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Author: Deepak Jain

  • Google Open-Sources a Liquid-to-Air Cooling Sidecar for Air-Cooled Data Centers

    Google Open-Sources a Liquid-to-Air Cooling Sidecar for Air-Cooled Data Centers

    Google has unveiled an open-source liquid-to-air cooling sidecar designed for air-cooled data center environments, as reported by Data Center Dynamics on June 17, 2026. The design targets one of the most pressing constraints in the industry: modern AI accelerators increasingly require direct liquid cooling, while the vast majority of existing data center floor space was built to move heat with air alone.

    A sidecar of this type is a heat-exchanger cabinet that sits beside a rack of liquid-cooled servers, circulating coolant through the chips in a closed loop and then rejecting that heat into the room’s existing airflow — no facility water piping required. By publishing the design openly, Google is inviting vendors and operators to build and adapt it rather than keeping it proprietary.

    Executive Summary

    The announcement matters less for what the hardware is than for where it lets liquid cooling go. Direct-to-chip liquid cooling has become effectively mandatory for the densest AI training hardware, but deploying it normally requires facility-level infrastructure — coolant distribution units, piping loops, and water connections that most operating data centers simply do not have. A liquid-to-air sidecar sidesteps that requirement: the liquid loop stays local to the rack, and the building’s existing air-handling systems carry the heat away as they always have.

    That makes this a retrofit play. Enterprises, colocation tenants, and smaller operators sitting on air-cooled capacity gain a path to host at least some liquid-cooled equipment without construction projects. It is also a continuation of Google’s recent posture of contributing cooling designs to the open hardware ecosystem rather than treating them as competitive secrets — a bet that standardizing the plumbing layer accelerates the whole market Google’s cloud and AI businesses depend on.

    The report available at the time of writing is brief, and the announcement as covered leaves key engineering and availability details unstated — including the design’s cooling capacity, its publication venue and license, and whether it reflects hardware Google runs in production. Those specifics will determine whether this is a broadly useful reference design or a niche one.

    The Retrofit Gap Is the Industry’s Quiet Bottleneck

    Headlines about AI data centers focus on new gigawatt-scale campuses, but most of the world’s installed data center capacity is older, air-cooled space designed for racks drawing 5 to 15 kilowatts. Current AI server racks can draw many times that, and the chips inside them ship with cold plates that expect liquid, not airflow. Operators of existing facilities face an unattractive menu: leave AI workloads to someone else, undertake disruptive plumbing retrofits in live buildings, or find a bridge technology.

    Liquid-to-air sidecars are that bridge. Because the liquid never leaves the immediate vicinity of the rack, the facility itself does not need water loops, external coolant distribution plants, or new mechanical rooms. The trade-off is physics: the room’s air systems still have to absorb every watt the sidecar rejects, so total rack density remains bounded by the building’s air-handling and power envelope. A sidecar extends the life of air-cooled space; it does not turn a legacy building into a frontier AI facility.

    Why Give the Design Away?

    Google has form here. The company has run liquid-cooled custom TPU accelerators internally since roughly 2018, and in 2025 it announced it would contribute a production coolant distribution unit design to the Open Compute Project, the industry body through which hyperscalers share hardware specifications. Open-sourcing a sidecar fits the same logic: cooling hardware is not where Google differentiates, but an immature, fragmented cooling supply chain slows everyone — including Google and the customers of its cloud business.

    Open designs give equipment manufacturers a common reference to build against, which tends to lower prices, improve interoperability, and widen the vendor pool. For Google there is also a soft-power dividend: hyperscaler-authored designs shape industry standards, and the ecosystem that grows up around them tends to stay compatible with the author’s infrastructure choices. None of that makes the contribution less useful — but it is worth understanding open-source hardware as strategy, not charity.

    Winners, Losers, and the Honest Limits

    The clearest beneficiaries are operators of existing air-cooled facilities — enterprise server rooms, regional colocation providers, and edge sites — who gain an on-ramp to liquid-cooled hardware without capital construction. Cooling-equipment manufacturers get a design they can productize; some may welcome the demand signal, while vendors selling proprietary sidecar and rear-door heat exchanger products now face an open alternative that could compress margins.

    The honest caveat is that the announcement, as reported, is a design release, not a product with published performance data. Until the specification’s capacity, tested configurations, and licensing terms are public and third parties have built against it, the practical impact is prospective. Open hardware contributions have a mixed track record: some become de facto standards, others languish without a manufacturing ecosystem. Which path this design takes depends on details the initial coverage does not yet supply.

    Background

    Google is one of the world’s largest data center operators and has cooled its custom TPU AI accelerators with liquid since roughly 2018 — years before liquid cooling became an industry-wide necessity. In 2025 it began contributing pieces of that cooling stack to the open hardware ecosystem, announcing a production coolant distribution unit design for the Open Compute Project, the body through which hyperscalers share server and infrastructure specifications.

    The backdrop is a market-wide squeeze: AI hardware demand is rising far faster than new liquid-ready facilities can be built, leaving a large installed base of air-cooled data centers unable to host the densest equipment. Bridge technologies that bring liquid cooling into air-cooled buildings — sidecars and rear-door heat exchangers among them — have become one of the fastest-moving segments of data center engineering.

    Source: Google unveils new open-source liquid-to-air cooling sidecar for air-cooled environments — Data Center Dynamics report, June 17, 2026, on Google’s open-source cooling hardware release.

  • FERC Pushes Grid Operators to Overhaul Data Center Interconnection Rules

    FERC Pushes Grid Operators to Overhaul Data Center Interconnection Rules

    The Federal Energy Regulatory Commission (FERC), the top US energy regulator, is pressing the nation’s grid operators to overhaul the rules governing how large data centers connect to and draw power from the electric grid, according to a Reuters report dated June 17, 2026. The push targets the regional transmission organizations that manage most of the US high-voltage grid, and lands in the middle of an unprecedented wave of AI-driven electricity demand.

    Executive Summary

    According to Reuters, FERC is urging grid operators to rewrite their rules for connecting large data center loads — the procedures, studies, and cost arrangements that determine how quickly a gigawatt-scale computing facility can plug into the transmission system and on what terms. The report frames this as a directive from the regulator to the regional grid operators rather than a finished rule, which means the substance will be worked out in filings, stakeholder processes, and likely litigation over the months ahead.

