’re saying no to large-scale data center developments, do we think they’re going to be saying no to these smaller edge inference locations?”

Murray pointed to growing opportunities in Tier 2 and underserved markets, particularly as federal broadband and connectivity investments continue to expand.

The discussion highlighted how digital infrastructure creates what the industry commonly refers to as “data gravity,” which is the idea that connectivity and compute resources naturally attract additional businesses, applications, and economic development.

“Digital infrastructure attracts other data points,” Miller explained. “Data gravity attracts other data applications and data usage.”

Why the Digital Infrastructure Framework Matters

A major focus of the session centered on Miller’s work leading the OIX  Digital Infrastructure Framework Committee (DIFC). The initiative aims to provide communities with practical guidance for evaluating and planning digital infrastructure projects.

Miller described the framework as an effort to bring structure, consistency, and long-term planning into infrastructure conversations that are often reactive and fragmented.

“The purpose of this framework is to provide a guidance planning document for city planners to implement digital infrastructure into their master plans,” Miller said.

She warned that communities failing to understand the strategic importance of digital infrastructure risk losing businesses, investment, and competitiveness over time.

“If we do not know the importance of that to government services, to business services, let alone to consumers, we are going to have a mass migration of businesses relocating across the country to where that data is.”

The framework initiative reflects a broader shift happening across the industry: moving conversations away from conflict and toward preparedness, planning, and informed decision-making.

A Call for Industry Engagement

One of the strongest moments in the fireside chat came when both Miller and Murray challenged industry professionals to become more actively involved at the local level.

Miller urged attendees to volunteer for planning boards, zoning committees, and local government advisory groups.

“Go to your local municipality and volunteer for your land use boards. Volunteer for your planning committees,” Miller said. “They need help. They do not know all this infrastructure, what it is and how to use it.”

Drawing on her own experience as a former elected official, she emphasized that many local leaders are being asked to make decisions about highly technical infrastructure without sufficient expertise or guidance.

Murray echoed the importance of education and public engagement, sharing examples of municipalities struggling with infrastructure planning despite significant funding opportunities.

“They don’t know what they don’t know,” Murray said. “One big voice can make a big difference in those areas.”

Building Trust Through Education and Transparency

As the session concluded, Miller emphasized that successful infrastructure deployment will require more than engineering and investment. It will require empathy, transparency, and trust.

“Before you say no, know what you’re saying no to,” Miller said. She encouraged attendees to continue having difficult but necessary conversations with communities about the realities, tradeoffs, and opportunities associated with digital infrastructure development.

“Have compassion and empathy when you’re doing that,” Miller advised. “We don’t all have to agree. That’s why this is a paradox. It’s both good and it’s bad, but we all have to figure out how to navigate this together.”

In many ways, the fireside chat captured a defining challenge for the next decade of infrastructure development: how to balance rapid technological advancement with public understanding, local governance, and long-term community planning.

As AI adoption accelerates and connectivity becomes even more foundational to society, the industry’s ability to move communities from resistance to readiness may ultimately determine how successfully the next generation of digital infrastructure gets built.

To learn more about Connected America and to save your seat at the next one, visit www.terrapinn.com/conference/connected-america/index.stm.

For information about the OIX DIFC, visit www.oix.org.

For support navigating community concerns, learn more about the Groundswell™ program offered by Miller’s company here www.imillerpr.com/community-engagement.

The post Why Communities Need a Digital Infrastructure Framework appeared first on Data Center POST.

TL;DR

• Lightpath launched a new 392-mile fiber route connecting Columbus and Chicago to support growing AI and cloud demands.
• The multi-conduit network delivers scalable, low-latency connectivity with enhanced resiliency and route diversity.
• The expansion strengthens Midwest infrastructure for enterprises, hyperscalers, carriers, and data center operators.

# # #

As demand for AI infrastructure, cloud connectivity, and high-capacity data transport continues to grow, organizations are placing increasing pressure on the networks that support modern digital operations. Scalable, low-latency connectivity and route diversity have become critical requirements for enterprises, hyperscalers, carriers, and data center operators alike.

To help meet these evolving infrastructure demands, Lightpath has announced a new 392-mile long-haul fiber route connecting Columbus, Ohio, and Chicago, Illinois.

The multi-conduit route is designed to provide scalable, high-capacity connectivity between two rapidly growing Midwest markets. Columbus continues to emerge as a major data center and cloud hub, while Chicago remains one of the country’s most important interconnection markets. By directly connecting the two, the new route will support increasing demand for AI, cloud, and data-intensive applications requiring resilient, low-latency transport.

The expansion also complements Lightpath’s broader infrastructure strategy, including LightCube edge data centers designed to support AI and edge compute deployments across key network corridors.

The system is engineered with multiple conduits to support future growth, additional fiber deployments, and enhanced route diversity. Because Lightpath owns and operates its infrastructure, customers benefit from a simplified operational model supported by a single provider and SLA.

Read more in the press release here.

The post Lightpath Announces New Long-Haul Route Connecting Columbus and Chicago appeared first on Data Center POST.

TL;DR

• New market launch: Empire Fiber Internet is now available in Wellsville, NY.
• 1,000+ locations reached: More homes and businesses can now access 100% fiber internet.
• Community presence growing: Empire is pairing service expansion with local engagement in Wellsville.

# # #

Empire Fiber Internet, a leading fiber optic internet service provider serving communities across New York and Pennsylvania, has expanded its service into Wellsville, NY, bringing next-generation connectivity to more than 1,000 homes and businesses. The expansion delivers fast, reliable internet with consistent performance built for today’s digital demands.

Unlike traditional cable or wireless services, Empire Fiber delivers a dedicated fiber connection directly to every home and business. That means symmetrical upload and download speeds, greater reliability, and dependable performance during peak usage for streaming, remote work, cloud-based applications, video meetings, and business operations.

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

Empire Fiber Internet offers multiple high-speed plans ranging from 500 Mbps to 2 Gig, all powered by a 100% fiber optic network with no data caps, no throttling, and transparent pricing. Local businesses can also access scalable fiber solutions designed to support reliability, security, and growth using the same proven technology trusted by enterprise organizations.

As part of its ongoing commitment to the community, Empire Fiber Internet has joined the Wellsville Area Chamber of Commerce and will participate in upcoming local events, including the Annual Main Street Festival. Empire Fiber Internet representatives will be available to answer questions, explain the benefits of fiber internet, and help residents and business owners understand their connectivity options.

This announcement reflects Empire Fiber Internet’s continued growth, strengthens the company’s presence in Western New York, and reinforces its position as a provider focused on both performance and local support. As communities are increasingly looking for future-ready broadband infrastructure that can support households, small businesses, and long-term economic development, Empire Fiber Internet is prepared to deliver.

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

The post Empire Fiber Internet Brings 100% Fiber Internet to Wellsville, New York appeared first on Data Center POST.

TL;DR

• AI workloads are accelerating demand for high-density infrastructure, driving increased adoption of liquid cooling, GPU-optimized environments and edge deployment strategies.
• Power availability and grid access are becoming primary factors in determining where data center projects can move forward across Southern Europe.
• Spain and Portugal continue emerging as strategic digital infrastructure hubs due to growing connectivity ecosystems, subsea cable access and hyperscale investment activity.
• Sustainability, energy efficiency and long-term operational resiliency remain central priorities as operators balance rapid expansion with evolving regulatory and environmental expectations.

# # #

Southern Europe’s role in the global digital infrastructure market continues to expand as companies look for new regions capable of supporting AI growth, subsea connectivity and large-scale data center deployment. That momentum was on full display at DCD>Connect Southern Europe 2026, held between May 6 and 7, 2026 in Madrid, where industry leaders gathered to examine the realities shaping the next phase of infrastructure growth across Spain, Portugal and the broader European market.

The conference agenda reflected an industry navigating increasingly complex demands tied to AI workloads, energy availability, cooling technologies and long-term sustainability. Across two days, conversations focused on how operators are adapting infrastructure strategies.

AI Infrastructure and High-Density Computing

AI remained at the center of nearly every major discussion throughout the event as operators prepare facilities for increasingly dense compute environments. Sessions explored how accelerated computing and GPU-driven workloads are changing infrastructure planning, with greater emphasis on liquid cooling, edge deployments and scalable facility design.

Rod Evans, EMEA VP – Supercomputing & AI Cloud Infrastructure at NVIDIA, contributed to discussions examining how AI infrastructure requirements are driving changes in compute architecture and facility design. Additional conversations featuring Tiziano Durante, Cloud Region Lead – EMEA at Microsoft, focused on operational efficiency and the growing importance of scalable cloud infrastructure across the European market.

The panel “Liquid Cooling as a Shared Strategy Among Manufacturers and Operators in the High-Density Era” examined how cooling technologies, facility architecture and chip innovation must evolve together to support next-generation AI infrastructure. Discussions reinforced that liquid cooling is rapidly moving from an emerging technology to an operational requirement for high-density deployments.

Additional sessions addressed how next-generation processors are reshaping data center design, including impacts on rack density, thermal management and power distribution strategies as AI workloads continue increasing infrastructure demands.

