Water treatment and chemicals giant Ecolab has agreed to pay $4.75 billion in cash for Canadian DLC specialist CoolIT. It is the latest sign of unabated demand for AI compute.
Increasing community opposition to data center development is compelling hyperscalers to rethink their decades-old practices.
Enterprises deploying AI inference need to choose carefully to limit costs and protect their data.
Even before data center operators move to higher voltages, rising power densities are increasing the risks faced by electricians.
Growing public opposition to data center development has pushed many data center companies to invest in media and promotional campaigns. But, as opposition intensifies, this type of outreach is unlikely to sway public opinion.
Although cloud platforms often offer the lowest cost for AI inference, on-premises deployment may be preferable due to application architecture, data locality and control requirements.
The cost of AI inference varies widely depending on deployment model, utilization and hardware. This pricing tool compares on-premises, colocation, cloud infrastructure and managed AI platforms on a like-for-like basis.
PUE measures facility energy overhead relative to IT load, but it does not show how much of a site's provisioned power envelope ultimately reaches IT. Power and compute effectiveness (PCE) introduces a metric that makes this allocation visible.
Some countries are attempting to create capacity headroom for new facilities by applying efficiency limits to existing data centers. In Singapore, reducing PUE will be expensive for operators.
Net-zero commitments are becoming more common across the data center industry, but power demand growth and stricter carbon accounting rules are reshaping expectations.
As the data center industry aims to address rising power density, technical developments in facilities are undergoing significant changes. With average rack densities climbing, new ways to configure and power data centers are increasing. To keep up…
Cloud and AI growth are straining power systems, and the US GRID Act could make expansion more difficult. The industry will need greater transparency on projected energy and water use, project plans, and incentives.
Uptime Intelligence analysis shows that minimum thresholds for IT power utilization misrepresents server work capacity utilization. These thresholds can unintentionally incentivize operators to disable server energy efficiency features.
Results from Uptime Institute's 2026 AI Infrastructure Survey (n=1,141) focus on the data center infrastructure currently used or being planned to use to host AI Training and AI Inference, as well as future industry outlooks on the usage of AI. The…
Concerns over rising electricity costs and environmental impact are driving local opposition to new data center projects in the US, prompting a growing number of cancellations.
Daniel Bizo
Peter Judge
Max Smolaks
Rose Weinschenk
Dr. Owen Rogers
Dr. Rand Talib
Douglas Donnellan
Chris Brown
Jay Dietrich
Dr. Tomas Rahkonen
Paul Carton
Anthony Sbarra
Laurie Williams