    Why it matters: interconnection has become the single biggest bottleneck in the AI infrastructure buildout. Chips can be bought and buildings can be raised in quarters; grid connections for very large loads are quoted in years. Whoever writes the rules for large-load interconnection — how costs are allocated, whether data centers can co-locate with power plants, and what reliability obligations big loads must accept — will effectively set the pace and geography of AI data center construction in the United States. A FERC push to standardize those rules is therefore one of the most consequential regulatory developments the industry has seen this cycle, even before its details are settled.

    Interconnection Is Now the Gating Factor for AI Capacity

    For most of the grid’s history, the hard problem was connecting new generators; large customer loads arrived gradually and were absorbed through routine utility planning. AI has inverted that. Individual data center campuses now request hundreds of megawatts — in some cases more than a gigawatt, roughly the draw of a mid-sized city — and they request it on construction timelines the traditional load-forecasting process was never designed to handle. Grid operators have responded with a patchwork: some regions created special large-load study tracks, others applied generator-style queue rules to loads, and others negotiated case by case. A federal push to overhaul and presumably harmonize these rules is a recognition that the patchwork itself has become a source of delay and dispute.

    For data center developers and their tenants, the near-term effect of any rule rewrite is uncertainty, but the medium-term prize is predictability. A standardized process — with defined study timelines, transparent cost estimates, and clear rules on what a large load must commit to — would let operators of digital infrastructure make siting decisions on engineering and economics rather than on which utility territory offers the friendliest ad hoc deal.

    The Fights Underneath: Co-Location, Cost Allocation, and Curtailment

    Three unresolved disputes sit beneath any large-load rule overhaul. First, co-location — siting a data center directly beside a power plant and buying its output behind the meter. The arrangement can bypass years of transmission upgrades, but regulators and utilities have questioned whether such configurations pay their fair share for the grid that still backs them up; FERC itself has been wrestling publicly with co-location frameworks since high-profile disputes over data centers sited at nuclear plants in the PJM region. Second, cost allocation: when a multi-hundred-megawatt load triggers new transmission lines or substations, someone pays — the developer, the utility’s general ratepayer base, or some blend. Consumer advocates in several states have argued that ordinary households risk subsidizing AI growth; developers counter that they routinely fund dedicated upgrades. Third, flexibility and curtailment: grid operators increasingly want large loads to accept interruption or demand-response obligations during system stress in exchange for faster connection. Each of these is a genuine economic contest between reasonable positions, and the Reuters report does not indicate which way FERC is leaning on any of them.

    Winners, Losers, and the Federal–State Seam

    If the overhaul produces faster, standardized large-load interconnection, the clearest winners are hyperscale cloud and AI companies with capital ready to deploy, and the transmission-rich regions able to absorb them. Utilities gain too, if the rules convert speculative or duplicative connection requests — a real problem, since developers often file in multiple territories for the same project — into firm, financially committed ones. The pressure lands on grid operators, which must rewrite tariffs under regulatory deadline while managing record demand growth, and potentially on smaller data center operators, if new rules impose financial-commitment thresholds sized for hyperscalers.

    There is also a jurisdictional seam worth watching. FERC governs wholesale markets and the interstate transmission system, but retail electric service and most siting decisions belong to the states, and Texas’s ERCOT grid sits largely outside FERC’s reach altogether. A federal overhaul can standardize how regional operators study and connect big loads, but it cannot by itself resolve state-level fights over who pays or where facilities are built. Buyers should expect a more legible federal process layered over a still-fragmented state landscape, not a single national rulebook.

    Background

    FERC, created in its modern form in 1977, oversees the interstate transmission system and the wholesale power markets run by regional grid operators. Its interconnection rules historically focused on generators — culminating in a 2023 queue-reform order aimed at the enormous backlog of power plants awaiting connection. Large customer loads, by contrast, were left mostly to individual utilities and states, an arrangement that held until AI demand broke it.

    From roughly 2024 onward, gigawatt-scale data center requests, contested co-location deals at nuclear plants in the PJM region, and warnings from grid operators about record demand growth pushed large-load interconnection onto FERC’s docket. The June 2026 push reported by Reuters is the continuation of that arc: the federal regulator moving from case-by-case dispute resolution toward pressing for systematic rules on how the grid absorbs the AI buildout.

    Source: Top US energy regulator pushes grids to overhaul data center power rules — Reuters, June 17, 2026, reporting FERC’s push for grid operators to rewrite large-load interconnection rules.

  • Offshore Nuclear Barges Eye California Ports and Data Centers

    Offshore Nuclear Barges Eye California Ports and Data Centers

    A concept for floating, offshore nuclear power barges is being pitched as a way to supply electricity to California ports and data centers, with proponents arguing that siting reactors in federal waters could avoid the state’s long-standing prohibition on new onshore nuclear plants. Fortune reported the proposal on June 16, 2026.

    Executive Summary

    The pitch pairs two trends: a resurgent interest in small, modular nuclear reactors and an acute shortage of firm, carbon-free power for AI-era data centers and electrified ports. By mounting reactors on barges moored offshore, developers argue they can deliver power directly to coastal customers behind the meter — meaning the electricity flows to the buyer without traversing the public grid — while operating under federal rather than state jurisdiction.

    The stakes are significant for California, where data center operators and port electrification programs are competing for the same constrained grid capacity, and where the state’s 1976 moratorium on new nuclear construction has effectively frozen a category of firm, low-carbon generation. Whether an offshore barge genuinely sits outside that moratorium — legally, politically, and practically — is the central question the proposal raises.

    Why Offshore, and Why Now

    The appeal is straightforward on paper. California data center demand is rising with generative AI workloads, and the state’s largest ports — Los Angeles, Long Beach, and Oakland — are under pressure to electrify cargo handling and shore power for docked ships. Both need round-the-clock electricity that solar and wind alone cannot provide without significant storage. A barge-mounted reactor delivered to a mooring can, in principle, be built in a shipyard, towed into place, and connected to a single large customer, compressing the multi-year permitting and construction timelines that plague land-based projects.

    Offshore siting also reframes the political map. State moratoria on new nuclear plants apply on land; federal waters begin three nautical miles from shore in most of California. A vessel-based reactor could plausibly be regulated primarily by federal agencies — the Nuclear Regulatory Commission and, for a marine platform, the Coast Guard — rather than the state. That is the crux of the sidestep argument, and it will be tested by lawyers long before it is tested by engineers.