Power Availability and Sustainability Pressures

Power constraints and energy procurement remained among the most significant concerns discussed in Madrid. Multiple sessions addressed the growing challenge of securing grid capacity while balancing sustainability goals and long-term infrastructure expansion.

Emma Fryer, Director of Public Policy for Europe at CyrusOne, participated in ESG-focused discussions examining sustainability strategy, regulatory expectations and the role of public policy in supporting future data center growth. Additional panels explored battery energy storage systems (BESS), renewable integration and power resiliency strategies as operators look for ways to support AI growth without overwhelming existing infrastructure.

The conference also featured extensive conversations around energy efficiency and infrastructure viability. Sessions emphasized that access to power is increasingly determining where projects move forward and how operators prioritize long-term development strategies.

Southern Europe’s Growing Infrastructure Position

Regional growth and connectivity also played a major role throughout the conference as Spain and Portugal continue positioning themselves as strategic digital infrastructure markets within Europe.

Emilio Diaz, CEO of Nabiax, participated in the panel “Building Europe’s Next Digital Growth Engine – Lessons from Portugal’s Acceleration,” which explored how investment, connectivity and public-private collaboration are helping drive regional infrastructure expansion. Discussions examined how Portugal’s development model could influence broader European growth strategies as operators seek new locations capable of supporting hyperscale and AI deployments.

Eulalia Flo, Vice President at Equinix, also contributed to discussions around edge infrastructure and the increasing importance of proximity, latency and distributed deployment models as enterprises expand AI and cloud capabilities closer to end users.

DCD>Connect Southern Europe 2026 demonstrated how rapidly the European infrastructure market is evolving as AI adoption, energy strategy and operational scalability continue reshaping data center development priorities. The conversations in Madrid reflected an industry focused less on future possibilities and more on the immediate realities of deploying infrastructure capable of supporting the next generation of digital growth.

To learn more about DCD>Connect and upcoming events, visit www.datacenterdynamics.com/es/dcd-connect-live/south-europe/2026.

The post DCD>Connect Southern Europe 2026 Highlights AI Infrastructure Expansion, Power Strategy and Cooling Innovation appeared first on Data Center POST.

TL;DR

• Open house incoming: Duos Edge AI is hosting a public showcase of its newly operational Waco Edge Data Center on May 21.
• Serving the region: 77 school districts and 12 counties across the Region 12 footprint will benefit from localized AI, network, and disaster recovery capabilities.
• Growing the footprint: The Waco deployment is a key step in Duos’ broader strategy to scale distributed edge infrastructure across Central Texas and beyond.

# # #

Duos Technologies Group Inc. (Nasdaq: DUOT), through Duos Edge AI, Inc., has announced a newly operational Edge Data Center in Waco, Texas, designed to serve as a scalable local computing hub for the broader Central Texas region. The facility supports high-performance compute, network infrastructure, AI workloads, education technology, telemedicine, and disaster recovery solutions for the Region 12 Education Service Center footprint spanning 77 school districts and 12 counties.

The Waco deployment advances Duos Edge AI’s continued rollout of modular edge data centers, bringing low-latency connectivity and computing power closer to where data is created and consumed rather than routing it through distant tier one city data centers. The facility is built to integrate seamlessly with existing network infrastructure and scale alongside growing demand for real-time applications across education, healthcare, business, and emerging AI use cases.

“Waco plays a key role in Duos Edge AI’s growth strategy,” said Doug Recker, CEO of Duos Edge AI and Duos Technologies Group,Inc. “With this deployment, we’re delivering reliable, localized computing resources closer to the schools, businesses, carriers, and communities that rely on them. We’re honored to contribute to the advancement of digital infrastructure in Waco and across Central Texas.”

Community leaders, business representatives, education stakeholders, and industry partners are invited to tour the facility at the open house on Thursday, May 21, 2026, from 11:00 AM to 1:00 PM CT at 2101 W. Loop 340, Waco, TX 76712.

To learn more about Duos Edge AI and register for the open house, visit freeevite.com/event.php?e=o66IsNQrkH8Y7xG49SDytA.

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

TL;DR

• The Limits of Reactive Monitoring: Traditional alert-based monitoring struggles to manage today’s complex, multi-domain data center environments, often generating excessive noise rather than anticipating system issues.
• Anticipating Risk with Predictive and Causal AI: Moving beyond basic correlation, predictive AI forecasts potential failures hours or days in advance, while causal AI identifies root cause-and-effect relationships across interconnected systems.
• The Rise of Agentic Operations: Advanced AI systems can now recommend and independently execute corrective actions, such as adjusting cooling or redistributing workloads, which elevates human operators from manual triage to strategic oversight

# # #

As data center environments evolve, operators are managing far more than racks and servers. Today’s facilities span hybrid architectures, support increasingly dense workloads, and operate under strict energy and sustainability constraints. Yet many operations teams still rely on traditional monitoring—thresholds, alerts, and dashboards—to maintain performance. That model is reaching its limits.

Reactive monitoring was built for a simpler era. Static thresholds and rules-based automation can surface known issues, but they struggle with dynamic, multi-domain environments where signals from power, cooling, network, and IT systems are deeply interdependent. The result is often noise: thousands of alerts, limited context, and delayed response times. More importantly, these approaches lack the ability to anticipate problems before they occur.

A new operational paradigm is emerging—one defined by predictive and agentic AI.

Predictive AI enables operations teams to move upstream, identifying patterns and anomalies that signal potential failures hours or even days in advance. Instead of waiting for a temperature threshold breach or a server failure, models continuously learn from historical and real-time telemetry to forecast risk. This shift from detection to anticipation is foundational to improving reliability at scale.

Equally important is causal AI, which provides the “why” behind an issue. In complex environments, correlation alone is not enough. Operators need to understand the chain of events across systems: how a cooling inefficiency might impact compute performance, or how a network anomaly could cascade into application degradation. By establishing cause-and-effect relationships, causal AI reduces ambiguity and enables higher-confidence decision-making.

Building on this foundation is the rise of agentic operations. Unlike traditional systems that simply surface alerts, agentic systems can recommend, and increasingly execute, actions. These systems operate with context, memory, and defined guardrails, allowing them to take corrective steps such as workload redistribution, cooling adjustments, or automated ticket resolution. The goal is not to remove humans from the loop, but to elevate their role—shifting from manual triage to oversight and optimization.

A critical enabler of this transformation is unified operational intelligence. By fusing telemetry across facility and IT domains into a single, continuously learning system, organizations can break down silos that have historically slowed response. This integrated view accelerates root cause analysis, reduces duplicate effort, and ensures that actions taken in one domain do not negatively impact another.

The benefits are tangible: fewer incidents, faster resolution times, reduced operational noise, and the ability to scale infrastructure without proportional increases in headcount. As portfolios grow and complexity increases, this becomes not just an advantage, but a necessity.

Looking ahead, the concept of the “self-driving data center” is no longer theoretical. With the right combination of predictive insight, causal understanding, and agentic execution, implemented with strong governance and safety controls, operations teams can run facilities that continuously learn, adapt, and improve.

Organizations exploring this shift are beginning to evaluate platforms that combine predictive, causal, and agentic capabilities into a unified operational model. One emerging approach is applying these capabilities at the front line of operations, such as L1 or NOC environments, where AI can reduce noise, provide real-time context, and guide or automate initial response.

In this model, the role of the operator evolves. Instead of reacting to alarms, teams oversee systems that anticipate risk, act at machine speed, and deliver consistent, reliable performance across increasingly complex environments.

# # #

About the Author

Casey Kindiger is the Founder and CEO of Grokstream, where he is driving the next wave of AI-driven IT operations through a neuroscience-inspired approach to automation and prediction. A serial entrepreneur with more than 25 years of experience in enterprise IT, Casey previously founded and led gen-E and Resolve Systems as President and CEO and earlier built the consulting practice at Tidal Software as Vice President of Consulting Services.

At Grokstream, Casey established a strategic partnership with Numenta to apply cutting-edge neuroscience research, continuing to advance cognitive learning principles in the development of Grok, a self-healing AI platform that reduces alert noise, identifies root causes in real time, and enables predictive and agentic operations at scale.

His vision for cognitive AI has positioned Grokstream as an award-winning disruptor in the evolving operations market.

The post From Monitoring to Autonomy: How Predictive and Agentic AI Is Transforming Data Center Operations appeared first on Data Center POST.

TL;DR

• Rising Densities Dictate Design: As rack densities surge to 50–100kW and beyond to support high-performance computing, cooling decisions can no longer be an afterthought; they must be integrated early because they fundamentally influence the entire data centre layout, structural loading, and plant space.
• The Shift to Liquid and Hybrid Solutions: Traditional air cooling becomes difficult to manage beyond roughly 15–25kW per rack, driving the adoption of direct-to-chip liquid cooling and carefully zoned hybrid environments that mix both air and liquid cooling to retain flexibility.
• Critical Water vs. Power Trade-offs: Developers must balance Power Usage Effectiveness (PUE) against Water Usage Effectiveness (WUE), carefully evaluating local water availability, discharge constraints, and the added maintenance requirements of water-based systems.

# # #

Cooling strategy is becoming one of the earliest design decisions in high-density data centre projects, as rack densities rise and operators look for systems that can support different workloads within the same facility.

