As new capacity is concentrated in super-sized data centers and legacy facilities continue to operate in large numbers, market trends become more difficult to read. This report looks at how size affects the age distribution of capacity.
AI training clusters can show rapid and large swings in power consumption. This behavior is likely driven by a combination of properties of both modern compute silicon and AI training software — and may be difficult to manage at scale.
Generative AI models brought about an influx of high-density cabinets. There has been much focus on how to best manage thermal issues, but the weight of power distribution equipment is a potentially overlooked concern.
Increasing supply air temperature is gaining interest as an approach to potentially save data center energy. However, savings will not be universally possible and understanding its potential involves a complex multivariable analysis.
Pulling reliable power consumption data from IT is increasingly important for operators. Although third-party software products offer promise, significant roadblocks still hinder adoption.
UPS systems are the number one root cause of significant and severe outages. Analysis of reliability data from data center management software provider Fulcrum Collaborations sheds more light on the prevalent UPS component failures.
Densification is — once again — high on the agenda, with runaway expectations largely due to compute power requirements of generative AI workloads. Will this time be different? Uptime’s 2024 global survey of data center managers offers some clues.
Hydrogen is a promising energy storage medium that can help decarbonize infrastructure. It is not a great fit for the majority of data centers, and the hydrogen economy is not fully developed.
The data center industry’s drive for carbon-free growth appears to be at odds with electricity grid stability. Data center operators will need to reorient their strategies to integrate growth, efficiency and decarbonization.
Water use has become a critical element of a sustainability strategy. It is a location-specific issue: local climate and resources and the data center design will determine the water use profile of the facility.
Most operators will be familiar with the outrageous power and cooling demands of hardware for generative AI. Why are these systems so difficult to accommodate, and what does this mean for the future of data center design?
The transition to direct liquid cooling has been a slow process. Today, operators work with water cold plates more than any other type of cooling, but this might change once a wider range of DLC types become available.
The 14th edition of the Uptime Institute Global Data Center Survey highlights the experiences and strategies of data center owners and operators in the areas of resiliency, sustainability, efficiency, staffing, cloud and AI.
Although there is still uncertainty around the rate of AI adoption, many organizations are pushing ahead to avoid being left behind. However, behind this enthusiasm, there are six issues that operators face when hosting AI.
Many data centers struggle to achieve maximum capacity and optimal cooling, resulting in troublesome hot spots. Advances in cooling optimization software have addressed this complexity and could be the answer.