    The Behind-the-Meter Economics

    Behind-the-meter power arrangements let a generator sell electricity directly to a co-located customer, bypassing utility tariffs and, often, transmission queues that now stretch years. For hyperscale data center operators, that shortcut has become the single most valuable feature of any new generation project, which is why they have signed deals for restarted nuclear plants and are exploring small modular reactors on their own campuses. An offshore barge extends the same logic to sites that lack the land for on-site generation.

    The economics still have to close. Marine nuclear platforms carry costs that land plants do not: marinization of equipment, mooring and undersea cable systems, corrosion management, and specialized crews. They also inherit the industry’s chronic problem — first-of-a-kind small reactors have consistently come in above their initial cost estimates. Whether the shipyard-build efficiencies proponents cite can offset those headwinds is unproven at commercial scale.

    Regulation, Siting, and the Politics of a Workaround

    Framing a project as a jurisdictional workaround invites the jurisdiction being worked around to push back. California has other levers even if the reactor sits in federal waters: the California Coastal Commission reviews activities affecting the coastal zone, cable landings require state and local permits, and the electricity buyer on shore is a regulated entity. A project marketed primarily as a way to avoid state law is likely to draw sharper scrutiny than one that engages the state on its merits.

    There are also legitimate questions to ask of critics as well as proponents. Opposition to nuclear in California has historically blended safety, seismic, and waste concerns with broader anti-industrial sentiment, and the coalition that upheld the 1976 moratorium is not monolithic. A fair debate requires pressing both sides: proponents on safety, security, and decommissioning of a marine reactor; opponents on what alternative firm, low-carbon supply they propose for the same coastal loads on the same timeline.

    Background

    California enacted its moratorium on new nuclear construction in 1976, tying future approvals to a federal solution for high-level radioactive waste that has not materialized. The state’s last operating commercial nuclear plant, Diablo Canyon, was scheduled to retire but received a life extension amid grid reliability concerns. Meanwhile, AI-driven data center demand and port electrification are straining coastal grid capacity.

    Interest in small modular reactors and factory-built nuclear designs has revived globally, with hyperscale technology companies signing power deals for restarted plants and exploring on-site reactors. Marine nuclear propulsion has decades of naval history, and Russia has operated a civilian floating nuclear plant since 2020, but no comparable commercial offshore reactor has been deployed in U.S. waters.

    Source: Offshore nuclear barges could power ports and data centers—starting with California, where nuclear is banned — Fortune reports on a proposal to moor small reactors offshore to serve California ports and data centers.

  • PJM Says Its Reformed Interconnection Process Is Delivering Results

    PJM Says Its Reformed Interconnection Process Is Delivering Results

    PJM Interconnection, the regional grid operator serving 13 states and the District of Columbia, announced on June 16, 2026 via its Inside Lines publication that its overhauled generator interconnection process is delivering results. The announcement, titled “New Interconnection Process Delivers,” signals that the reformed study framework — approved by federal regulators in 2022 to replace PJM’s clogged first-come, first-served queue — is now moving projects through review at a pace the old system could not match.

    Executive Summary

    Interconnection is the process by which a new power plant, battery, or other resource gets studied and approved to plug into the transmission grid. For years it has been one of the most stubborn bottlenecks in American energy: PJM’s legacy queue accumulated thousands of speculative and serious projects alike, with study timelines stretching years and many projects withdrawing before ever being built. In 2022, PJM won federal approval to replace that serial queue with a cluster-based, “first-ready, first-served” model that studies projects in batches and requires financial commitments up front to weed out placeholders.

    PJM’s declaration that the new process “delivers” matters because the region is simultaneously facing surging electricity demand — driven prominently by data center growth in markets like Northern Virginia, the largest data center concentration in the world — alongside the retirement of older generation. Whether new supply can be connected fast enough is now a first-order question for grid reliability, electricity prices, and the pace of digital infrastructure buildout.

    The announcement is a progress marker rather than a finish line: clearing studies is a necessary step, but megawatts only matter once projects secure equipment, financing, and construction — stages the interconnection process does not control.

    Why the Queue Became the Grid’s Chokepoint

    Under the old regime, PJM studied interconnection requests one at a time in the order received. That design worked when a handful of large plants applied each year, but it collapsed under the modern development model, in which developers file many speculative requests — often for renewables and storage — and decide later which to build. Each withdrawal forced restudies of everyone behind it, compounding delays. The result was a backlog measured in years, and a paradox: enormous volumes of proposed generation on paper, with comparatively little of it reaching commercial operation.

    The reformed process attacks this structurally. Projects are studied together in clusters, network upgrade costs are shared across the cluster rather than assigned by queue position, and developers must post deposits and demonstrate site control to stay in. “First-ready, first-served” replaces “first-in-line,” which changes developer incentives from claiming a place early to being genuinely prepared. This is a governance fix as much as an engineering one — and PJM’s announcement suggests the incentive redesign is doing its job.

    The Collision With Data Center Demand

    PJM’s territory includes the densest data center market on the planet, and the region’s load forecasts have swung from decades of flat demand to sustained growth. That reversal makes interconnection speed a commercial issue for the digital infrastructure industry, not just a utility concern: a data center campus is only as viable as the power that can reach it, and new generation stuck in study limbo tightens capacity markets and pushes up costs for every large power buyer.

    For data center operators, colocation providers, and their customers, a functioning interconnection pipeline is upstream of everything — site selection, lease pricing, and expansion timelines. If PJM can convert its backlog into energized projects, it relieves pressure on the supply side of an equation that has recently been dominated by demand headlines. If it cannot, the alternatives — demand curtailment, delayed retirements of aging plants, or higher capacity prices — all carry costs that eventually land on tenants and end users.

    From Cleared Studies to Steel in the Ground

    A cleared study is not a power plant. Projects that emerge from PJM’s process with signed interconnection agreements still face equipment lead times — transformers and high-voltage gear remain constrained industry-wide — plus financing, permitting, and supply chain realities. Historically, a large share of queued projects never get built, so the headline metric that matters over time is commercial operation dates, not study completions.

    It is also worth noting the source here: this is PJM’s own publication reporting on PJM’s own reform. That does not make the claim wrong — grid operators publish detailed queue statistics that independent analysts scrutinize closely — but a self-assessment titled “Delivers” should be read as a progress report from the institution being measured. The durable test is whether independent queue data shows sustained throughput across successive study cycles, and whether new entrants, not just legacy backlog projects, move through on predictable timelines.