The issue is no longer limited to choosing between air and liquid cooling. Designers need to decide when a cooling approach should be fixed, how much flexibility can be retained during early design, and what operational requirements will be introduced once more advanced systems are built into the facility.

Rack-level heat density is increasing as data centres support more high-performance computing, including GPU-based infrastructure and other accelerated workloads. Traditional enterprise and cloud environments have commonly operated at around 5–15kW per rack, while higher-density requirements are now regularly moving to 30kW and above, with some reaching 50–100kW per rack and beyond.

Once that level of power and heat is concentrated into a smaller footprint, cooling begins to influence the wider building design. Data hall layout, plant space, technical corridors, structural loading, distribution routes, commissioning and long-term asset flexibility all become affected by the cooling route selected.

Air-based systems remain important for lower-density environments. Below around 15–20kW per rack, fan wall units, computer room air handlers (CRAHs) and hot/cold aisle containment continue to support many facilities effectively, with dry air or evaporative heat rejection used depending on the site and climate.

There is no fixed threshold at which air cooling stops being viable. Local climate, energy restrictions, site constraints, CapEx and OpEx priorities all influence the decision, as does the level of future flexibility the operator needs to preserve. In many data centre applications, however, air-based cooling begins to become less attractive once power densities move beyond roughly 15–25kW per rack.

Across a typical row of 24–40 racks, that can equate to around 600kW. At this level, the air volumes required become harder to manage without compromising spatial efficiency, while air velocity through racks, pressure losses, fan energy, noise and uneven air distribution all become more difficult to control.

Air cooling can often still be engineered at these densities, but the question is whether it remains the best use of space, power and capital once the wider building constraints are taken into account.

For high-density environments, direct-to-chip liquid cooling is currently the most widely adopted liquid-based approach. By removing heat closer to the source, it reduces reliance on moving large volumes of air through the data hall, which is why cooling distribution units and technology water loops are now being considered much earlier on projects where high-density zones are expected.

Immersion cooling offers strong heat transfer performance, although it is not yet being adopted at the same scale in conventional commercial data centre projects. Its use often requires changes to operational procedures, maintenance practices and supply chains, making direct-to-chip a more practical route for many operators at present.

Hybrid cooling strategies are becoming more common as operators try to retain flexibility across the data hall. These allow lower-density air-cooled loads and higher-density liquid-cooled loads to sit within the same facility, which matters while customer requirements, hardware roadmaps and cooling technologies are still developing.

A hybrid hall cannot be treated as a conventional hall with liquid cooling added in selected areas. High-density zones need to be deliberately planned, with cooling and power infrastructure concentrated in the right locations. Cooling distribution units and technology water loops serve the liquid-cooled zones, while air-based systems support lower-density rows.

This zoning is determined by hall geometry, airflow distribution, resilience requirements and the ability to maintain operating temperatures during failure conditions. Computational fluid dynamics modeling now needs to inform the design earlier, helping teams test normal and failure scenarios, including outages affecting CRAHs or fan wall units.

During due diligence and early RIBA Stage 2, the priority is usually to keep options open. Design teams will assess a range of cooling approaches across a broad vendor base, often allowing for the most onerous equipment footprints and plant replacement requirements so the scheme remains vendor-agnostic for as long as practical.

That flexibility has to narrow before detailed design. By the end of RIBA Stage 2, the cooling approach needs to be fixed if the project is to progress with confidence. The chosen system determines plant allocations, technical corridors, primary distribution routes, structural design loadings and permitting requirements.

Leaving the decision too late can appear to preserve options, but it often increases the risk of redesign once other systems are fixed. In high-density facilities, cooling is too closely linked to the physical and operational model of the building to be treated as a late-stage package decision.

Water use also influences the choice of system. From a thermal perspective, water is an effective medium for heat transfer and can help reduce mechanical cooling loads and improve power usage effectiveness. That does not mean water-based heat rejection is always the right answer.

Developers increasingly have to balance power usage effectiveness against water usage effectiveness. Water availability, abstraction limits, discharge constraints, local climate, access to potable or non-potable water and the potential for rainwater harvesting all affect whether water-based heat rejection is viable. In water-scarce locations, every cubic metre of water use may need to be justified.

Operational and public health factors also need to be considered. Adiabatic and evaporative systems can support efficiency, but they introduce maintenance requirements, including water treatment and legionella control. In some locations, modern air-cooled chillers and dry air coolers, particularly those using free cooling and magnetic bearing compressors, may offer a more appropriate balance between efficiency, resilience and water use.

Where some water availability exists, hybrid air and evaporative systems can provide a useful compromise. These systems can operate in dry mode for much of the year and use water during peak ambient conditions, balancing energy and water performance rather than optimising one metric at the expense of the other.

Liquid cooling brings further design, installation and operational considerations. Leakage remains an obvious concern, particularly where distribution systems or components are not installed and maintained correctly. Installation quality becomes more important, and contractors and operations teams need the right training to manage coolant systems, cooling distribution units and distribution networks.

Compared with conventional air-cooled environments, there is also limited operational field experience. As more high-density data centres enter service, operating teams are likely to influence future system design more strongly, particularly around access, maintenance, isolation, monitoring and coolant management.

Standardisation remains another constraint. Direct-to-chip cooling is becoming more established, but vendor approaches still vary, creating integration challenges and increasing the risk of lock-in if flexibility is not protected during design and procurement.

Cooling strategy now affects technical performance, programme, water use, operational readiness and long-term asset value. The decision is no longer based only on which technology removes heat most efficiently. It is about selecting an approach that allows the facility to support higher densities without reducing resilience, limiting future adaptation or introducing operational issues that have not been fully accounted for.

As rack densities increase, advanced cooling technologies will form a larger part of the design response. Projects that retain flexibility during early design, while fixing the cooling strategy before detailed design, will be better placed to protect programme, resilience and long-term asset value.

# # #

About the Author

Aurore Knight is an Associate Director at Black and White Engineering based out of our European headquarters in Newcastle. Her primary responsibilities as Associate Director include project delivery, design management, client liaison and technical quality assurance. She has an MSc in Building Services Engineering with Renewable Energy, is a Chartered Engineer with the Engineering Council UK and is a member of the Chartered Institute of Building Services Engineers (CIBSE).

She has worked extensively across the UK, Middle East and Europe since 2007. Aurore was part of the founding team of Black & White when operations started in August 2014.

Aurore has worked on projects in a wide range of sectors including education, healthcare, commercial, hospitality, super high-rise and mixed-use developments. During her time at Black & White, she has developed into a data centre specialist and has worked on many projects throughout Europe.

She has experience not only in leading mechanical designs but also leading full MEP and CSA design teams. Aurore has worked with a range of data centre clients, leading designs all the way from site due diligence through to construction. She has a practical approach to design and a proven record of delivering complex projects. She strives to maintain positive working relationships using a collaborative approach to problem solving.

The post Advanced Cooling Technologies Are Changing Data Centre Design Decisions appeared first on Data Center POST.

TL;DR

• FiberLocator will debut its next-generation fiber intelligence platform in July 2026, with an exclusive preview at ITW 2026.
• The updated platform introduces enhanced performance, scalable tiered offerings and expanded API and download capabilities.
• FiberLocator expanded its direct-source data integrations to provide more detailed and actionable fiber network intelligence.
• The platform is designed to support carriers, enterprises, infrastructure investors and network planners navigating increasingly complex connectivity environments.

# # #

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.

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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.

The post The Digital Future Is Being Decided by Local Politics — Whether We Realize It or Not appeared first on Data Center POST.

TL;DR

• New entity established: Datalec Precision Installations (DPI) has officially incorporated in the Kingdom of Saudi Arabia, strengthening its Middle East footprint and end-to-end data center delivery capabilities.
• Strategic market entry: Saudi Arabia is targeting approximately 1.5 gigawatts of data center capacity by 2030, with hyperscale providers including AWS, Google, Oracle, and Microsoft investing heavily in local cloud regions.
• Regional platform expansion: The Saudi entity builds on DPI’s 51,000-square-foot Dubai hub, bringing integrated design, build, fit-out, and lifecycle services closer to customers driving the Kingdom’s digital transformation.

# # #

Datalec Precision Installations (DPI), a global provider of integrated data center delivery solutions, has officially incorporated a new entity in the Kingdom of Saudi Arabia, marking a significant milestone in its strategic growth across the Middle East.

Saudi Arabia is targeting approximately 1.5 gigawatts of data center capacity by 2030 under its National Data Center Strategy, supported by large-scale public and private investment. Personal Data Protection Law and cloud regulations requiring data to be hosted in-country are accelerating demand for local infrastructure solutions. Hyperscale cloud providers including Amazon Web Services, Google, Oracle, and Microsoft are investing in cloud regions in the Kingdom, with Microsoft Azure expected to be live by Q4 2026.

“Formalising our presence in Saudi Arabia is a pivotal step in DPI’s Middle East growth journey and reflects our long-term commitment to the Kingdom’s digital transformation,” said Sean Christie, regional director, Middle East, DPI.

The expansion builds on DPI’s 51,000-square-foot Dubai hub, which serves as its Middle East head office, manufacturing center, and training facility. The Saudi entity will enable DPI to deliver grey space technical fit-outs, whitespace integration, lifecycle services, and facilities management closer to customers as they scale to meet growing cloud, AI, and data localization requirements.

