Results from the Uptime Institute Sustainability and Climate Change Survey 2024 reveal how operators navigate climate change risks while expanding efforts to improve their environmental footprint.
How far can we go with air? Uptime experts discuss and answer questions on cooling strategies and debate the challenges and trade-offs with efficiency and costs. Please watch this latest entry in the Uptime Intelligence Client Webinar series. The ser...
Uptime Institute provided three documents to the EU Commission and their consultants, Ernest and Young and Borderstep, in response to two surveys. The surveys are intended to gather data to facilitate the development of a data center labeling/rating ...
Major and damaging publicly reported outages are increasingly likely to be due to a deliberate attack — whether cyber or physical, according to Uptime Intelligence public outage data for 2024.
Critics argue that data center water use is excessive and poorly managed. Operators should select a cooling system to fit the local climate and available water supply, explaining water use within the context of local conditions.
Chinese large language model DeepSeek has shown that state of the art generative AI capability may be possible at a fraction of the cost previously thought.
High-end AI systems receive the bulk of the industry’s attention, but organizations looking for the best training infrastructure implementation have choices. Getting it right, however, may take a concerted effort.
Data shows that cuts to workforce initiatives and mentorships had little effect on the proportion of new hires in 2024. Owners and operators can consider reassessing and restructuring these programs.
The high capital and operating costs of infrastructure for AI mean an outage can have a significant financial impact due to lost training hours
The US’ SEC has withdrawn requirements for climate risk reporting, and the EU is revising its rules. Despite this, strong drivers remain for operators to measure their environmental impact
Scalability and cost efficiency are the top reasons enterprises migrate to the cloud, but scalability issues due to application design flaws can lead to spiralling costs — and some workload repatriation to on-premises facilities
Compared with most traditional data centers, those hosting large AI training workloads require increased attention to dynamic thermal management, including capabilities to handle sudden and substantial load variations effectively.
AI is not a uniform workload — the infrastructure requirements for a particular model depend on a multitude of factors. Systems and silicon designers envision at least three approaches to developing and delivering AI.
Understanding the principles of human behavior and how they relate to community engagement and siting strategies can reduce potential conflict between data centers and local residents
Large data centers can affect grid power quality, inviting community scrutiny. Best practices already protect power quality in facilities and grids, but operators may need to increase monitoring and publicize their efforts.
Douglas Donnellan
Rose Weinschenk
Andy Lawrence
Daniel Bizo
Jacqueline Davis
Tomas Rahkonen
Muhammad Naveed Saeed
Jay Dietrich
John O'Brien
Owen Rogers
Peter Judge
Max Smolaks