Enterprises need a data center matched to their workloads, growth plans and recovery requirements—not a single prescribed architecture. Whether infrastructure is owned, colocated, cloud-based or hybrid, assess capacity, power and cooling, resilience, operating practices, efficiency, sustainability measurement, deployment timing and total cost together.
What does “modern” mean for an enterprise data center?
Modern means adaptable and fit for the work it must run. A facility that suits steady, lower-density workloads may not suit high-density computing, and a design that works for one enterprise may not be right for another. The U.S. Department of Energy’s Federal Energy Management Program (FEMP) guide explicitly cautions that no guide can prescribe the most energy-efficient design for every data center scenario.
Start with the demands the infrastructure must meet: current and forecast workload volume, compute intensity, latency, recovery objectives, location constraints and the time available to deploy. Then test whether power, cooling, space, people and operating procedures can support those demands over the facility’s expected life.
How much capacity—and what kind—will workloads need?
Capacity planning should account for both total demand and how concentrated it is. High-density cabinets can make power delivery and heat removal the limiting factors even when a site has unused floor space. Consider the most demanding rack, not just the average, and determine whether an existing data hall can be retrofitted if workload density rises.
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Uptime Institute’s 2024 survey of data center owners, operators and vendors reported an average typical rack density of 8 kW. Excluding 11 sites that reported their highest rack density above 50 kW, the calculated average was 7.1 kW. These are survey results, not recommended design targets. In the same survey, 29% of operators said they were upgrading existing data hall space to deliver power and cooling to higher-density cabinets.
That growth pressure affects existing facilities as well as new builds. In Uptime Institute’s July 2024 survey announcement, executive director of research Andy Lawrence said: “In 2024, we see the challenges of increased demand impacting power and cooling capabilities of existing facilities and the need for further investment to keep up with the demand.”
Questions to settle before committing capacity
- Which workloads need to run in this location, and how are their compute, storage and network needs expected to change?
- What is the highest rack density the design must support, and can power and cooling be delivered to those cabinets?
- What spare capacity is available now, and what retrofit work, lead time or disruption would expansion require?
- How will demand be monitored so that deployment plans can change as actual workloads evolve?
How should workload location shape the plan?
Owned facilities, colocation and cloud are options to compare, not mutually exclusive answers. Uptime Institute’s 2024 survey estimated that 55% of surveyed organizations’ IT workloads were hosted off-premises. Respondents forecast that share would reach 58% by 2026; this is a forecast from the 2024 survey, not a verified measurement of 2026 workloads.
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Use workload characteristics and business constraints to decide placement. Compare latency, growth, density, power and cooling needs, recovery requirements, deployment timing, geographic or regulatory constraints, staffing and total cost. A hybrid plan can place different workloads where they fit best and can change over time; it also requires clear responsibility for dependencies and operations across locations.
| Option | Questions to evaluate |
|---|---|
| Owned data center | Can the enterprise fund and operate the required capacity, power, cooling, resilience and staffing? What are the build or retrofit timeline and long-term costs? |
| Colocation | Can the site supply the required density, power and cooling, meet recovery and location requirements, and provide clear operating responsibilities and expansion options? |
| Cloud | Does the service meet workload, latency, recovery, location and cost requirements? Which infrastructure and operating responsibilities remain with the enterprise? |
| Hybrid | Which workloads belong in each environment, and how will the enterprise manage connectivity, recovery, security and operational dependencies across them? |
The survey figures describe respondents’ workloads and expectations; they do not prove that any one placement model is best for a particular enterprise.
What makes a data center resilient?
Resilience depends on the whole chain of dependencies—not just whether equipment is redundant. Assess how power enters and is distributed through the facility, how cooling supports IT equipment, how networking and IT systems depend on that infrastructure, and how the site recovers from failures. Test the design against the organization’s recovery objectives and the failure scenarios that could interrupt its workloads.
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Power distribution deserves particular scrutiny. In the Uptime Institute Global Data Center Survey 2024, on-site power distribution was attributed as the cause of 54% of surveyed respondents’ most recent impactful outages (n=97). IT systems and networking together accounted for 23% of impactful outages. These are survey responses, not universal outage rates.