To learn more about Datalec Precision Installations, visit datalecltd.com.

The post Datalec Unveils Next-Generation Modular Data Centre Solution to Accelerate Deployment appeared first on Data Center POST.

TL;DR

• Power availability is now the primary constraint on data center growth, shifting site selection toward regions where energy access, interconnection, and permitting align with deployment timelines.
• Operators are adapting strategies through hybrid energy sourcing, long-term power purchase agreements, and closer coordination with utilities to secure reliable capacity.
• ESG has become central to investment decisions, with capital increasingly tied to sustainability, energy efficiency, and alignment with community and regulatory expectations.
• Circular design, renewable integration, and high-density infrastructure optimization are emerging as key approaches to improve performance, reduce waste, and support long-term scalability.

# # #

With power availability tightening across key markets, Datacloud Energy & ESG 2026 focused squarely on the practical realities shaping data center growth. Held March 25–26, 2026 in Brussels, the event brought together operators, utilities, investors, and policymakers to examine how energy constraints, sustainability expectations, and regulatory frameworks are influencing development timelines and long-term strategy.

Discussions throughout the two-day program reflected an industry adjusting to a new set of constraints. The rapid rise of AI workloads continues to drive demand for capacity, but access to reliable power is emerging as the primary limiting factor. Rather than expanding wherever land is available, operators are increasingly prioritizing locations where energy procurement, grid interconnection, and permitting processes can align with deployment schedules.

Sessions featuring Bruce Owen, President of Global Data Centers at Equinix, explored how operators are adapting expansion strategies to reflect these realities. The shift toward hybrid energy sourcing, including long-term power purchase agreements and on-site generation, is becoming more common as companies look to secure capacity while managing risk tied to grid availability.

The role of utilities and infrastructure planning was another key focus. John Pettigrew, CEO of National Grid, addressed the growing pressure on transmission and distribution networks as data center demand accelerates. His remarks highlighted the need for earlier engagement between developers and utilities, as well as increased investment in grid modernization to support large-scale digital infrastructure projects.

From an investment standpoint, ESG considerations are now embedded in how projects are evaluated and financed. Alec Fedorov, Managing Director at ICG, noted that capital allocation is increasingly tied to a project’s ability to demonstrate long-term sustainability, efficient energy usage, and alignment with community priorities. Environmental impact and energy sourcing are no longer secondary factors, but central to investment decisions.

Circularity and operational performance were also key themes. During the panel on building more efficient, circular data centers, Fabiola Bordino, Chief Sustainability Officer at TTSP-HWP, focused on how circular design principles can improve power usage, cooling performance, predictive operations, and scalability. The discussion explored practical steps to embed circularity from design through end-of-life, including a three-pillar approach to sustainability and energy efficiency. Panelists also examined the ROI of circularity, highlighting reduced waste, improved resource utilization, and longer-term infrastructure value.

Design strategies are also evolving in response to higher-density workloads. Thomas Meier, CEO of Maincubes, discussed how operators are optimizing power distribution and cooling to increase compute output per megawatt, reflecting a broader shift toward performance-driven infrastructure rather than footprint expansion.

Adding a broader perspective, Dr. Nina Skorupska, CEO of the Renewable Energy Association, emphasized the importance of integrating renewable energy into the data center ecosystem while addressing challenges related to intermittency and storage. Her comments reinforced the need for a more coordinated approach across energy providers, infrastructure developers, and policymakers, particularly as energy strategy becomes a defining factor in how and where new data center capacity is deployed.

To learn more about upcoming Datacloud events and industry insights, visit the Datacloud event series.

The post Brussels Sets the Stage for Critical Energy and ESG Conversations at Datacloud Energy & ESG 2026 appeared first on Data Center POST.

TL;DR

• New data center capacity in New York: Hudson InterXchange (Hudson IX) has launched a 1 MW expansion at the 60 Hudson Street data center, delivering high-density colocation in one of the most connected carrier hotel NYC locations.
• Solving NYC data center constraints: The expansion adds scalable data center power and space in a supply-constrained New York City colocation market, supporting AI infrastructure, cloud platforms, and low-latency connectivity.
• Expansion ahead: Hudson IX plans an additional 1 MW data hall in Q2 2026, reinforcing its role as a key provider of colocation NYC and digital infrastructure growth in the region.

# # #

As demand for high-density infrastructure continues to accelerate, access to power and space in key metro markets has become increasingly limited—especially in New York City. Hudson InterXchange (Hudson IX) has announced an expansion at 60 Hudson Street, one of the most important data center and carrier hotel locations in NYC.This will introduce new capacity in one of the most network-dense buildings in the United States.

The company’s newly launched 1 MW data hall is now operational and available for high-density colocation deployments, providing rare access to both power and connectivity in a market where both remain constrained. Located within a carrier hotel that supports more than 300 networks and service providers, the expansion enables customers to deploy infrastructure in close proximity to critical ecosystems, an essential advantage for low-latency connectivity in NYC.

This development is coming during a time in which infrastructure requirements are evolving rapidly. Cloud adoption, AI-driven workloads, and real-time applications are placing increased pressure on existing capacity, particularly in legacy connectivity hubs like 60 Hudson Street. As a result, data center capacity constraints in NYC have become a growing challenge for enterprises and providers alike. By bringing new supply to market, Hudson IX is helping address a gap that many operators and enterprises are actively navigating.

This new data hall will support a broad range of deployments, from traditional enterprise environments to enterprise colocation solutions and high-density configurations required for compute-intensive workloads like AI inference.This flexibility positions Hudson IX to serve a diverse customer base, including network providers, content platforms, financial institutions, and cloud operators seeking AI infrastructure in New York.

“This expansion is the result of our remarkable team and its commitment to delivering a large, world-class, high-performance data center platform, with scalable solutions ranging from single cabinets to bespoke cages, supporting a wide spectrum of rack densities, all within one of New York City’s most highly connected buildings,” said Atul Roy of Hudson InterXchange. “We are grateful to our customers for entrusting us with their infrastructure, and we look forward to expanding our facility to support their growing needs.”

The announcement also reflects a longer-term growth strategy. Hudson IX plans to bring an additional 1 MW data hall online in the second quarter of 2026, with a broader roadmap that will expand total capacity at 60 Hudson Street beyond 10 MW. This continued investment reinforces the company’s role as a key provider of scalable data center power.

As digital infrastructure demand continues to scale, expansions like this highlight the importance of unlocking new capacity within existing interconnection hub NYC environments. For organizations seeking proximity, performance, and scalability, developments at 60 Hudson Street represent a critical opportunity in an otherwise supply-constrained market.

The post Hudson IX Expands at 60 Hudson with New 1 MW Data Hall, Roadmap Beyond 10 MW appeared first on Data Center POST.

TL;DR

• Predictable Performance for Mature AI: While hyperscale environments are ideal for early experimentation and rapid scaling, colocation offers the stability and long-term cost predictability required as AI workloads transition to continuous operation and fine-tuning.
• The Optimal Middle Ground: Colocation bridges the gap between on-premises and cloud setups, allowing enterprises to deploy dedicated hardware and maintain strict control without taking on the capital-intensive complexities of building their own facilities.
• Purpose-Built Infrastructure: Modern colocation facilities are being heavily upgraded with advanced environmental controls, reinforced structures, and dense network ecosystems, making them perfectly adapted to support continuous, high-density AI workloads.

# # #

Most of the current conversation around AI infrastructure tends to point in one direction. Hyperscale environments dominate the headlines, and for good reason: they offer immediate access to large pools of compute, making them an obvious starting point for many teams. However, when AI workloads move beyond early experimentation, things change. Running models continuously, managing expanding datasets, while keeping performance consistent over time introduces a different set of concerns, ones that can’t always be addressed by scale alone. What’s starting to matter more is how predictable and reliable the environment is, how costs behave long-term, and how closely the infrastructure can be reshaped around the workload itself.

Today, many colocation facilities are already being adapted to handle higher-density deployments, with upgrades in power distribution, cooling design, and interconnection capacity to support modern AI environments. Established sites are expanding their connectivity ecosystems, which makes it easier to integrate colocation into hybrid architectures without ending up with unnecessary complexity.

So, colocation for AI stays in the focus of infrastructure decisions as a very reasonable and relevant solution that continues to offer value in the age of AI. Let’s take a closer look at recent changes and why enterprises continue to choose colocation.

Hyperscalers are Not the Only Way

Hyperscale environments will continue to play a major role in how AI infrastructure evolves, especially as large-scale model training pushes demand for tightly integrated GPU clusters and massive power footprints. For certain workloads, particularly those that require rapid scaling or short-term access to large amounts of compute, they remain a very practical option.

At the same time, not every AI deployment operates at that level, and treating hyperscale as the default can lead to mismatches between the workload and the environment it runs in. Many organizations are working with more contained models, fine-tuning existing architectures, or running inference pipelines that need to perform consistently over time rather than scale unpredictably. In those cases, access to unlimited capacity matters less than having a stable, well-understood infrastructure baseline.

