Data centres have traditionally been designed with a focus on compute capacity, with cooling treated as a supporting system that can be scaled as needed. That assumption no longer holds. As demand for data processing continues to grow, driven by cloud services and artificial intelligence, cooling is becoming a primary constraint on how infrastructure is designed, operated and expanded.

This shift is particularly relevant in Australia, where rapid growth in digital infrastructure is being balanced against constraints around energy availability, cost and sustainability expectations. As new facilities are developed and existing sites are expanded, operators are facing increasing pressure to optimise both performance and resource use.

One of the clearest indicators of this change is the scale of energy required to run modern data centres. Cooling alone accounts for a significant portion of overall consumption, and total demand continues to rise as compute intensity increases. This is not just a question of efficiency. It is a question of whether existing approaches to cooling can keep pace with increasing thermal loads while remaining viable in a constrained energy environment.

The result is a shift in how cooling is viewed. It is no longer a downstream engineering decision. It is a core determinant of performance, cost and scalability. This becomes more pronounced as rack densities increase. Traditional air-based systems remain effective at lower densities, but their limitations become more apparent as heat loads rise.

Liquid cooling has emerged as a practical response. By using the thermal properties of liquids, systems can remove heat more efficiently and support higher-density infrastructure. However, this is not simply a technology shift. It requires a different approach to system design, integration and operation.

In this environment, performance is no longer defined by capacity alone. It is increasingly defined by control. Cooling systems must operate in dynamic conditions, responding to fluctuating workloads rather than steady-state assumptions. This has driven a move away from fixed, flow-based control towards temperature-driven approaches that adjust output based on real-time demand.

This shift is important because it changes where efficiency gains are achieved. Instead of relying on incremental improvements in individual components, operators are focusing on how well systems match output to actual demand. This reduces energy waste and improves overall system stability, which is particularly important in environments with variable load profiles.

Reliability expectations remain unchanged, but the conditions under which reliability must be delivered are becoming more complex. Cooling systems must maintain stable operation during both normal and peak conditions, often with very limited tolerance for disruption.

At the same time, another constraint is becoming more visible. Water. In Australia, where water availability and management are ongoing considerations, the volume of water used in cooling is receiving increasing attention alongside energy consumption. This is shifting sustainability from a reporting exercise to a design consideration.

Taken together, these pressures are changing the way cooling is designed and discussed. Cooling is no longer a passive system that supports compute. It is an active constraint that defines what is possible. The organisations that respond effectively will be those that approach cooling as an integrated system, designed to operate under real conditions and optimised over time.

Source: Optimising Data Center Cooling Efficiency During Transformational Growth (Grundfos 2026)