Three ways data centers can operate more sustainably

Over the next decade, the energy demands of data centers will continue to grow worldwide as AI workloads scale, placing new pressure on power grids, water resources and operating costs.

This is forcing operators to rethink how digital infrastructure is planned, built and operated – but data center operators cannot optimize for a single constraint without creating knock-on effects elsewhere.

Decisions about cooling, location and hardware procurement all carry consequences for water availability, grid stability and global supply chains. Data centers are tightly coupled to the systems around them.

They interact with power grids, requiring careful thought about where power supplies come from, and, importantly, with water supplies. Large hyperscale data centers can consume up to 2.5 billion liters of water annually, equivalent to the needs of approximately 80,000 people, according to UK Government estimates.

Data centers also have an impact on supply chains, driving demand for specialized equipment, skilled labor and chips.

Addressing these pressures requires data center operators to look beyond any single metric and manage sustainability as a set of connected trade-offs.

There are three key areas data center operators can focus on to make rapid and measurable gains in sustainability: the efficiency of cooling systems, increased circularity around reuse and recycling, and workload management.

Improving cooling efficiency

Energy constraints are becoming a limiting factor for data center growth. GPU-dense AI workloads are driving up power density and overall energy demand.

Today, much of the energy used by data centers is not used for computing at all, but for cooling components, with 43% of energy used in U.S. data centers going to cooling, rather than computing.

Data center efficiency is commonly measured using power usage effectiveness (PUE). PUE is the power required to run the whole data center, divided by the power demands of the IT equipment within. In simple terms, the lower we can get the PUE ratio, the better.

Liquid cooling has an important role to play here. Liquid cooling uses water to remove heat from components and remove heat more effectively than traditional air-based systems.

Water cooling can reduce power consumption by up to 40%, and some liquid-optimized data centers have already hit PUE levels of 1.1, meaning far less energy is lost to cooling and other non-computing overheads.

As a result, a smaller proportion of total energy is diverted away from computing, enabling data centers to be far more sustainable.

Designing for circularity

Today, only a small proportion of data center infrastructure is actually recycled or reused at end of life. For data center operators, designing hardware for reuse and longer lifecycles can yield rapid results in terms of curbing waste and emissions.

Asset recovery services for data centers are designed to handle environmentally responsible disposal and recycling of IT hardware, including servers, storage, and networking equipment. Adopting circular economy approaches can be a practical first step on the sustainability journey for many organizations.

Improving reuse and recycling delivers clear, practical benefits, including the recovery of valuable materials and reduced pressure on new manufacturing across the electronics industry. Everything from how components are designed to how they are shipped and how they are disposed of at end of life has a measurable impact.

‘As a service’ models can also reduce overprovisioning by aligning capacity more closely with actual demand. In cooling systems, circularity can also have an impact. Hot water from today’s warm-water cooling systems could be used to heat offices or nearby homes to help curb the environmental impact of data centers.

Closed-loop, ‘circular’ cooling systems also have a role in reducing water use. Older evaporative cooling systems tend to be more water-intensive, particularly in warmer or water-stressed regions. Moving to closed-loop systems which use liquid-to-air heat exchangers can curb the water demands of data centers.

Reducing wasted compute

Workload management is another key factor, and one that is all too often overlooked. The most effective energy savings often come from eliminating wasted compute rather than improving hardware alone. Every watt that is ‘spent’ in the data center should be translated into meaningful computing output.

Virtualization can help to minimize idle capacity and maximize usage, by allowing multiple applications to run on the same server.

By ensuring that every workload makes effective use of the hardware it runs on, workload efficiency helps align sustainability goals with performance by increasing utilization and reducing idle capacity.

Updating older systems can also have important sustainability benefits. Newer architectures tend to deliver more performance at lower energy costs.

Switching to an ‘as a service’ model for infrastructure means that data center operators can provide up-to-date hardware without the up-front capital expenditure usually associated with technology refreshes.

Warm-water cooling systems can also help, allowing components such as GPUs to operate more consistently at higher utilization without thermal throttling. Data center operators should take a gradual ‘one workload at a time’ approach to build momentum incrementally towards wider systemic change.

Making sustainability operational

The increasing demands placed on data centers by AI workloads mean that operators will have to focus more on sustainability in the coming years. Physical infrastructure and workloads need to be planned together, connecting physical efficiency, such as cooling and power delivery, with how workloads are designed and run.

Circularity will also grow in importance, as will the measurable gains of as-a-service models. By dealing with each facet of digital infrastructure and how it interacts with wider society, data center operators can make sustainability a practical, operational part of how data centers are planned and operated.

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