As a result, colocation for AI can offer a more balanced approach. Instead of relying on shared cloud environments, teams have the opportunity to deploy dedicated hardware, shape the infrastructure around their specific requirements, and maintain the necessary level of control, which is becoming increasingly important as workloads mature.

These tendencies are showing in the broader market trajectory. According to recent predictions, the global colocation data center market is projected to grow from roughly $83 billion in 2024 to over $180 billion by 2030, with a compound annual growth rate above 14%. That kind of expansion doesn’t happen if colocation is becoming less relevant. On the contrary, it points to ongoing demand from organizations that are looking for alternatives that can offer a balanced approach between the constraints of on-prem solutions and the abstraction of hyperscalers.

It’s becoming more apparent across the industry that AI infrastructure is settling into operating within a mix of models. Hyperscale, colocation, and edge environments are being used together, depending on how workloads behave and where they need to run. In this context, colocation is an essential part of how enterprises design scalable and predictable AI environments.

The Optimal Solution is the One That Fits Workloads

There isn’t a single best environment that works well for every AI deployment, and that becomes clear the moment workloads move beyond the initial isolated experimentation. Large model training, fine-tuning existing architectures, and running inference pipelines all behave differently at the infrastructure level, which in most cases leads to decisions around placement following the workload, and not a pre-established strategy. Most organizations end up distributing workloads across multiple environments. Because hyperscale platforms are useful when access to large-scale compute is the priority (especially for burst-heavy or short-lived tasks), but on-premises setups still make sense where strict control or data locality is important. A growing share of workloads, however, sits between those extremes, requiring more complex solutions, because of their complex needs: performance has to stay consistent, infrastructure needs to be adaptable, and costs should preferably remain predictable over time.

Colocation for AI offers a viable solution that many choose as a middle ground solution. Colocation makes it possible for organizations to deploy their own hardware in facilities designed specifically for IT workloads, without taking on the full complexity of building and operating those environments themselves. So, instead of adapting workloads to fit a predefined platform, this way teams can shape the infrastructure around how their systems actually run, and what they need to run optimally.

Why Colocation for AI is More Relevant Than Ever

What’s been unfolding over the past few years is a steady alignment between the demands of AI workloads and the way colocation environments are built and upgraded. Facilities are now designed with reinforced structures, advanced fire suppression systems, and controlled environmental conditions that can support the continuous, high-density operation requirements of AI workloads. Providers that meet strict compliance and certification requirements are a must for organizations operating in regulated sectors where infrastructure decisions carry not just operational, but legal weight as well.

Colocation environments have changed a lot, and this means that they have also become far more interconnected in the past few years. Direct access to cloud platforms, dense carrier ecosystems, and high-capacity interconnection layers are now standard features in many facilities, making it easier to integrate colocation into hybrid architectures without friction. As AI workloads grow in complexity, combining dedicated infrastructure with this level of connectivity and operational support becomes difficult to replicate internally. For this reason, and many others, choosing colocation for AI increasingly shows up as the most practical infrastructure choice.

Colocation for AI Compared to Other Types of Data Centers

When you step back and look at the broader infrastructure landscape, most deployments fall into a few well-defined categories: on-premises, hyperscale cloud, edge, and colocation. Each model exists for a reason, but each one serves a very different operational priority.

On-premises environments offer maximum control, but scaling them to support high-density AI workloads can become complex and capital-intensive, especially when power, cooling, and physical resilience have not been upgraded. Hyperscale platforms remove much of that burden, but instead, they introduce a level of abstraction that can make it harder to control performance characteristics or manage costs when workloads grow. Edge environments bring compute closer to users or devices, but they are typically optimized only for latency-sensitive use cases, and not for sustained, high-throughput processing.

Colocation for AI can work like a solution that brings together the best of all of these different models by combining dedicated infrastructure with facilities purpose-built for reliability and performance. Organizations can deploy their own systems, connect directly to cloud providers and network ecosystems, and scale their environments without redesigning the underlying facility. This makes colocation particularly effective for AI workloads that need both stability and flexibility, especially as part of a broader, distributed architecture.

Wise Infrastructure Choices for Long-term Value

As AI workloads move into continuous operation, infrastructure decisions start to show their real impact over time. What matters at that stage isn’t just how quickly resources can be provisioned, but also how reliably systems perform under sustained load, how costs evolve as usage stabilizes, and how easily the environment can adjust as requirements change. These are the factors that shape long-term value, and they tend to become visible only after workloads have already been running for a while.

When early choices start to show their limitations, disfunctionalities become obvious: sometimes  the environment itself makes it difficult to control the costs changed by scale, or sometimes there’s not enough visibility and flexibility once workloads mature. Choosing colocation for AI can prove to be just the right kind of stable, purpose-built environment that allows managing the infrastructure more directly. The advantage comes from this balance over time: having predictably behaving systems that can be tuned precisely to the workload can support the growth and easy scaling that is so essential for the health and optimal operation of these workloads long-term.

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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.

# # #

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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The post Why AI Is Driving the Need for Fiber-Rich Network Infrastructure appeared first on Data Center POST.

TL;DR

• Major expansion completed: Empire Fiber Internet finished its latest fiber build in Steuben County, bringing service to Avoca, Birdseye Hollow, Caton, Hornby, Howard, and Savona.
• Nearly 2,000 homes connected: The project expands access to reliable high-speed internet for more local residents and businesses.
• Bigger impact beyond the build: This expansion highlights Empire’s community investment and supports the broader push to close rural broadband gaps.

# # #

Empire Fiber Internet, a leading fiber optic internet service provider serving communities across New York and Pennsylvania, has completed its latest fiber expansion in Steuben County, bringing reliable high-speed service to residents in Avoca, Birdseye Hollow, Caton, Hornby, Howard, and Savona. Nearly 2,000 more homes are now connected, strengthening access to the kind of broadband service needed for work, school, and daily life.

The expansion reflects Empire Fiber Internet’s continued partnership with Steuben County to bring modern broadband infrastructure to rural communities. For the company, the project reinforces its local roots, deepens its investment in the region, and extends its role as both a service provider and a community partner.

“Headquartered right here in Steuben County, we’re proud to employ local residents and invest in the community where we live and work,” said Kevin Dickens, CEO of Empire Fiber Internet. “This expansion is about more than fiber, it’s about connecting people to opportunities, education, and each other. Now, nearly 2,000 more households can experience fast, reliable internet that supports how they live, work, and learn every day.”

This announcement is significant for the company, showing measurable network growth, deepening its local footprint, and demonstrating execution on long-term infrastructure investment. It also reinforces Empire Fiber Internet’s reputation as a provider focused on reliability, community impact, and future-ready broadband.

“Steuben County is extremely proud and grateful for our partnership with Empire Access for the expansion of rural broadband services across our communities,” said Jack Wheeler, Steuben County Manager. “When the County received American Rescue Plan Act (ARPA) funding in 2021, the County Legislature made it clear that rural broadband was the top priority for use of these funds, and as a result, over 2,000 previously unserved homes and businesses will now have access to high-speed internet. This would not be possible without the investment and dedication of Empire Access, who has been a trusted and responsive partner. We are thrilled with the fruition of this project and will continue to work with Empire to explore opportunities to expand broadband to all.”

Across the broadband sector, providers and local governments are under pressure to close rural connectivity gaps. This project shows how public funding and private deployment can work together to expand access, turning broadband expansion into both a service milestone and a workforce-development opportunity.

On May 13, the team will also participate in Career Day with Prattsburgh Elementary School, giving students a hands-on look at careers in fiber internet and technology. That effort underscores that broadband expansion is not only about connectivity, but also about building awareness of the jobs and skills that support the industry’s future.

Steuben County residents can check availability and sign up at empirefiber.com. Empire Fiber Internet offers 100% fiber connections with symmetrical speeds up to 2 Gig, enterprise-level reliability, locally staffed customer support, and no data caps.

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

The post Empire Fiber Internet Celebrates Major Steuben County Expansion appeared first on Data Center POST.

TL:DR;

• Full occupancy reached: Harrison Street Asset Management and 1547 have achieved full capacity at their Orangeburg, New York data center campus following a strategic, demand-driven expansion.
• Significant capacity growth: Since acquiring the site in 2021, the joint venture has successfully expanded the facility from 3.7 megawatts to approximately 18 megawatts of critical IT load.
• Future expansion underway: To meet continued market demand, the partners are developing an additional 12-megawatt utility feed and planning a pre-approved 230,000-square-foot expansion supported by a 60-megawatt on-site substation.

# # #

Harrison Street Asset Management and fifteenfortyseven Critical Systems Realty (1547) have reached a significant milestone at their Orangeburg, New York data center campus, achieving full occupancy following a phased, demand-driven expansion. The achievement highlights the continued demand for highly connected, low-latency digital infrastructure in the Greater New York market and reinforces Orangeburg’s growing role as a strategic hub for enterprise and financial services customers.

Located approximately 18 miles north of Manhattan, the purpose-built colocation facility has been expanded through a phased, demand-driven development strategy since Harrison Street and 1547 acquired the site in 2021. At the time of acquisition, the campus supported 3.7 megawatts of critical IT load. Since then, the joint venture has added roughly 14 megawatts of incremental capacity while increasing density across the existing 232,000-square-foot footprint.