    Background

    PJM Interconnection, headquartered in Pennsylvania, is the largest regional transmission organization in the United States, coordinating the grid and wholesale power markets from the Mid-Atlantic into the Midwest. Like other U.S. grid operators, PJM saw its interconnection queue swell dramatically through the early 2020s as renewable, storage, and gas projects applied faster than its serial study process could handle, prompting a FERC-approved overhaul in 2022 that shifted to clustered, readiness-based studies and a phased transition to work off the backlog.

    The reform arrived just as PJM’s demand outlook inverted. After years of flat load, forecasts turned sharply upward on data center growth and electrification, while older coal and gas plants moved toward retirement — making the speed at which new resources can connect a central reliability and cost question for the region, and a closely watched variable for the digital infrastructure industry that depends on PJM power.

    Source: New Interconnection Process Delivers — PJM Inside Lines, PJM’s June 16, 2026 self-published update on the performance of its reformed generator interconnection process.

  • Anubis Ransomware Hit on Adriatic Port Authority Exposes Maritime OT Risk

    Anubis Ransomware Hit on Adriatic Port Authority Exposes Maritime OT Risk

    Cybersecurity firm Resecurity has published research detailing a ransomware attack by the Anubis group against an Adriatic Port Authority, as reported by Industrial Cyber on June 16, 2026. The disclosure is being framed as a detailed look at how ransomware operators are reaching into maritime critical infrastructure — a sector where information technology (IT) systems and operational technology (OT, the systems that control physical processes like cranes, gates, and cargo handling) are increasingly intertwined.

    Executive Summary

    According to the report, threat-intelligence firm Resecurity has documented an intrusion attributed to Anubis — a ransomware-as-a-service operation that surfaced in underground markets in late 2024 and drew attention for pairing conventional encryption with a destructive file-wiping capability — against a port authority on the Adriatic coast. Port authorities are the public bodies that govern harbor operations, vessel traffic, and often the digital systems that commercial terminals depend on, which makes them an unusually consequential ransomware target.

    The significance is less the individual incident than what it illustrates: ports sit at the junction of national logistics, customs, energy imports, and military mobility, and a single compromised authority can ripple across all of them. Vendor research that documents such an attack in technical detail is valuable to defenders — though, as with any single-vendor disclosure, the claims that matter most (scope of access, operational impact, and how the intrusion happened) deserve independent confirmation, and the public reporting available at publication is thin on those specifics.

    Why Ports Are Ransomware’s Ideal Target

    Modern ports run on software to a degree that surprises outsiders. Terminal operating systems schedule every container move; gate systems decide which trucks enter; berth management coordinates vessel arrivals; customs and port-community platforms link the authority to shippers, freight forwarders, and government agencies. When ransomware locks those systems, cargo does not merely slow — it physically stops, because cranes and yard equipment have nowhere to be told to go. That is why the sector’s precedents are so costly: the 2017 NotPetya incident forced Maersk to rebuild its global IT estate at a cost the company put in the hundreds of millions of dollars, and ransomware halted container operations at Japan’s Port of Nagoya in 2023. An Adriatic port authority fits the same profile: high downtime costs, public-sector budget constraints, and a web of third-party connections that widens the attack surface.

    The OT dimension raises the stakes further. Even when attackers only encrypt IT systems, operators frequently shut down OT as a precaution because the boundary between the two is porous. The practical lesson for infrastructure operators of every kind — ports, data centers, utilities — is that segmentation between business networks and control networks is not a compliance checkbox; it is the difference between an expensive IT incident and a physical-operations outage.

    Anubis and the Economics of Destructive Ransomware

    Anubis is a relatively young ransomware-as-a-service brand — a model in which core developers lease their malware and infrastructure to affiliates who conduct the actual intrusions in exchange for a revenue share. What set Anubis apart in earlier security-industry reporting was a so-called wipe mode: the ability to destroy file contents outright rather than merely encrypt them. That capability changes the victim’s calculus. Classic ransomware is, in a grim sense, a negotiation with a counterparty that wants its decryptor to work; a wiper-equipped operator can credibly threaten permanent destruction, which increases pressure to pay quickly and raises the ceiling of potential damage if talks collapse.

    For a critical-infrastructure victim, that threat profile pushes the incident out of the purely financial category and toward something closer to sabotage risk. It also strengthens the case for offline, regularly tested backups — the one control that removes most of a wiper’s leverage — and for incident-response planning that assumes data may be unrecoverable from the attacker regardless of payment.

    What Vendor Research Does — and Doesn’t — Establish

    This disclosure comes from Resecurity, a commercial threat-intelligence firm, relayed through trade press. Vendor research is a legitimate and often essential channel — private firms frequently see intrusion details that victims and governments do not publish — but it also serves a marketing function, and readers should hold it to the same evidentiary standard as any other claim. The fair questions cut in every direction: Has the affected port authority confirmed the incident? Do the technical indicators trace to Anubis with high confidence, or by resemblance to known tooling? Was operational technology actually touched, or is OT exposure an inference from network architecture? The public reporting available at the time of writing — an aggregated headline and summary — does not settle any of these, and it would be a mistake to treat the incident’s most dramatic possible reading as established fact.

    The Regulatory Tide Meets the Waterline

    If the affected authority sits in an EU member state — as most Adriatic port authorities do — the incident lands squarely inside the NIS2 directive’s remit, the EU regime that designates ports as essential entities and imposes incident-reporting deadlines and management-level accountability for cyber risk. The International Maritime Organization has likewise required cyber risk to be addressed in ship and port safety-management systems since 2021. An incident like this one becomes a live test of whether those frameworks produce faster disclosure and better resilience in practice, or whether public understanding of critical-infrastructure attacks continues to depend on third-party security researchers publishing what victims will not.

    Background

    Anubis appeared in cybercrime markets around late 2024 as a ransomware-as-a-service brand and was flagged by multiple security researchers in 2025 for combining data-theft extortion with an optional file-destruction mode — an escalation from the encrypt-and-negotiate model that has dominated ransomware for a decade. Maritime targets have figured in ransomware history since NotPetya crippled Maersk in 2017, and attacks on the ports of Lisbon (2022) and Nagoya (2023) demonstrated that both port authorities and terminal operators are viable victims.