Resilience includes operating practice
Equipment alone does not determine reliability. Uptime Institute reported that four in five surveyed operators believed their most recent significant downtime incidents could have been prevented with better management, processes or configuration. That is respondents’ assessment, not independent proof of causation. Include staffing, documented procedures, configuration control, testing and incident learning in resilience planning.
At rack level, power distribution and monitoring are part of the design conversation. A rack-mounted PDU can distribute power to equipment and provide monitoring features depending on its specification, but it cannot by itself prevent outages or substitute for facility-level electrical design, capacity planning and operating controls.
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How can enterprises improve energy efficiency?
Efficiency is a system-level problem: IT equipment, room conditions, air management, cooling, electrical systems and heat recovery interact. DOE FEMP’s data center guide addresses those areas as well as measurement and benchmarking. Use the guide’s categories to identify opportunities, then evaluate them against the site’s workloads, constraints and operating conditions rather than treating any single design as universally optimal.
Measure performance consistently and use the results to guide changes. Power consumption and Power Usage Effectiveness (PUE) are useful parts of the picture, but they do not describe every sustainability impact. Pair them with water-use information and, where relevant to the site and its reporting goals, heat-reuse opportunities.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What should a sustainability measurement plan include?
Choose measures that support decisions and reporting, not only a headline score. Uptime Institute’s April 2025 survey results showed that among owner/operator respondents, 79% reported tracking IT or data center power consumption for sustainability purposes, 72% tracked PUE and 45% tracked water usage. The overall survey included 974 industry respondents; owner/operator response bases varied by question.
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In the same 2025 survey, 42% of respondents reported an enterprise-wide data center renewable-energy goal and 26% an enterprise-wide carbon-free energy consumption goal. These are reported goals, not evidence that the goals had been achieved.
Build measurement around decisions
- Define which facilities, workloads and reporting periods each measure covers.
- Track power and PUE alongside water use so that efficiency comparisons do not overlook resource trade-offs.
- Set out how measurements relate to enterprise sustainability goals, including renewable or carbon-free energy goals where applicable.
- Assess whether heat recovery or reuse is practical for the site and its surrounding context.
- Check that collection methods are consistent enough to compare performance over time and support reporting.
How should enterprises evaluate cooling choices?
Evaluate cooling against actual rack density, facility conditions, reliability requirements, operating capability and efficiency goals. Avoid selecting a technology based only on a broad claim that it is more modern or more efficient; the available evidence does not establish a universally best cooling technology or target PUE.
The Uptime Institute Global Data Center Survey 2024 report stated: “The reliability of liquid cooling is, as yet, untested at scale in the field.” Treat that as the report’s 2024 publication-context statement, not as a current universal verdict on every liquid-cooling deployment. For a specific project, establish the system’s suitability and operating requirements with the relevant provider or engineering team.
What decision framework can compare ownership, colocation, cloud and hybrid plans?
Use the same criteria across candidate plans so that a low initial cost or a headline efficiency metric does not hide a mismatch elsewhere. The appropriate balance depends on the workload and the enterprise’s requirements; the available DOE and Uptime Institute sources do not name one best architecture, provider or target PUE.
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1Repair Windows errors before they cause bigger problems2Fix the driver behind crashes, sound loss and screen glitches3Clear out junk files and repair common Windows errors- Define workload fit. Document workload growth, latency needs, the most demanding rack density, recovery objectives and any geographic or regulatory constraints.
- Test capacity and resilience. Compare available power and cooling, redundancy, failure dependencies, expansion options and recovery capabilities against the workload requirements.
- Compare efficiency and resources. Assess energy performance alongside water use, measurement capability and heat-reuse opportunities.
- Assess operations. Identify staffing needs, responsibility boundaries, procedures, testing practices and how incidents will be reviewed and learned from.
- Evaluate delivery and cost. Compare deployment timing, retrofit or migration effort, geographic fit and total cost over the relevant planning period.
- Plan for change. Decide how capacity and workload placement will be reviewed as demand, technology and business needs evolve.
Make the trade-offs explicit. A plan that meets today’s workload but cannot expand on time, recover within required objectives or produce the measurements needed for sustainability reporting may not meet the enterprise’s broader needs.
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