The campus now supports approximately 18 megawatts of critical IT load and is operating at near-full utilization, driven largely by demand from financial institutions, high-frequency trading firms, hedge funds, and other organizations requiring ultra-low-latency connectivity into Manhattan and the broader metro region. The site also benefits from access to multiple terrestrial fiber routes and proximity to subsea cable landing infrastructure along the East Coast, making it an attractive destination for connectivity-focused workloads.

“With the facility now fully leased, each phase of development has been aligned to demonstrate customer demand,” said Michael Hochanadel, Head of Digital Assets at Harrison Street Asset Management. “Our partner delivered on schedule and within budget, while continuing to operate a critical data center with no downtime, reinforcing the strength of our collective platform.”

That disciplined approach has been central to how the Orangeburg campus has evolved. Rather than building ahead of demand, capacity has been delivered in step with customer needs, ensuring performance and reliability at every stage.

“Orangeburg is a prime example of what can be achieved through disciplined execution and close partnership,” said J. Todd Raymond, Chief Executive Officer and Managing Director of 1547. “From day one, our focus has been on delivering capacity in direct response to customer demand while maintaining the performance and reliability our clients depend on.”

With the facility fully leased, Harrison Street and 1547 are already advancing additional expansion plans to meet future customer demand. An additional 12-megawatt utility feed is currently under development, while the long-term roadmap for the campus includes a pre-approved 230,000-square-foot expansion supported by a planned on-site 60-megawatt substation.

As demand for low-latency, network-dense infrastructure continues to grow, projects like Orangeburg reflect a broader shift toward strategic, connectivity-rich locations that can scale in line with customer requirements. For Harrison Street and 1547, the continued momentum at Orangeburg further strengthens their growing data center platform and positions the campus for long-term growth.

Read the full release here.

The post Harrison Street and 1547 Reach Full Occupancy at Orangeburg Data Center as Expansion Continues appeared first on Data Center POST.

TL;DR

• AI-driven sales transformation: 365 Data Centers has entered a multi-year partnership with Collective[i], deploying its technology as a strategic intelligence layer to modernize its go-to-market operations and improve revenue predictability.
• Automated operational intelligence: The platform replaces manual processes with automation by automatically capturing activity, centralizing deal collaboration, and identifying buyer-specific risks in real time.
• Significant performance gains: The integration has led to consecutive quarters of above-plan performance, driving a 15% increase in win rates, a 35% reduction in sales cycles, and double-digit revenue growth within the first six months.

# # #

365 Data Centers is showing how AI can move beyond experimentation and into measurable business impact. In a new multi-year agreement with Collective[i], the company has transformed its commercial go-to-market operation, reporting improved win rates, shorter sales cycles, and stronger quarterly performance.

Since deploying the platform, 365 Data Centers reports that win rates have increased by more than 15% and sales cycle length has decreased by 35%. Those gains helped support several consecutive quarters of above-plan performance, including record bookings in the fourth quarter of 2025 and continued outperformance in the first quarter of 2026.

Embedding Intelligence Into Sales

365 is utilizing Collective[i]’s technology as a strategic intelligence layer across its revenue organization, replacing manual processes with automation and helping teams identify buyer-specific risks in real time. The platform also centralizes deal collaboration and captures activity automatically, which has strengthened its internal data and improved productivity.

Derek Gillespie, CEO and CRO of 365 Data Centers, expressed in the announcement that the integration supports the company’s broader commitment to data-driven inspection and AI enablement. Per Gillespie, the partnership has improved predictability and helped the company stay on track toward its long-term growth goals.

Within the first quarter of deployment, 365 Data Centers reported a 20% increase in productivity and a 34% increase in its contact database. The company also saw impressive double-digit revenue growth within just six months of deployment.

Industry Implications & Future Outlook

The timing is notable for the data center industry, where operators are under pressure to improve speed, precision, and commercial execution while serving increasingly complex customer needs. 365 Data Centers is positioning AI not only as an infrastructure advantage, but also as a tool for improving sales performance and revenue operations. Together, the two companies offer a clear example of how AI can support growth across both technical and commercial functions.

The post 365 Data Centers Partners with Collective[i], Leveraging AI to Drive Sales and Increase Revenue appeared first on Data Center POST.

Originally posted on EdgeIR.

Live streaming at scale, particularly for interactive broadcasts and sports, requires extremely low latency to maintain viewer immersion. Traditional centralized infrastructure often struggles with the “thundering herd” problem, where massive sudden spikes in viewership strain single origin points, resulting in buffering and expensive infrastructure overprovisioning. To resolve these bottlenecks, Multi-access Edge Computing (MEC) brings processing power and application hosting directly to local points of presence, drastically shortening data travel paths. Shifting tasks such as transcoding, caching, and adaptive bitrate (ABR) logic to the edge reduces first-frame delays and enables platforms to react rapidly to real-time local network conditions.

Even with these localized capabilities, high-performance bare metal servers remain vital for core, intensive workloads. Because bare metal environments lack hypervisor overhead and tenant contention, they provide the highly stable and predictable processing power necessary for demanding tasks like real-time 4K origin encoding and security orchestration. By adopting a hybrid architecture, organizations can split these responsibilities effectively, relying on bare metal for intensive central operations while utilizing edge nodes for user-proximity delivery.

Beyond optimizing the viewer experience, this hybrid approach addresses critical economic and regulatory challenges. Dedicated bare metal servers with generous included bandwidth often deliver substantially better economics for steady-state streaming compared to aggressive cloud autoscaling and expensive pay-per-GB egress models. Furthermore, keeping user ingest, sessions, and personalization local at the edge helps organizations comply with evolving regional data privacy frameworks, leaving central cores to manage global functions like digital rights management and billing.

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The post Why Streamers Need a Hybrid Edge-Bare Metal Architecture for Live at Scale appeared first on Data Center POST.

TL;DR

• Edge AI optimizes real-time performance: While cloud data centers are ideal for training massive AI models, running inference at the edge significantly lowers latency, improves data privacy, and ensures autonomous operation during network outages.
• Critical across multiple industries: Localized AI processing is vital for data-intensive, real-time applications such as healthcare diagnostics, advanced driver assistance systems (ADAS), manufacturing quality control, and security surveillance.
• Strategic deployment is required: Successfully operating AI in decentralized edge environments requires careful management of processing architecture tradeoffs, stable power distribution, thermal constraints, and system redundancy to handle potential component or power failures.
• Industry standards ensure reliability and security: Implementing established frameworks, specifically TL 9000 for system quality, TIA-942 for infrastructure resilience, and SCS 9001 for cybersecurity, is essential for keeping edge endpoints secure, robust, and highly available.

# # #

Artificial intelligence (AI) and machine learning (ML) are driving new levels of automation, insight, and responsiveness across a wide range of industries. As organizations deploy increasingly advanced generative AI (GenAI) models, they must continuously evaluate where and how to run workloads for optimal performance.

While cloud data centers offer the processing power and scale needed to train large language models (LLMs), many real-time AI applications—such as sensor networks and computer vision systems—perform more effectively when data is processed closer to the edge.

This article explores the advantages of edge AI for various applications such as healthcare, manufacturing, and advanced driver assistance systems (ADAS). It also reviews key deployment considerations, including processing architecture, power and cooling, resilient system management, and security.

Why Edge AI?

AI developers train complex LLMs in cloud-based data centers using vast datasets, high-performance compute, and petabyte-scale storage. Applying deep learning techniques, these models analyze historical data and identify patterns to refine their predictive capabilities. However, edge deployments typically perform inference—applying learned patterns to real-time data—more efficiently due to:

• Lower latency and reduced network congestion: Edge AI minimizes round-trip time by processing data locally, reducing transmitted data volume, easing traffic bottlenecks, and lowering egress costs.
• Improved data privacy and security: Onsite data processing reduces susceptibility to external threats such as man-in-the-middle attacks while simplifying compliance with data sovereignty and privacy regulations.
• Optimal resilience and autonomy: Many edge AI systems continue operating during wider network outages, a key capability for mobile, remote, or mission-critical applications.
• Increased scalability and flexibility: Distributed edge architecture allows organizations to expand AI capabilities incrementally, without overhauling centralized data center infrastructure.
• Incremental learning: Some edge systems are beginning to support incremental learning by adapting models locally based on real-time streams or historical data. This reduces the need for frequent retraining in the cloud.

Key Applications

Edge AI systems are increasingly critical for real-time, high-reliability, and data-intensive use cases. In healthcare, they enable early diagnosis and responsive care by analyzing patient telemetry and medical imaging in real time. These platforms also support robotic surgery, triage decisions, and remote patient monitoring. In pharmaceuticals, edge-deployed AI accelerates drug discovery and clinical trials through localized analysis of genomic and biomarker data. It also supports predictive modeling to customize therapies and assess patient outcomes more efficiently.

In advanced driver assistance systems (ADAS), edge AI enables real-time perception, decision-making, and actuation. Onboard processors run computer vision and sensor fusion models to detect obstacles, interpret traffic signals, and assess road conditions with millisecond-level latency. These capabilities support adaptive cruise control, lane keeping, emergency braking, and driver monitoring. Edge AI also facilitates fully autonomous driving, where vehicles must interpret and respond to complex environments without relying on cloud connectivity.

