While modern data centers ought to be highly integrated systems, in practice many still operate as distinct sets of assets and principles. This traditional separation between white space and gray space infrastructure isn’t fit for purpose. By integrating the two, you’ll not only optimise operations, but better prepare your data centers for AI workloads.

What are gray and white space?

Grey space refers to the critical infrastructure of a data center – power, cooling, and energy distribution. White space includes IT equipment and workloads – servers, storage, networks, and compute.

The two have traditionally been planned, monitored, and managed separately – a distinction which made sense when data center demand and operation have been relatively predictable. But as AI workloads require ever-higher rack densities and faster deployment cycles, demand is greater and more volatile than ever. AI workloads can require sudden shifts in power draw and utilization that legacy planning assumptions struggle to accommodate.

There are also significant macroeconomic and industry pressures to account for, including new energy regulations and sustainability reporting expectations, as well as systemic tension between grid capacity and power demand.

• Fewer than half of data center operators are tracking the metrics needed to assess their sustainability and meet pending regulatory requirements.
• Data centers currently consume around 2.5 percent of the UK’s electricity, with consumption expected to rise four-fold by 2030.
• In Europe, data center power demand will rise to 236TWh, or 5.7 percent of the total European power demand by 2035.

To match the growth and sophistication of the infrastructure needed in this landscape, operators have to make every effort to unify visibility and operational methodologies. Decisions made in white space have immediate and material consequences in gray space – and vice versa. Managing the two separately is a structural vulnerability.

The impact of working in silo

When grey and white space operate independently, teams only work with part of the picture. Facilities teams have insight into conditions of existing infrastructure but lack an intuitive understanding of power workloads or application performance. IT teams may plan new deployments without enough awareness of physical limitations, extra cooling requirements, or the market availability of energy.

This misalignment has practical consequences – duplicated data, conflicting KPIs, and inefficient responses to operational issues. Without real-time, accurate insight into IT workloads, operators tend to run infrastructure conservatively – if done unnecessarily this can lead to lower rack utilisation, higher costs, and reduced power usage efficiency (PUE).

Uptime Institute outage analysis shows human error and communication breakdown are contributing factors in 30-50 percent of data center downtime incidents. Higher, more volatile demand only compounds the impact of these fragilities.

Integration is an operational shift

Connecting grey and white spaces changes operational choices. When teams share a common view, dependencies between areas such as infrastructure planning and IT procurement are more explicit. Teams understand the implications for energy use, safety, budgets, and much more, in a more holistic way, working from the same data and insights.

This shared context reduces guesswork, enables more dynamic planning, and helps decision makers identify potential issues earlier.

Over time, this integration shifts the operating model from reactive intervention towards predictability. Less time and fewer resources are spent on compensating for uncertainty – and operators can align infrastructure management with actual business need.

Finding solutions to unify visibility and optimise management

For most organisations, this level of integration requires a unifying management layer, which can allow operators to visualise and monitor the data center at every level. A Data Center Infrastructure Management (DCIM) platform can bring together data from power, cooling, environmental systems, and IT workloads into one view.

Rather than fragmenting insight across tools, DCIM establishes a consistent source of truth. Operators can see, in real time, how changes in workload affect power draw, thermal conditions, and capacity – and how infrastructure decisions, in turn, affect IT performance.

This enables:

• More accurate, granular capacity planning and rack density
• Faster identification of abnormal data center conditions
• Better coordination between infrastructure and IT teams
• Simpler, more comprehensive reporting of resource utilization

For European markets, where new directives demand strict monitoring of energy consumption and efficiency, integrated DCIM is increasingly used to support grid-aligned operations and efficiency initiatives.

DCIM can also support business continuity, by establishing root causes and enabling teams to take appropriate action. By monitoring device data, DCIM can also create alerts for anomalous conditions, and provide the insight to accelerate response times.

What changes when you get it right

With integrated operations, you can optimise at the systemic level, rather than just honing processes or workflows.

By removing the disconnects between capacity planning and actual energy demands, you can improve rack utilisation and avoid stranded capacity. You can make the best use of existing infrastructure, without impacting safety. Or tune airflow and thermal strategies to real-life data center power draw, instead of worst-case modelling.

All of your key sustainability objectives, from energy efficiency to carbon reporting and water use, become easier to achieve as they are continuously aligned to the operational reality.

Moving forward

The separation between grey and white space is a legacy of a simpler time. Where it persists today, it creates blind spots that organizations can’t afford.

Thankfully, connecting operations doesn’t require abandonment of all established disciplines or responsibilities. Instead, we need to align them, through shared data, tools, and insight.

Data center operators that do so will be better equipped to manage complexity and adapt to changing demand.

If you want to know how you can build connected, efficient data center solutions, talk to the Mitsubishi Electric experts today and we’ll help you take the next steps on your journey.