    The Adriatic coastline hosts significant EU trade gateways in Italy, Slovenia, and Croatia, making its port authorities essential entities under the EU’s NIS2 cybersecurity directive. Resecurity, the firm behind this disclosure, is a commercial threat-intelligence company that regularly publishes intrusion research on ransomware groups and critical-infrastructure targeting.

    Source: Resecurity details Anubis ransomware attack on Adriatic Port Authority, exposing maritime infrastructure risks — Industrial Cyber, reporting on Resecurity threat research into a ransomware intrusion at an Adriatic port authority, published June 16, 2026.

  • Google Retrofits Liquid Cooling Into Legacy Data Halls: Why It Matters

    Google Retrofits Liquid Cooling Into Legacy Data Halls: Why It Matters

    A June 16, 2026 report from the Data Center Richness newsletter on Substack says Google is bringing liquid cooling into its legacy data halls — retrofitting existing, originally air-cooled facilities rather than confining liquid cooling to newly built AI campuses. The report positions the move as a marker that liquid cooling is graduating from a specialty technology for new AI construction into something operators must engineer into buildings that already exist.

    Executive Summary

    According to the report, Google — one of the world’s largest data center operators — is extending liquid cooling beyond greenfield construction and into older data halls in its existing fleet. Liquid cooling circulates fluid close to (or directly across) hot silicon instead of relying on chilled air, and it has become the default answer for the extreme heat produced by modern AI accelerators.

    The significance is less about any single facility and more about direction of travel. Until recently, the industry’s working assumption was that liquid cooling arrives with new buildings designed around it, while legacy halls carry on with air. If a hyperscaler of Google’s scale is instead threading liquid into buildings that were never designed for it, that suggests demand for accelerator capacity is outrunning the pace of new construction — and that existing real estate, with its already-secured power and grid connections, is too valuable to leave running at air-cooled densities.

    One caveat up front: this is a single analyst-newsletter report, not a detailed Google engineering disclosure. The headline claim is clear; the scope, sites, methods, and timeline behind it are not spelled out in the source material available.

    From Greenfield Exception to Fleet-Wide Expectation

    For most of the past two decades, data center cooling meant moving air: chilled air pushed through raised floors or hot-aisle containment, absorbing heat from servers and carrying it away. Liquid cooling — whether direct-to-chip cold plates that sit on processors or full immersion of hardware in dielectric fluid — was a niche reserved for supercomputers. AI changed the math. Modern accelerator racks concentrate far more heat in far less space than air can economically remove, so new AI facilities are now routinely designed liquid-first.

    The retrofit story flips the remaining assumption. If liquid cooling only lived in new builds, older halls would gradually become second-class assets, suitable only for lighter workloads. Retrofitting says the opposite: the industry’s installed base is being upgraded in place. For an operator with Google’s fleet size, even partial retrofits could unlock meaningful accelerator capacity without waiting years for new construction.

    Why Retrofit When You Can Build New? Power and Time

    The economics here are straightforward even without disclosed figures. The scarcest resources in data center development today are grid power and time — utility interconnections and permits for new campuses can take years in major markets. A legacy data hall already has land, a building, a grid connection, and delivered megawatts. Converting some of that hall to liquid cooling lets an operator redeploy existing power toward denser, higher-value AI capacity on a much shorter clock than greenfield construction allows.

    Retrofits are not free or trivial, though. Liquid cooling in an air-designed building typically means adding coolant distribution units (the pumping and heat-exchange gear that moves fluid between facility water systems and server cold plates), new piping runs, leak detection, and floor-loading and maintenance procedures the original design never contemplated — often while neighboring racks keep serving live traffic. The engineering challenge of doing this in production facilities is precisely why a credible report of Google doing it at fleet scale is notable.

    What It Signals for the Rest of the Market

    Hyperscaler practice tends to become industry expectation. If Google normalizes liquid retrofits, colocation providers and enterprise operators will face the same question from their customers: can your existing halls take liquid-cooled racks, or only your new ones? Operators who can answer yes gain a way to monetize older buildings at AI-era densities; those who cannot may see legacy space reprice downward relative to liquid-ready capacity.

    The supplier picture shifts too. A retrofit wave would expand the addressable market for cooling-distribution hardware, piping, quick-disconnect fittings, and specialized integration services well beyond the new-construction pipeline — because the installed base of air-cooled data halls worldwide is vastly larger than any single year’s new builds. At the same time, air cooling is not disappearing: the bulk of general-purpose computing still runs comfortably on air, and most retrofits produce hybrid halls where liquid and air coexist. The realistic near-term future is mixed-mode facilities, not a wholesale replacement.

    Background

    Google operates one of the world’s largest data center fleets and has long treated infrastructure engineering as a competitive advantage, publishing influential work on efficiency and custom hardware. It was an early hyperscale adopter of liquid cooling, deploying it at scale with its TPU v3 AI chips in 2018 — years before the generative-AI boom made the technology an industry-wide priority.

    Across the wider market, the surge in AI computing since 2023 has pushed rack power densities far beyond what conventional air cooling handles economically, making liquid cooling standard in new AI construction. The unresolved question has been what happens to the enormous installed base of air-cooled facilities — which is exactly the question a credible hyperscaler retrofit program begins to answer.

    Source: Google Brings Liquid Cooling to Legacy Data Halls — Data Center Richness (Substack), June 16, 2026, reporting on Google’s retrofit of liquid cooling into existing air-cooled data halls.

  • KKR Launches Helix, Tapping Ex-AWS CEO Adam Selipsky for AI Hyperscale Bet

    KKR Launches Helix, Tapping Ex-AWS CEO Adam Selipsky for AI Hyperscale Bet

    Global investment firm KKR has launched Helix, a new venture aimed at building AI infrastructure at hyperscale, and has tapped former Amazon Web Services CEO Adam Selipsky to lead the effort. The announcement, reported June 16, 2026 by Data Center Frontier, frames Helix as an attempt to build a “new hyperscale model” — a cloud-scale computing platform purpose-built for artificial intelligence workloads — with a capital commitment coverage characterizes as running into the billions of dollars.

    Executive Summary

    The announcement pairs two things the AI infrastructure market watches closely: very large pools of private capital and proven hyperscale operating talent. KKR is one of the world’s largest alternative-asset managers and an established data center investor, while Selipsky ran AWS — the world’s largest cloud provider — from 2021 to 2024. Putting a former AWS chief executive at the head of a purpose-built AI infrastructure venture signals that KKR intends Helix to be an operating platform, not merely a real-estate or lending vehicle.