Manufacturing, industrial, and logistics operations leverage edge AI to improve quality control, identify inefficiencies, and enable predictive maintenance. Machine learning models trained in the cloud run locally to monitor sensor data, detect anomalies, and optimize equipment performance in real time. In supply chain deployments, edge systems support inventory tracking, demand forecasting, and shipping optimization. Computer vision helps verify shipments, sort goods, and maintain real-time visibility across warehouses and transit hubs.

Security and surveillance systems similarly benefit from local video processing. These applications can identify unauthorized access, classify threats, and automate alerts without immediately transmitting footage to the cloud, improving response time and maintaining data privacy.

Deployment Considerations

Processing Architecture

Edge AI system developers select processors based on workload demands, power budgets, and thermal constraints. Each processor type presents tradeoffs in performance, efficiency, and applicability to specific tasks. The table below outlines key processor considerations and options for edge deployments:

Table 1: Edge AI processor comparison, illustrating advantages, edge deployment considerations, and target applications.

Power and Cooling

Although edge systems generally run at lower densities than cloud clusters, AI workloads can still drive significant power consumption and thermal output. GPUs, in particular, draw more power than other edge AI silicon and often require more robust thermal management, especially in remote or space-constrained environments.

Stable power distribution is essential to maintain uptime in edge AI systems. Common strategies include uninterruptible power supplies (UPS), dual power feeds, and intelligent power distribution units (PDUs) with integrated monitoring. Where practical, remote monitoring tracks power quality, runtime, and system status. Some edge installations benefit from direct current (DC) power for improved efficiency, although most still require a combination of alternating current (AC) and DC infrastructure.

Resilient System Management

Edge AI deployments must tolerate component failures, communication disruptions, and power fluctuations. This requires redundancy across compute, storage, and power, along with intelligent failover mechanisms, remote management platforms, and orchestration tools that dynamically reroute workloads. Systems must also cache tasks locally and resume processing once connectivity is restored, an essential capability for high-availability and safety-critical deployments.

Developers can adopt the TL 9000 standard to embed quality and resilience into their edge AI systems efficiently and comprehensively. Defined by the Telecommunications Industry Association (TIA) and built on ISO 9001, the scalable TL 9000 adds more than 80 ICT-specific requirements spanning software, hardware, and service lifecycles.

TIA-942 complements the TL 9000 standard by defining rigorous infrastructure requirements for data centers supporting edge AI ecosystems. The standard addresses the architecture, power distribution, cooling, telecommunications, redundancy, physical security, and sustainability of data centers, ensuring high availability and scalability as AI workloads increase across both core and edge deployments.

Ensuring Security

Edge AI systems broaden attack surfaces by introducing more physical endpoints and increasing digital exposure across distributed architectures. Key cybersecurity strategies include:

• Securing AI models at rest, in transit, and during execution
• Enforcing authentication and encryption across systems
• Limiting access to verified nodes and provisioning securely
• Centrally managing nodes with granular policy controls

Organizations can implement TIA’s SCS 9001 cyber and supply chain security standard to ensure protections are applied consistently and verifiably across edge AI endpoints and infrastructure. SCS 9001 provides a certifiable, scalable ICT-specific framework that helps validate controls, assess supplier risk, and enforce safeguards in decentralized deployments. Extending quality management into the security domain, SCS 9001 can be adopted independently or alongside TL 9000 to support a unified quality and security strategy for edge AI systems.

Conclusion

High-bandwidth, low-latency applications are accelerating edge AI adoption across industries. While centralized data centers remain essential for training LLMs, edge deployments provide crucial advantages for real-time inference, data privacy, system resilience, and operational control. Effective edge AI implementation requires selecting silicon that aligns with power and thermal constraints, while embedding quality and security throughout the system lifecycle with industry standards such as TL 9000, TIA-942 and SCS 9001.

# # #

About the Author

Mike Peterson serves as the Lead for the Data Center Program at the Telecommunications Industry Association, where he oversees the global TIA-942 certification ecosystem and works closely with TR-42 subcommittees to advance data-center standards. A longtime CTO/CIO with more than three decades of experience, Mike has led data-center operations, global cloud transformations, and large-scale engineering organizations at CFA Institute, Travelzoo, and Neustar. His background spans AI strategy, platform modernization, cybersecurity, large-scale data architectures, and enterprise operational resilience. He also brings entrepreneurial roots as a founder, patent holder, and innovation leader, giving him a unique perspective at the intersection of standards, engineering, and digital-infrastructure strategy.

Mike Peterson
Data Center Program Manager
TIA (Telecommunications Industry Association)
T: +1 469-450-7950
MPeterson@tiaonline.org

The post From the Cloud to the Intelligent Edge: Benefits, Applications, and Key Considerations appeared first on Data Center POST.

Originally posted on Nomad Futurist.

Nomad Futurist Foundation Ambassador Dan Ephraim recently engaged with MBA and BSBA students at Washington University’s Olin School of Business to introduce them to the digital infrastructure industry. During interactive sessions, students explored crucial industry topics such as real estate, energy, sustainability, supply chain, and business models. The goal was to demonstrate how students could apply their existing foundations in financial analysis, operations, and leadership to meaningful career pathways within this growing sector.

The initiative successfully energized the attendees, with many students requesting tours of data centers in Virginia and St. Louis to see the operations firsthand. Feedback indicated that the sessions were eye-opening and helped solidify their interest in pursuing roles that bridge technical knowledge with go-to-market strategies. For many participants, this served as their very first real introduction to the digital infrastructure field.

Ultimately, these outreach efforts reflect the core mission of the Nomad Futurist Foundation: to open doors, connect emerging talent with opportunities, and inspire future strategists, operators, and leaders. By partnering with educational institutions and encouraging industry experts to mentor students, the foundation aims to actively shape the next generation of digital infrastructure professionals.

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DCD>Connect New York 2026 took place March 23–24, 2026 in New York City, bringing together operators, engineers, investors, and energy providers to examine how digital infrastructure is adapting to the rapid acceleration of AI-driven demand. Across two days of panels, debates, and technical sessions, the focus centered on how the industry is navigating constraints tied to power, delivery timelines, and evolving design requirements, with companies such as ZincFive participating as a Mega Partner and exhibitor, showcasing its nickel-zinc battery solutions designed to support the growing power demands of AI-driven infrastructure. .

The 2026 event reflected a maturing market, where conversations have moved beyond forecasting growth and toward executing at scale. Sessions across the agenda addressed the realities of interconnection delays, rising construction costs, and supply chain limitations, while also highlighting the increasing role of policy, permitting, and community engagement in determining how quickly projects can move forward.

Artificial intelligence remained at the center of the discussion. Industry leaders explored how AI workloads are reshaping infrastructure requirements, particularly in terms of density, latency, and geographic distribution. As demand expands beyond core hyperscale markets, operators are being pushed to rethink where and how infrastructure is deployed to support both training and inference use cases.

Power infrastructure was a defining focus throughout the event. Panels such as “Eureka! How to power data centers in the age of AI” examined how traditional utility models are being supplemented with private generation, microgrids, and hybrid procurement strategies. As AI workloads increase power intensity, access to reliable and scalable energy is becoming one of the most critical factors influencing site selection and project viability.

Cooling and facility design also emerged as key areas of innovation. Discussions highlighted how rising rack densities are accelerating the adoption of liquid and hybrid cooling solutions, while new regulatory requirements and environmental considerations are shaping how these systems are deployed. The shift toward high-density compute is driving more fundamental changes in how data centers are engineered to support next-generation workloads.

Several speakers addressed how sustainability is evolving alongside these shifts. Simone Kramer, Head of Sustainability at Bloomberg, discussed the importance of balancing speed with responsible infrastructure development. Heather McGeory, Vice President of Sustainability at CoreWeave, focused on how efficiency is becoming a key metric in evaluating sustainability strategies as compute demands increase.

The event also highlighted workforce development through the “Powering the Next Generation – Student Workshop,” hosted by Nomad Futurist and Infrastructure Masons (iMasons), designed to introduce students to the digital infrastructure ecosystem and its career opportunities. The session featured industry leaders sharing practical insights and firsthand experiences, helping to clarify how the sector operates and where emerging talent can contribute. Ilissa Miller, Founder & CEO of iMiller Public Relations (iMPR), joined Vic Rose, Director, AI Inferencing, at Microsoft, and other participants in a discussion on the foundational role of digital infrastructure and the pathways available to the next generation of industry professionals.

Energy coordination between stakeholders was another area of focus. Gene Alessandrini, Senior Vice President of Energy & Location Strategy at CyrusOne, highlighted the need for closer collaboration between operators and utilities as demand profiles become more dynamic. Danielle Rossi, Global Director of Mission Critical Cooling at Trane, contributed to discussions on advancing thermal management strategies to support high-density AI environments.

From an investment perspective, Sharif Metwalli, Chief Financial Officer at Vantage Data Centers, examined how capital deployment strategies are evolving as developers and investors respond to increasing risks tied to power access, permitting timelines, and cost volatility. The conversation reflected a shift toward more disciplined investment, with a focus on projects that demonstrate long-term viability.

