『The Data Center Frontier Show』のカバーアート

The Data Center Frontier Show

The Data Center Frontier Show

著者: Endeavor Business Media
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Welcome to The Data Center Frontier Show podcast, telling the story of the data center industry and its future. Our podcast is hosted by the editors of Data Center Frontier, who are your guide to the ongoing digital transformation, explaining how next-generation technologies are changing our world, and the critical role the data center industry plays in creating this extraordinary future.

Copyright Data Center Frontier LLC © 2019
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  • Power Quality: The Conversation Data Centers Can't Afford to Ignore
    2026/09/24

    Uptime and cooling performance both depend on something that is often overlooked during the data system design process: power quality. In this podcast, "Power Quality: The Conversation Data Centers Can't Afford to Ignore," we talk with a Power Quality expert about harmonic distortion in data centers — what it is, how it is created, and how poor power quality impacts data center cooling, uptime and performance. We will also dig into solutions engineers can employ to mitigate poor power quality in their data center.

    Power quality deserves a seat at the table alongside the metrics data center operators already obsess over — availability, PUE, and thermal performance. Total Harmonic Distortion, or THD, gives engineers a real, measurable way to gauge the health of their electrical system, turning power quality from an abstract concern into something concrete that can be monitored, benchmarked, and acted on.

    This discussion will focus on where harmonics actually come from — and it's something of a paradox. Many of the same components installed specifically to make data centers more efficient, such as variable frequency drives and EC fans, are also responsible for generating the harmonic distortion that undermines power quality. Understanding which specific equipment, in which specific areas of a facility, pose the greatest risk to power quality, gives engineers a practical way to identify where problems are most likely to originate.

    Once data center engineers understand the source of harmonics, we’ll dig into the interdependency between power quality and thermal cooling in data centers. Clean, stable power is required to cool a facility properly, and proper cooling is required to run a data center efficiently — the two don't operate independently, one relies on the other. When harmonics go unmanaged excess heat accelerates equipment wear, protective devices trip unexpectedly, cooling systems degrade, and thermal throttling sets in. Left unaddressed, the result is unplanned downtime — the very outcome every data center is designed to avoid.

    The physical layout of a facility matters too. "Grey space" and "white space" — the mechanical/support areas and the core IT data hall, respectively — each present different harmonic challenges and require different mitigation approaches. There isn't one single location in a data center where power quality can be fixed once and for all; effective mitigation means evaluating the facility as a whole, rather than searching for a single point of resolution.

    Finally we’ll explore solutions available for engineers to help mitigate harmonics in data centers. One of the primary solutions we will focus on will be active harmonic filters. Active harmonic filters continuously monitor power quality of the system and make real-time corrections to mitigate harmonics. Where these filters are installed matters as much as the technology itself, and getting placement right has a direct impact on effectiveness. We’ll also discuss how engineers can take a hands-on approach to maintaining power quality by calculating their own harmonic distortion levels to determine how much filtering capacity they actually need — turning an otherwise theoretical challenge into something they can size, plan for, and solve.

    Ultimately, this podcast makes the case that power quality deserves the same level of design attention as uptime and cooling — because in reality, all three are connected. Whether you're a data center engineer, facility owner, or simply responsible for keeping systems running reliably, understanding harmonic distortion isn't a peripheral concern. It's foundational to how well a data center performs.

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    18 分
  • OIX's Ilissa Miller: Preparing Communities for AI Data Centers
    2026/09/22
    Communities across the U.S. are being asked to make increasingly consequential decisions about data centers at the same time that AI infrastructure development is moving faster than traditional municipal planning processes. On this episode of the Data Center Frontier Show, DCF Editor-in-Chief Matt Vincent speaks with Ilissa Miller, founder and CEO of iMiller Public Relations and a board member of the Open Infrastructure Exchange (OIX), about a new effort to help communities prepare before specific data center projects arrive. At the center of the conversation is the OIX Digital Infrastructure Framework, designed to give municipal planners and elected officials a structured set of questions for evaluating data centers and other digital infrastructure. Rather than prescribing what communities should approve, Miller says the framework is intended to help them determine where digital infrastructure fits within their own long-term land-use strategies. Many municipalities, she notes, still do not explicitly recognize data centers as an acceptable land use — even on parcels already designated for industrial activity. That can send developers into conditional-use or zoning processes while residents and public officials are still trying to understand what exactly is being proposed. Miller argues that comprehensive planning offers a better starting point. Communities should be deciding in advance where different types of digital infrastructure might be appropriate, what information developers will need to provide, and how data centers fit alongside other economic-development priorities. The need has become particularly acute as opposition to data centers increasingly overlaps with broader public anxiety about artificial intelligence. “Most opposition is about more than the data center itself,” Miller says. Concerns over AI governance, automation and societal impacts are legitimate topics for debate, she argues, but they are not necessarily the same questions local officials must answer when evaluating land use, power, water, noise, construction and community impacts. For developers, Miller says earlier community engagement is equally important. Engagement should begin before a conditional-use application and before a project design has effectively been finalized. Developers should hold listening sessions, understand local business and political dynamics and give communities a meaningful opportunity to influence project plans. “The key to those engagements and those listening events is actually listening,” Miller says. That means showing communities what was heard, explaining what changed as a result and tailoring community benefits to actual local priorities rather than arriving with a standardized package. But Miller also emphasizes that communications cannot compensate for a poorly conceived project. “Not all data center developments should be built,” she says. Her firm will decline engagements involving certain attempts to rezone agricultural or otherwise inappropriate land for data center development. Miller argues that developers should look first toward properly zoned industrial locations, redevelopment opportunities and sites where intensive land use already exists. That principle gets to the larger question of social license: community trust begins with project execution and site selection, not simply better messaging. The conversation also explores perhaps the most difficult challenge facing both the industry and municipalities — speed. AI chip development is occurring on cycles measured in months or a few years, while data center development, municipal planning and infrastructure investment historically operate over much longer timelines. Miller says the industry itself is struggling to absorb that pace. Looking five years ahead, she envisions communities incorporating digital infrastructure directly into comprehensive master plans, distinguishing between hyperscale AI campuses, colocation, carrier hotels, edge facilities and other forms of digital infrastructure. Not every community needs — or can support — a massive AI data center. But Miller argues that communities still need to understand the infrastructure requirements of their hospitals, manufacturers, businesses and public services. The objective is not to ensure that every data center gets built. It is to ensure that when a proposal does arrive, the community is no longer beginning the conversation from zero.
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    24 分
  • Industrial-Grade Reliability: Why Data Centers Are Rethinking Measurement Infrastructure
    2026/09/17

    As data centers race to support AI workloads, liquid cooling, and accelerated construction timelines, operators are facing new challenges around reliability, efficiency, and infrastructure visibility. Many facilities still rely on commercial-grade instrumentation across critical cooling and utility systems, creating blind spots that can increase operational risk and reduce confidence in performance.

    In this episode, we explore why leading operators are adopting industrial-grade instrumentation to gain more accurate insight into flow, temperature, pressure, and fluid quality across their facilities. The conversation covers the critical measurement points that impact uptime, how liquid cooling is changing infrastructure requirements, and the role measurement technology plays in helping operators commission faster, reduce risk, and confidently scale for future growth.

    Listeners will walk away with practical guidance for evaluating instrumentation strategies, selecting technology partners, and preparing their facilities for the next generation of data center demands.

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    16 分
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