    Why it matters: AI demand has strained the traditional hyperscale playbook, in which a handful of cloud giants self-fund and self-build their own capacity. A wave of alternative models — specialized GPU clouds, build-to-suit developers, and now investor-led platforms — is competing to finance and operate the next generation of AI data centers. Helix is a bet that private capital can own more of that stack directly. That said, the launch coverage is light on specifics: no disclosed capital figure, sites, customers, or timeline accompany the framing, so the scale of the bet remains asserted rather than itemized.

    Why Private Capital Wants Its Own Hyperscaler

    For most of the cloud era, hyperscale infrastructure — the massive, standardized data center fleets run by Amazon, Microsoft, and Google — was financed from those companies’ own balance sheets. AI training and inference have changed the math: capacity needs are growing faster than even the largest corporate balance sheets comfortably absorb, and the industry has increasingly turned to infrastructure funds, private credit, and joint ventures to carry the cost. KKR has been on the supplying side of that shift for years, including its co-acquisition of data center operator CyrusOne in 2022.

    Helix, as framed, moves KKR up the stack — from landlord and financier toward operator. The economic logic is straightforward: the further up the stack you operate, the more of the AI value chain you capture, but the more operational and demand risk you take on. A firm that owns the facility, the compute platform, and the customer relationship earns more than one that only owns the shell — and loses more if utilization disappoints.

    The Selipsky Signal

    Leadership is the most concrete fact in this announcement, and it is a meaningful one. Adam Selipsky led AWS through 2021–2024, a period spanning the launch of the generative-AI boom, and before that built Tableau into a major software company as its CEO. Hiring an executive of that profile is a costly, credible signal: it suggests Helix aspires to hyperscale-grade engineering and go-to-market discipline rather than a pure asset-aggregation play.

    It is also a recruiting and customer-credibility asset. Enterprises and AI labs committing multi-year capacity contracts weigh whether a new platform will still exist — and perform — in five years. A founding CEO who has run the largest cloud in the world addresses that question more directly than a capital commitment alone. Still, a leader is not a product: the announcement does not describe what Helix will actually sell, to whom, or how it differs technically from the incumbents Selipsky used to compete for.

    What Could a “New Hyperscale Model” Mean?

    The phrase invites scrutiny because the field of would-be alternatives is already crowded. Specialized GPU cloud providers (sometimes called “neoclouds”) rent AI compute directly; build-to-suit developers construct campuses against long-term hyperscaler leases; sovereign and utility-linked ventures bundle power with compute. If Helix simply combines KKR capital with leased or built capacity, it joins an existing category rather than creating one. If it integrates power procurement, facility ownership, and a cloud-style software platform under one roof, it would be a genuinely different structure — closer to a privately held fourth hyperscaler.

    The winners-and-losers question follows from which version materializes. An operating hyperscaler backed by KKR would compete with the very cloud giants that are also KKR’s counterparties elsewhere, and with the neocloud cohort for GPUs, power, and talent. A financing-first version would compete mainly with other infrastructure funds. The launch materials, as reported, support the ambition but not yet the mechanism — a distinction buyers and investors should keep in view.

    Background

    KKR, founded in 1976, is one of the world’s largest alternative-asset managers and a major force in infrastructure investing. Its digital-infrastructure portfolio includes the 2022 co-acquisition of hyperscale data center operator CyrusOne, positioning the firm as landlord and financier to the cloud industry well before this launch. Adam Selipsky spent over a decade at AWS across two stints, led Tableau as CEO in between, and ran AWS from 2021 until stepping down in 2024 — giving him firsthand experience of both the strengths and the strains of the incumbent hyperscale model.

    The launch arrives amid a broader restructuring of how AI infrastructure gets financed. Surging demand for AI training and inference capacity has pulled infrastructure funds, private credit, and specialized GPU cloud providers into a market once dominated by three self-funding cloud giants, with capital commitments across the sector reaching historic scale.

    Source: KKR Bets Big on AI Infrastructure With Helix Launch, Tapping Former AWS CEO Adam Selipsky to Build a New Hyperscale Model — Data Center Frontier’s June 16, 2026 report on KKR’s launch of the Helix AI infrastructure venture.

  • Senate Bill Would Put Data Center Grid Access Under Federal Review

    Senate Bill Would Put Data Center Grid Access Under Federal Review

    A Republican U.S. senator has introduced a bill that would give the federal government authority over data centers’ access to the electric power grid, NBC News reported on June 15, 2026. The measure targets the fast-growing AI and cloud data center sector, whose interconnection requests have become a flashpoint in state utility proceedings across the country.

    Executive Summary

    The proposal, as summarized by NBC News, would insert a federal role into what has historically been a state- and regional-utility matter: deciding when, where, and on what terms large data centers can plug into the grid. The senator’s office has framed the bill as a response to concerns that hyperscale AI campuses are absorbing scarce generation and transmission capacity ahead of residential and industrial customers.

    For the data center industry, the stakes are meaningful even if the bill never becomes law. A federal review layer — depending on scope — could add time, cost, and uncertainty to interconnection, the process by which a new load or generator is approved to connect to the grid. It would also reopen a long-settled jurisdictional question about who governs retail electric service.

    Why Washington Is Suddenly Interested In Interconnection Queues

    Interconnection — the technical and contractual process of hooking a large customer up to the transmission system — used to be a sleepy engineering topic. AI has changed that. Single hyperscale campuses now request hundreds of megawatts, and in some regions gigawatts, of firm capacity. That has produced multi-year queues, contested rate cases, and political pressure on governors and public utility commissions. A federal bill directed specifically at data center grid access is a signal that the issue has migrated from utility filings to national politics.

    The measure appears to target a genuine coordination problem: individual state regulators approve individual interconnections, but the cumulative effect ripples across multi-state grid operators such as PJM, MISO, and ERCOT. Whether a federal gatekeeper is the right fix, or would simply add a layer on top of existing FERC and regional transmission organization processes, is the substantive question the bill will have to answer.

    Who Wins And Who Loses If A Federal Role Is Added

    Incumbents with signed interconnection agreements and energized sites are the clearest short-term winners of any friction added to new connections: their capacity becomes scarcer and more valuable. Developers still in queue — particularly speculative sites without anchor tenants — face the most exposure, because a federal review could reshuffle priority or impose siting criteria unrelated to a project’s engineering readiness.