Beyond the formal sessions, DCD>Connect New York continued to serve as a key meeting point for the industry. Attendees spent significant time in one-on-one meetings and informal discussions, reinforcing the event’s role in facilitating partnerships, project development, and investment opportunities across the digital infrastructure ecosystem.

Looking ahead, the themes discussed in New York point to an industry entering a more execution-focused phase, where success will depend on the ability to align power, capital, and design with the realities of building infrastructure at scale.

Next, the industry will gather at DCD>Connect Virginia 2026 on November 3–4, 2026, bringing together more than 3,000 end users and specifiers across the cloud and colocation ecosystem to collaborate, build partnerships, and address key industry challenges. To learn more and register, visit DCD>Connect Virginia 2026 www.datacenterdynamics.com/en/dcdconnect-live/virginia/2026.

The post DCD>Connect New York 2026 Highlights Evolving Investment and Build Strategies appeared first on Data Center POST.

Originally posted on Sabey Data Centers.

Digital infrastructure serves as the crucial operating backbone for sectors like healthcare, finance, cloud platforms, and artificial intelligence. Because disruptions in these areas have immediate and widespread impacts that rarely stop at a single building, securing this infrastructure can no longer be treated merely as a perimeter issue. Instead, modern data centers must be recognized as dynamic, live operating environments where facility systems, infrastructure, software platforms, and customer expectations constantly intersect.

To address these complex needs, Sabey Data Centers integrates security directly into its overall operational resilience strategy. Rather than relying solely on visible physical barriers, this approach emphasizes disciplined processes, accountable operations, and careful environmental design that is supported over time. Protecting mission-critical infrastructure requires high visibility, consistency, and a deep security mindset that prioritizes long-term reliability, trust, and uptime.

Ultimately, customers are investing in confidence rather than just capacity. They need assurance that their provider truly understands the high operational stakes and weaves resilience into day-to-day execution. Sabey focuses on meeting this standard by continually building toward secure, resilient infrastructure that is tailored to the serious realities and demands of modern digital operations.

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The global data center heat exchanger market was valued at USD 2.8 billion in 2025 and is estimated to grow at a CAGR of 10.1% to reach USD 7.2 billion by 2035, according to a recent report by Global Market Insights Inc.

The industry is gaining strong momentum as advanced thermal management becomes critical to digital infrastructure performance. As artificial intelligence applications, cloud environments, and distributed computing architectures continue to scale, data center operators are prioritizing efficient and sustainable cooling technologies. Heat exchangers now play a central role in maintaining uptime, optimizing power usage effectiveness, and supporting higher rack densities. The market covers air-to-air, liquid-to-liquid, and refrigerant-based technologies integrated into rear-door systems, in-row platforms, and direct-to-chip liquid cooling architectures.

Increasing rack power densities exceeding 30-100 kW are accelerating the transition from legacy air-based models toward liquid and hybrid systems. The widespread deployment of AI processors and high-performance computing components is further elevating demand for compact plate and microchannel heat exchangers designed to improve thermal transfer while minimizing water and energy consumption. Growth is also supported by regulatory pressure, cost efficiency goals, and continuous innovation in hyperscale and colocation facilities.

The data center heat exchanger market from liquid-to-air heat exchangers segment accounted for 54% share in 2025 and is anticipated to grow at a CAGR of 9.7% between 2026 and 2035. This category represents the foundational cooling approach within many data centers, incorporating rear-door heat exchangers, chilled-water-based air handling systems, and integrated coil technologies. These solutions rely on water’s strong heat absorption capacity, transferring thermal energy from server exhaust air through engineered exchange surfaces before recirculating conditioned air back into the facility. Their established infrastructure compatibility continues to drive widespread adoption.

The air-cooled systems segment held a 55% share in 2025 and is forecast to grow at a CAGR of 9.8% through 2035. This segment includes direct expansion refrigerant technologies, chilled water air handlers, standalone chillers, and economizer-based free cooling configurations. Long-standing industry familiarity, proven reliability, and compatibility with raised-floor airflow designs have reinforced their dominance. Air-cooled platforms remain particularly effective for enterprise environments operating at 5-15 kW per rack, where installation costs and operational simplicity remain primary considerations.

United States data center heat exchanger market generated USD 782.1 million in 2025 and is estimated to grow at a CAGR of 9.4% during 2026-2035. Market leadership is supported by continued hyperscale development, strict energy efficiency mandates, and oversight from federal regulatory bodies. Rising demand for compute-intensive workloads and digital services is accelerating the shift toward high-performance cooling technologies, with liquid-to-air heat exchangers recognized for dependable and energy-efficient operation.

The competitive landscape includes key industry participants such as Airedale, Alfa Laval, CoolIT Systems, Eaton, Munters, Nortek Air, Rittal, Schneider Electric, STULZ, and Vertiv, all contributing to product innovation and global market expansion. Companies operating in the global data center heat exchanger market are strengthening their market position through technology innovation, strategic partnerships, and capacity expansion initiatives. Manufacturers are investing heavily in research and development to introduce advanced liquid cooling systems, compact microchannel designs, and energy-efficient hybrid solutions tailored for high-density data centers. Strategic collaborations with data center developers and infrastructure providers enable early integration of customized thermal management systems. Firms are also expanding manufacturing facilities and regional distribution networks to meet growing demand across North America and other high-growth regions. In addition, companies are focusing on sustainability-driven product enhancements that reduce water consumption and carbon emissions, aligning with regulatory expectations and enterprise ESG commitments.

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In ever-higher-density data center environments, unplanned downtime is costly. Whether it’s interrupting AI training workloads or impacting strict service-level agreements, the financial fallout can be severe.

Data center resilience is more important than ever.

Backup generator systems are a vital part of the sector’s resilience architecture. But while generator engines have been optimized and made more efficient, far less time has been spent engineering their starting systems – which often prove to be the weak point in backup generator reliability.

Now, a new ‘systems thinking’ approach is tackling this issue, while streamlining build time of the power distribution system.

Power Remains the Leading Cause of Outages

Data center outages are becoming less frequent, according to Uptime Institute’s most recent survey, but also more costly. However, the report also points out that, “Power remains the leading cause of impactful outages.” And when power fails, resilience depends on effective backup systems.

The Hidden Genset Weak Point 

Caterpillar and Cummins, along with NFPA, have all stated that the primary cause of standby generator failure is the starting battery system.

Too often, this stems from a ‘loose piece’ construction model. Batteries, chargers, redundancy components, racks, disconnects, and wiring are sourced as individual pieces from multiple vendors. These are then assembled on-site in a complex, costly, and high-risk integration processes.

Why Loose-Piece Construction is Riskier

Many starting system failures stem from this approach. Each component is viewed in isolation. Even if optimized to meet design specifications, it may not operate as efficiently when combined with the other elements.

This is especially true for batteries: the single greatest point of failure. Flooded lead-acid batteries are commonly chosen due to low cost and availability.

However, these batteries were designed for vehicle use, where they are only recharged by the alternator after cranking. In generator starting systems, on the other hand, the charge must be continuously maintained and the system kept on standby.

Under these conditions, battery life is severely curtailed, necessitating proactive replacement every 2-3 years. Yet even with regular maintenance, sudden, catastrophic failure still occurs.

Introducing Systems Thinking

Systems thinking is reshaping starting system design by tackling the underlying causes of failure. This means shifting attention from batteries in isolation to how they are charged and operate within the genset.

With this approach, all the components are engineered to work optimally together. It starts with selecting long-life, high-performance battery chemistries that need much less maintenance and are not harmed by constant float charging.

Smart chargers, hardened for harsh environments, monitor and respond to real-time conditions, optimizing the charging profile for the specific battery type, temperature and other factors.

Packaged engine starting systems house high-performance batteries with an integrated charger, best battery selectors, alternator and engine panel power redundancy, DC disconnects and racking, ensuring the greatest total system reliability in the smallest possible footprint.

Because these integrated systems are ordered as a single part, optimized and factory-tested by the manufacturer, they enable plug-and-play installation. Integration shifts from field conditions to a controlled factory environment, reducing points of failure while removing time-consuming, high-risk electrical work from the critical path.

A New Foundation for Resilience

Ever-increasing demand and AI-fueled growth have driven a technological transformation in chips, server racks, and cooling techniques. That evolution must now extend to a key element of data center resilience: backup generator starting systems.

Loose-piece construction no longer meets the resilience demands of today’s data center industry. When power fails, and genset reliability really counts, systems thinking and a new approach to starting system engineering are addressing this hidden weak point in data center resilience.

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About the Author 

Olen Scott, Chief Commercial Officer, SENS

Olen has over 30 years of experience leading high-growth businesses across global markets, from early-stage startups to Fortune 50 companies. At SENS, he oversees all sales, marketing, channels, and customer success, driving the company’s commercial strategy and growth.

The post Data Center Power Resilience: Systems Thinking for Reliability appeared first on Data Center POST.

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.

The post Why the Data Center Debate Isn’t About Data Centers appeared first on Data Center POST.

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.

The post Fire Prevention in Data Centers appeared first on Data Center POST.

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.

Want more digital infrastructure news? Stay in the know and subscribe to Data Center POST today!

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.

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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.

The post Empire Fiber Internet Expands into Pennsylvania’s Lehigh Valley appeared first on Data Center POST.

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.

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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.

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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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