This report outlines the characteristics of machine learning (ML) applications, describes production use cases for ML-based software in data center M&O, and profiles several vendors offering AI-based functionality in their products.
Over the past 15 years, Daniel has covered the business and technology of enterprise IT and infrastructure in various roles, including industry analyst and advisor. His research includes sustainability, operations, and energy efficiency within the data center, on topics like emerging battery technologies, thermal operation guidelines, and processor chip technology.
dbizo@uptimeinstitute.com
This report outlines the characteristics of machine learning (ML) applications, describes production use cases for ML-based software in data center M&O, and profiles several vendors offering AI-based functionality in their products.
It is becoming a near certainty that many facility operators will use direct liquid cooling within a few years. This raises a number of engineering questions, one of which is how to size coolant distribution units.
Refrigeration’s history of progress is also a history of environmental concern. Whenever new refrigerants solve a problem, they create further crises down the line — and now history appears to be repeating itself.
Preliminary calculations by Uptime Intelligence suggest the initial impact of generative AI on global data center power use is low — but it will rise quickly as adoption increases. How far generative AI will go remains unclear.
New EU legislation will raise recycling and reporting standards for batteries, regardless of chemistries. Although motivated by battery use in electric vehicles, the regulations also place obligations on data center operators.
There is more to managing server power than just conserving energy when the machine is idle. Another side to optimizing energy performance involves setting processor performance levels appropriate for the application.
Air-assisted direct liquid cooling systems offer trade-offs that make them attractive to operators looking to address server cooling and rack density challenges — and are relatively easy to install and maintain.
Without the active contribution from IT, data center infrastructure energy performance and sustainability will fall short of aspirations. Server power management features remain unexplored and underused by most efficiency initiatives.
Uptime Intelligence looks beyond the more obvious trends of 2024 and identifies some challenging issues. Strong IT demand, high-density IT systems and tough sustainability requirements will drive a new wave of investment.
Despite high expectations, most operators will only see moderate impact from specialized AI hardware installations in the immediate future. The emergence of AI as a major force will sway the industry in a more profound, but less direct, fashion.
Thermal trends in server silicon will challenge assumptions that underpin efficiency and sustainability expectations around DLC. Limited visibility of future server cooling requirements means operators can only make an educated guess.
DLC promises attractive thermal performance and economics, but data center operators looking to adopt it will need to examine how they define and uphold their resiliency standard as product designs and resiliency guidance evolve.
Industry average PUE has not improved consistently for some years now, according to Uptime Institute’s annual survey. However, the headline number may be masking underlying dynamics of meaningful improvements.
The suitability of a data center environment is primarily judged by its effect on the long-term health of IT hardware. Facility operators define their temperature and humidity set points with a view to balancing hardware failure rates against the…
The data center industry's largest and most influential survey results are in! Join us as we discuss the 13th Annual Uptime Global Data Center Survey 2023 which reveals an industry that is growing, dynamic and increasingly resilient.