Data center infrastructure management software is widely used but rarely utilized at full potential. Adopting the latest capabilities and optimizations could achieve better resiliency and efficiency.
This summary of the 2025 predictions highlights the growing concerns and opportunities around AI for data centers.
Power and cooling requirements for generative AI training are upending data center design and accelerating liquid cooling adoption. Mainstream business IT will not follow until resiliency and operational concerns are addressed.
Uptime Intelligence looks beyond the more obvious trends of 2025 and identifies examines some of the latest developments and challenges shaping the data center industry.
Cloud providers need to win AI use cases in their early stages of development. If they fail to attract customers, their AI applications may be locked-in to rival platforms and harder to move, which can have serious repercussions.
Nvidia’s dominant position in the AI hardware market may be steering data center design in the wrong direction. This dominance will be harder to sustain as enterprises begin to understand AI and opt for cheaper, simpler hardware.
In this inaugural Uptime Intelligence client webinar, Uptime experts discuss and answer questions on cooling technologies and strategies to address AI workloads. Uptime Intelligence client webinars are only available for Uptime Intelligence subscribe...
The cost and complexity of deploying large-scale GPU clusters for generative AI training will drive many enterprises to the public cloud. Most enterprises will use pre-trained foundation models, to reduce computational overheads.
Not all generative AI applications will require large and dense infrastructure footprints. This complicates AI power consumption projections and data center planning.
Enterprises have much enthusiasm for AI, interviews and workshops by Uptime Intelligence suggest, but this is tempered by caution. Most hope to avoid disruptive, expensive or careless investments.
Enterprises have various options on how and where to deploy their AI training and inference workloads. This report explains how these different options balance cost, complexity and customization.
To meet the demand driven by AI workloads, a new breed of cloud provider has emerged, delivering inexpensive GPU infrastructure as a service. Their services are highly demanded today, but longer-term, the market is ripe for consolidation.
Many speculate that AI and automation might replace humans in data center jobs but there is little evidence to support this line of thought. The data center industry has characteristics that researchers believe may protect against worker displacement
This report provides a regional view of the results from the Uptime Institute Global Data Center Survey 2024 and highlights some of the different challenges and strategies of data center owners and operators across the globe.
Trust in AI as a tool for data center operations has declined sharply in the past three years. It is possible to control for the factors that drive mistrust — and see better outcomes when employees interact with AI-based systems.
John O'Brien
Douglas Donnellan
Jacqueline Davis
Andy Lawrence
Daniel Bizo
Max Smolaks
Peter Judge
Dr. Owen Rogers
Chris Brown
Rose Weinschenk