    Utilities are harder to place. Some have complained that speculative data center requests inflate their planning forecasts; a federal filter could relieve that pressure. Others rely on large-load growth to spread fixed costs across more kilowatt-hours and would resist anything that slows revenue. Residential ratepayer advocates, who have argued that AI loads are effectively cross-subsidized by households, may find themselves unusual allies of a bill from across the aisle.

    What The Bill Would Have To Overcome

    Retail electric service — the sale of power to end customers, including data centers — has traditionally been a state matter under the Federal Power Act, with FERC’s jurisdiction limited to wholesale sales and interstate transmission. A federal veto over data center grid access would test that boundary and likely draw legal challenge from states that have aggressively courted the industry, as well as from operators with existing contracts.

    The politics are also non-obvious. A Republican-led bill imposing federal oversight on a private industry cuts against the party’s usual deregulatory posture, suggesting the sponsor sees data center power consumption as a constituent-facing affordability and reliability issue rather than a market question. Whether that framing attracts bipartisan support or stalls in committee will determine if this is a serious legislative vehicle or a marker bill.

    Background

    Data centers house the servers that run cloud computing, streaming, and AI workloads. Historically they consumed a manageable share of U.S. electricity, but the training and deployment of large AI models since 2023 has driven exceptional growth in individual site sizes and total sector demand. That has collided with a slower-moving power system, where new generation and transmission routinely take five to ten years to build.

    Grid access for large customers has traditionally been a state matter, with utility regulators approving special contracts and rates. Federal involvement has been limited to wholesale markets and interstate transmission, primarily through the Federal Energy Regulatory Commission. Proposals to expand that federal role, from either party, mark a departure from decades of practice.

    Source: Republican senator proposes federal control over data centers’ access to the power grid – NBC News, reporting on newly introduced legislation targeting federal authority over how data centers connect to the U.S. electric grid.

  • Elemental Impact Commits Up to $5M for Data Center Cooling That Saves Energy and Water

    Elemental Impact Commits Up to $5M for Data Center Cooling That Saves Energy and Water

    Elemental Impact, a nonprofit climate-technology investor, has launched a Data Center Innovation Initiative that will provide up to $5 million in funding for cooling technologies that reduce energy and water consumption in data centers. The announcement, reported June 15, 2026 by the trade publication Natural Refrigerants, positions the initiative squarely at the intersection of the AI-driven data center boom and growing scrutiny of the industry’s resource footprint.

    Executive Summary

    The headline commitment is modest by data center standards — up to $5 million — but the target is one of the industry’s most consequential engineering problems. Cooling is typically among the largest energy loads in a data center after the IT equipment itself, and many facilities also rely on evaporative systems that consume significant volumes of water. Technologies that cut both at once address the two resource concerns that most often put data center projects in conflict with host communities and utilities.

    The initiative’s framing in a natural-refrigerants publication is itself a signal: it suggests interest in cooling approaches built on refrigerants such as CO2, ammonia, or hydrocarbons, which avoid the high-global-warming-potential fluorinated gases (HFCs) that regulators in the U.S. and elsewhere are phasing down. For a nonprofit investor like Elemental Impact, the play is catalytic — using relatively small, early money to help promising cooling technologies reach commercial deployment faster than conventional venture or infrastructure capital would carry them.

    Cooling Is Where Efficiency Gains Are Still on the Table

    A data center’s power draw splits between the computing hardware and the overhead needed to keep it running — chiefly cooling and power distribution. Operators measure this with power usage effectiveness (PUE), the ratio of total facility power to IT power, and the gap between an average facility and a best-in-class one is largely a cooling story. As AI accelerators push rack densities far beyond what traditional air cooling was designed for, the industry is being forced toward liquid cooling, advanced heat rejection, and smarter refrigeration cycles anyway. Funding aimed at this transition arrives with the market already moving in its direction.

    Water is the quieter half of the problem. Evaporative cooling saves electricity precisely by consuming water, so operators often face a trade-off between energy efficiency and water efficiency. Technologies that genuinely reduce both — rather than shifting the burden from one resource to the other — are the harder engineering target, and the initiative’s dual framing suggests that is the bar Elemental Impact intends to set.

    What $5 Million Can and Cannot Do

    Five million dollars does not build data center infrastructure; a single large facility can represent hundreds of millions or billions in capital expenditure. But that comparison misses how catalytic capital works. Early-stage cooling hardware faces a well-known commercialization gap: pilots are expensive, data center operators are conservative buyers who rarely gamble uptime on unproven equipment, and the revenue that would fund a first deployment depends on having done a first deployment. Philanthropic and nonprofit capital is one of the few tools designed to absorb exactly that risk.

    The realistic measure of success for an initiative this size is not megawatts cooled but proof points created — field data, reference customers, and validated performance claims that let follow-on investors and buyers commit with confidence. That leverage effect is the standard theory of change for organizations like Elemental Impact, which has spent years funding climate technologies through the awkward stage between lab and market.

    The Regulatory Tailwind Behind Natural Refrigerants

    The venue for the announcement matters. Conventional cooling systems have long depended on fluorinated refrigerants with high global warming potential, and those chemicals are now being phased down under the international Kigali Amendment and, in the United States, the AIM Act. Natural refrigerants — carbon dioxide, ammonia, propane, and similar substances — sidestep that regulatory curve entirely, but they bring their own engineering challenges around pressure, toxicity, or flammability that have slowed adoption in data centers.

    If the initiative channels money toward natural-refrigerant cooling for data centers specifically, it is betting that regulatory pressure plus AI-era density demands will finally pull these systems into a market that has historically been cautious about them. That is a defensible bet, though the announcement as reported does not detail how prescriptive the initiative will be about refrigerant choice.

    Winners, Losers, and Who Should Pay Attention

    The most direct beneficiaries are early-stage cooling companies that need pilot funding and credibility. Data center operators benefit indirectly: a broader menu of proven, efficient cooling options lowers operating costs and eases the permitting and community-relations friction that increasingly delays projects over power and water concerns. Utilities and water authorities in data center markets gain, too, if efficiency gains materialize at scale.

    The competitive question is whether small, mission-driven funding can move faster than the incumbents. Major cooling vendors and hyperscale operators are investing heavily in their own thermal management roadmaps. A $5 million initiative will not outspend them — but it can back approaches those incumbents consider too early or too unconventional, which is historically where nonprofit climate capital has earned its keep.

