Microsoft’s second Fairwater data center in Atlanta isn’t just “another big GPU shed.” It represents the other half of a deliberate architectural experiment: proving that two massive AI campuses, separated by roughly 700 miles, can operate as one coherent, distributed supercomputer. The Atlanta installation is the latest expression of Microsoft’s AI-first data center design: purpose-built for training and serving frontier models rather than supporting mixed cloud workloads. It links directly to the original Fairwater campus in Wisconsin, as well as to earlier generations of Azure AI supercomputers, through a dedicated AI WAN backbone that Microsoft describes as the foundation of a “planet-scale AI superfactory.” Inside a Fairwater Site: Preparing for Multi-Site Distribution Efficient multi-site training only works if each individual site behaves as a clean, well-structured unit. Microsoft’s intra-site design is deliberately simplified so that cross-site coordination has a predictable abstraction boundary—essential for treating multiple campuses as one distributed AI system. Each Fairwater installation presents itself as a single, flat, high-regularity cluster: Up to 72 NVIDIA Blackwell GPUs per rack, using GB200 NVL72 rack-scale systems. NVLink provides the ultra-low-latency, high-bandwidth scale-up fabric within the rack, while the Spectrum-X Ethernet stack handles scale-out. Each rack delivers roughly 1.8 TB/s of GPU-to-GPU bandwidth and exposes a multi-terabyte pooled memory space addressable via NVLink—critical for large-model sharding, activation checkpointing, and parallelism strategies. Racks feed into a two-tier Ethernet scale-out network offering 800 Gbps GPU-to-GPU connectivity with very low hop counts, engineered to scale to hundreds of thousands of GPUs without encountering the classic port-count and topology constraints of traditional Clos fabrics. Microsoft confirms that the fabric relies heavily on: SONiC-based switching and a broad commodity Ethernet ecosystem to avoid vendor lock-in and accelerate architectural iteration. Custom network optimizations, such as packet trimming, packet spray, high-frequency telemetry, and advanced congestion-control mechanisms, to prevent collective

Land & Expand is Data Center Frontier’s periodic roundup of notable North American data center development activity, tracking the newest sites, land plays, retrofits, and hyperscale campus expansions shaping the industry’s build cycle. October delivered a steady cadence of announcements, with several megascale projects advancing from concept to commitment. The month was defined by continued momentum in OpenAI and Oracle’s Stargate initiative (now spanning multiple U.S. regions) as well as major new investments from Google, Meta, DataBank, and emerging AI cloud players accelerating high-density reuse strategies. The result is a clearer picture of how the next wave of AI-first infrastructure is taking shape across the country. Google Begins $4B West Memphis Hyperscale Buildout Google formally broke ground on its $4 billion hyperscale campus in West Memphis, Arkansas, marking the company’s first data center in the state and the anchor for a new Mid-South operational hub. The project spans just over 1,000 acres, with initial site preparation and utility coordination already underway. Google and Entergy Arkansas confirmed a 600 MW solar generation partnership, structured to add dedicated renewable supply to the regional grid. As part of the launch, Google announced a $25 million Energy Impact Fund for local community affordability programs and energy-resilience improvements—an unusually early community-benefit commitment for a first-phase hyperscale project. Cooling specifics have not yet been made public. Water sourcing—whether reclaimed, potable, or hybrid seasonal mode—remains under review, as the company finalizes environmental permits. Public filings reference a large-scale onsite water treatment facility, similar to Google’s deployments in The Dalles and Council Bluffs. Local governance documents show that prior to the October announcement, West Memphis approved a 30-year PILOT via Groot LLC (Google’s land assembly entity), with early filings referencing a typical placeholder of ~50 direct jobs. At launch, officials emphasized hundreds of full-time operations roles and thousands

As the global data center industry races through its most frenetic build cycle in history, one question continues to define the market’s mood: is this the peak of an AI-fueled supercycle, or the beginning of a structurally different era for digital infrastructure? For Green Street Managing Director and Head of Global Data Center and Tower Research David Guarino, the answer—based firmly on observable fundamentals—is increasingly clear. Demand remains blisteringly strong. Capital appetite is deepening. And the very definition of a “data center market” is shifting beneath the industry’s feet. In a wide-ranging discussion with Data Center Frontier, Guarino outlined why data centers continue to stand out in the commercial real estate landscape, how AI is reshaping underwriting and development models, why behind-the-meter power is quietly reorganizing the U.S. map, and what Green Street sees ahead for rents, REITs, and the next wave of hyperscale expansion. A ‘Safe’ Asset in an Uncertain CRE Landscape Among institutional investors, the post-COVID era was the moment data centers stepped decisively out of “niche” territory. Guarino notes that pandemic-era reliance on digital services crystallized a structural recognition: data centers deliver stable, predictable cash flows, anchored by the highest-credit tenants in global real estate. Hyperscalers today dominate new leasing and routinely sign 15-year (or longer) contracts, a duration largely unmatched across CRE categories. When compared with one-year apartment leases, five-year office leases, or mall anchor terms, the stability story becomes plain. “These are AAA-caliber companies signing the longest leases in the sector’s history,” Guarino said. “From a real estate point of view, that combination of tenant quality and lease duration continues to position the asset class as uniquely durable.” And development returns remain exceptional. Even without assuming endless AI growth, the math works: strong demand, rising rents, and high-credit tenants create unusually predictable performance relative to