    Background

    Elemental Impact, previously known as Elemental Excelerator, is a nonprofit investing platform that has spent more than a decade funding climate technologies across energy, transportation, water, and industry, with an emphasis on getting first deployments into the ground alongside community partners. The data center initiative extends that model into digital infrastructure at a moment when the sector’s growth has made its energy and water footprint a mainstream policy issue.

    Data center cooling itself is in the middle of a generational transition: AI accelerators are pushing power densities beyond what conventional air cooling handles economically, while refrigerant regulations and water scarcity are constraining the traditional fixes. That convergence has turned thermal management — long a back-of-house discipline — into one of the most actively funded corners of data center technology.

    Source: Elemental Impact’s Data Center Innovation Initiative Will Provide Up to $5 Million in Funding for Cooling Tech That Reduces Energy and Water Use — Natural Refrigerants trade publication report, June 15, 2026, on the nonprofit’s new funding program for efficient data center cooling.

  • Cummins to Supply Natural Gas Generators for Large-Scale West Texas Data Centers

    Cummins to Supply Natural Gas Generators for Large-Scale West Texas Data Centers

    Cummins announced on June 15, 2026 that its natural gas generators will power large-scale data centers in West Texas. The announcement, issued by the engine and power-systems maker itself, confirms a supply arrangement for on-site power generation but does not disclose the customer, the number of units, the total generating capacity, or the delivery schedule.

    Executive Summary

    Cummins, the Indiana-based manufacturer best known for diesel engines and generator sets, says its natural gas generators have been selected to power large-scale data center development in West Texas. Stripped to its substantiated core, the announcement establishes three facts: the vendor (Cummins), the fuel (natural gas), and the setting (large-scale data centers in West Texas). Everything else — megawatts, dollars, dates, and the developer’s name — is left unstated.

    Even so, the deal is worth attention because of what it represents. Data center developers are increasingly buying their own power plants rather than waiting years for utility interconnections, and West Texas — with abundant natural gas, cheap land, and a congested grid — has become the proving ground for that model. A generator manufacturer announcing data-center-scale natural gas orders is a data point in one of the most consequential shifts in how digital infrastructure gets energized.

    Why Data Centers Are Buying Their Own Power Plants

    The traditional model — build a data center, plug it into the utility grid — is breaking down under AI-era demand. Requests for new grid connections in fast-growing markets can take several years to fulfill, because utilities must study, permit, and build transmission lines and substations before energizing a large new load. For developers racing to deliver capacity to cloud and AI tenants, that queue is often the single longest item on the schedule.

    On-site generation — sometimes called behind-the-meter power, because it sits on the customer’s side of the utility meter — collapses that timeline. Reciprocating natural gas generators of the kind Cummins builds can be manufactured, shipped, and commissioned far faster than a transmission project, and they can be added in increments as a campus grows. What was once purely backup equipment, sized to ride through rare outages, is increasingly being specified as primary or bridge power that runs for thousands of hours a year.

    West Texas: Abundant Gas, Strained Wires

    West Texas is a logical setting for this model. The region sits atop the Permian Basin, one of the most productive oil and gas regions in the world, where natural gas is plentiful and pipeline infrastructure is dense. Land is inexpensive, and the area already hosts substantial wind and solar development. What the region lacks is transmission: moving power across the Texas grid, operated by ERCOT (the Electric Reliability Council of Texas), is constrained by long distances and congested lines.

    For a data center developer, that combination — fuel at the wellhead, but a bottlenecked grid — makes on-site gas generation attractive. Rather than exporting the region’s energy as electrons over strained wires, the data center effectively moves the demand to the fuel. The announcement does not say whether these facilities will also seek grid connections later, a common strategy in which on-site generation serves as a bridge until utility service arrives.

    What It Means for Cummins and the Genset Market

    For Cummins, data-center demand is reshaping a business that historically sold generators as insurance. Backup generators run perhaps a few dozen hours a year; prime-power installations run continuously, which means more units, larger service contracts, and steadier parts revenue. Major engine and turbine makers across the industry have reported stretched lead times for large power equipment as data-center orders stack up, so a manufacturer publicizing a West Texas win is competing for position in a genuinely supply-constrained market.

    The competitive backdrop matters too. Data center developers weighing on-site power can choose among reciprocating gas engines, gas turbines, and, eventually, small modular nuclear or fuel-cell options. Reciprocating engines like Cummins’ occupy a middle ground: faster to deploy and more modular than turbines, though generally better suited to incremental capacity than to single gigawatt-scale blocks. Which architecture wins at a given site depends on scale, gas supply, and air-permitting headroom — none of which this announcement details.

    The Trade-Offs the Headline Skips

    Natural gas generation is cleaner than the diesel that has long dominated data-center backup — it burns with lower particulate and sulfur emissions — but it is still a fossil-fuel source with carbon dioxide and nitrogen oxide emissions, and large installations require air-quality permits from Texas regulators. Hyperscale tenants with public net-zero commitments will want to know whether gas-powered campuses fit their carbon accounting, whether the plants are bridge or permanent solutions, and whether the equipment can later run on lower-carbon fuels.

    Reliability cuts the other way: a well-designed fleet of gas generators with firm fuel supply can rival or exceed grid reliability, and it insulates the tenant from ERCOT’s scarcity-priced energy market during extreme weather. The honest framing is that on-site gas is a pragmatic trade — speed and control in exchange for emissions and fuel-price exposure — and this release, as circulated, makes the case for the first half without quantifying the second.

    Background

    Founded in 1919 in Columbus, Indiana, Cummins built its reputation on diesel engines for trucks and heavy equipment, and its power systems division has long been a leading supplier of standby generator sets for data centers, hospitals, and industry. In recent years the company has expanded its natural gas engine lineup as customers seek lower-emission alternatives to diesel.

    The backdrop is a historic surge in electricity demand from AI and cloud computing that has outpaced utilities’ ability to connect new loads. Texas has emerged as a leading destination for this buildout, and West Texas in particular — sitting atop the Permian Basin’s gas supply but far from major transmission corridors — has become a testbed for data centers that generate their own power on-site rather than waiting for the grid.

    Source: Cummins Natural Gas Generators to Power Large Scale Data Centers in West Texas — company announcement dated June 15, 2026, stating that Cummins natural gas generators will power large-scale data center development in West Texas.