In a coordinated leadership transition this fall, Ryan Mallory has stepped into the role of CEO at Flexential, succeeding Chris Downie. The move, described as thoughtful and planned, signals not a shift in direction, but a reinforcement of the company’s core strategy, with a sharpened focus on the unprecedented opportunities presented by the artificial intelligence revolution. In an exclusive interview on the Data Center Frontier Show Podcast, Mallory outlined a confident vision for Flexential, positioning the company at the critical intersection of enterprise IT and next-generation AI infrastructure. “Flexential will continue to focus on being an industry and market leader in wholesale, multi-tenant, and interconnection capabilities,” Mallory stated, affirming the company’s foundational strengths. His central thesis is that the AI infrastructure boom is not a monolithic wave, but a multi-stage evolution where Flexential’s model is uniquely suited for the emerging “inference edge.” The AI Build Cycle: A Three-Act Play Mallory frames the AI infrastructure market as a three-stage process, each lasting roughly four years. We are currently at the tail end of Stage 1, which began with the ChatGPT explosion three years ago. This phase, characterized by a frantic rush for capacity, has led to elongated lead times for critical infrastructure like generators, switchgear, and GPUs. The capacity from this initial build-out is expected to come online between late 2025 and late 2026. Stage 2, beginning around 2026 and stretching to 2030, will see the next wave of builds, with significant capacity hitting the market in 2028-2029. “This stage will reveal the viability of AI and actual consumption models,” Mallory notes, adding that air-cooled infrastructure will still dominate during this period. Stage 3, looking ahead to the early 2030s, will focus on long-term scale, mirroring the evolution of the public cloud. For Mallory, the enduring nature of this build cycle—contrasted

A Platform Built for Both Colo and AI Density The combined Evoque–Cyxtera platform entered the market with hundreds of megawatts of installed capacity and a clear runway for expansion. That scale positioned Centersquare to offer both traditional enterprise colocation and the higher-density, AI-ready footprints increasingly demanded through 2024 and 2025. The addition of these ten facilities demonstrates that the consolidation strategy is gaining traction, giving the platform more owned capacity to densify and more regional optionality as AI deployment accelerates. What’s in the $1 Billion Package — and Why It Matters 1) Lease-to-Own Conversions in Boston & Minneapolis Centersquare’s decision to purchase two long-operated but previously leased sites in Boston and Minneapolis reduces long-term occupancy risk and gives the operator full capex control. Owning the buildings unlocks the ability to schedule power and cooling upgrades on Centersquare’s terms, accelerate retrofits for high-density AI aisles, deploy liquid-ready thermal topologies, and add incremental power blocks without navigating landlord approval cycles. This structural flexibility aligns directly with the platform’s “AI-era backbone” positioning. 2) Eight Additional Data Centers Across Six Metros The acquisitions broaden scale in fast-rising secondary markets—Tulsa, Nashville, Raleigh—while deepening Centersquare’s presence in Dallas and expanding its Canadian footprint in Toronto and Montréal. Dallas remains a core scaling hub, but Nashville and Raleigh are increasingly important for enterprises modernizing their stacks and deploying regional AI workloads at lower cost and with faster timelines than congested Tier-1 corridors. Tulsa provides a network-adjacent, cost-efficient option for disaster recovery, edge aggregation, and latency-tolerant compute. In Canada, Toronto and Montréal offer strong enterprise demand, attractive economics, and grid advantages—including Québec’s hydro-powered, low-carbon energy mix—that position them well for AI training spillover and inference workloads requiring reliable, competitively priced power. 3) Self-Funded With Cash on Hand In the current rate environment, funding the entire $1 billion package

Constellation proposes to begin with 1.5 GW of fast-tracked projects, including 800 MW of battery energy storage and 700 MW of new natural gas generation to address short-term reliability needs. The remaining 4.3 GW represents longer-term investment at the Calvert Cliffs Clean Energy Center: extending both units for an additional 20 years beyond their current 2034 and 2036 license expirations, implementing a 10% uprate that would add roughly 190 MW of output, and pursuing 2 GW of next-generation nuclear at the existing site. For Maryland, a state defined by a dense I-95 fiber corridor, accelerating data center buildout, and rising AI-driven load, the plan could be transformative. If Constellation moves from “option” to “program,” the company estimates that 70% of the state’s electricity supply could come from clean energy sources, positioning Maryland as a top-tier market for 24/7 carbon-free power. TerraPower’s Natrium SMR Clears a Key Federal Milestone On Oct. 23, the Nuclear Regulatory Commission issued the final environmental impact statement (FEIS) for TerraPower’s Natrium small modular reactor in Kemmerer, Wyoming. While not a construction permit, FEIS completion removes a major element of federal environmental risk and keeps the project on track for the next phase of NRC review. TerraPower and its subsidiary, US SFR Owner, LLC, originally submitted the construction permit application on March 28, 2024. Natrium is a sodium-cooled fast reactor producing roughly 345 MW of electric output, paired with a molten-salt thermal-storage system capable of boosting generation to about 500 MW during peak periods. The design combines firm baseload power with flexible, dispatchable capability, an attractive profile for hyperscalers evaluating 24/7 clean energy options in the western U.S. The project is part of the DOE’s Advanced Reactor Demonstration Program, intended to replace retiring coal capacity in PacifiCorp’s service territory while showcasing advanced fission technology. For operators planning multi-GW