Understanding Data Center Capacity Planning & Best Practices

Total capacity for data centers worldwide is expanding rapidly. Several markets in 2023 received requests for power that exceeded the current capacity of their power grids, leading to development pipelines that are set to more than double capacity levels. New developments have purchase power agreements that range from 200-400 megawatts (MW) on average, with Google setting a record agreement for 600 MW. To put this in perspective, 1,000 MW equals 1 gigawatt (GW), which could power 876,000 U.S. households for one year.

It’s clear based on these trends that data centers are preparing for massive data use, but capacity planning is also important for individual businesses. Here’s what your organization should know about data capacity planning and how to prepare for your future data needs.

What is Data Center Capacity Planning?

Data centers need to be able to meet both current and future demands. Data center capacity planning keeps the future in mind by strategically managing and planning for future needs of data center infrastructure.

How is Data Center Capacity Measured?

Data center capacity can’t be calculated with just one measurement. Multiple figures are combined to determine capacity, including space, power, cooling, computing resources, and network connectivity.

What Are the Capacity Components of Data Centers?

When each of these capacity components is well-understood, they can be used in combination to pinpoint your business needs.

Power

Servers, storage systems, and network equipment all need a constant and reliable power supply to function properly. Data centers have a primary power source and typically more than one source of backup power, such as uninterruptible power supplies (UPS) and generators. Looking at power in terms of data center capacity also involves how the power is distributed throughout the facility.

Cooling

Robust cooling systems are also necessary to keep data center components cool and working without breaking. Air conditioning systems, airflow management, and liquid cooling can all be used to keep temperatures low in the building and with specific equipment.

Data Storage

Data can be stored in massive amounts in data centers via hard disk drives (HDDs), solid-state drives (SSDs), and tape libraries. HDDs are used for long-term storage, whereas SSDs are typically used for data that requires quick access. Tape libraries can be added for archival records.

Network Connectivity

The network connectivity in a data center determines the speed at which information is exchanged. Facilities need high-bandwidth connections to allow for communications between servers and storage systems, as well as external network connections that go to private networks or the internet.

Physical Space

Making the most of a data center means making the most of the space, including with optimized server racks and hot aisle/cold aisle containment. The more businesses optimize their footprint, the more room they have to expand in the future.

Disaster Recovery

Disaster recovery isn’t necessarily a traditional capacity component. However, it is important for improving data center resilience, and businesses need to ensure they have sufficient resources to support DR initiatives. This can include power and cooling redundancies, backup sites, and data replication measures.

Why Does Data Center Capacity Planning Matter?

Capacity planning is important largely due to the exponential growth of data and subsequent demands placed on data center infrastructure as a result of this growth. Total capacity for data centers is set to at least double in most regions, with the U.S. development pipeline set to increase capacity 2.5 times over to meet these demands. Surges in data requirements mean a need for more processing power, network bandwidth, and storage capacity.

High-density colocation facilities are also becoming more popular. These facilities concentrate power and cooling in concentrated spaces to support HPC (high performance computing) demands. This places a greater emphasis on the importance of capacity planning to ensure power and cooling distribution are implemented efficiently with an eye on growth.

Underestimating capacity needs can lead to risks, including:

• Downtime
• Performance issues
• Increased costs from hastily provisioned resources

Overprovisioning also leads to problems, such as:

• Wasted resources
• Energy overconsumption
• Reduced scalability
• Agility issues

Key Considerations for Data Center Capacity Planning

Capacity planning isn’t solely about additional capacity in all circumstances. The clearer your picture is on current usage and what capacity you’ll need to support future strategic business initiatives, the more you can balance the performance and costs of your system and focus your attention on emerging technologies that can meet your workload demands.

Understanding Required Capacity

Determinations of capacity can be done at a rack level, row level, and room level:

• Rack-level capacity: How much power, cooling, and space will you need on a single-rack basis?
• Row-level capacity: What does this look like when expanded out to a row of servers?
• Room-level capacity: What does the overall infrastructure look like, and what will it require?

Current and Future Strategic Business Initiatives

Your overall goals and IT strategy should be aligned with your capacity planning. Application roadmaps that include planned deployments and upgrades can help you calculate what might impact data center resource requirements in the near future.

Business Growth Projections and Scalability Requirements

Capacity planning needs to start with the current state of the business and factor in growth projections and scalability needs for the next several years. This can include data storage growth, user base expansion, and additional power, compute, and cooling resources necessary to facilitate growth.

Finding a Balance Between Performance and Costs

Maximizing performance is important for a great user experience and retention rates; however, most businesses are not working with unlimited budgets. Performance needs to be considered alongside costs. Chances are, some workloads will have more vital performance needs than others.

Emerging Technologies and Workload Demands

Emerging technologies often have much greater capacity demands compared to current workloads. Factor in the potential of emerging technologies, such as AI and ML, and what they might mean for your processing power and storage needs in the coming years. Containerized applications and Internet of Things (IoT) devices can also introduce new resource demands.

Capacity Planning Methodologies and Best Practices

When it comes time to engage in data center capacity planning, there are a few approaches you can take and best practices you should consider following.

Top-Down vs. Bottom-Up Capacity Planning Approaches

You may decide to start with either a top-down or a bottom-up capacity planning approach. With top-down, you start with the organization’s overarching IT strategy and business goals and plan the necessary resources from there. What do you project your users, data storage needs, and application usage will look like in the years to come?

A bottom-up approach starts by looking at the existing data center resources, taking stock of all equipment and utilization rates, and planning to eliminate bottlenecks. Employing both approaches will be the most helpful at giving you a comprehensive picture of what’s now and what’s next.

Leveraging Data Center Infrastructure Management (DCIM) Tools

Data center infrastructure management (DCIM) tools can streamline capacity planning by:

• Visualizing your data center layout, allowing you to see where capacity exists for future projects
• Tracking and managing your inventory of current assets
• Monitoring utilization in real-time of power, cooling, and network usage
• Simulating the impact of new equipment deployment on capacity utilization at the data center

Data center managers can use this information to make better plans for the present and future of your capacity needs.

Establishing Capacity Planning Governance and Processes

Because it’s impossible to predict the future with complete accuracy, it’s important to have checks and balances in place for potential overages and point people for the capacity planning process. Develop a governance structure that defines capacity planning roles and responsibilities, sets thresholds and triggers for capacity, and sets an intention for regular policy review.

Utilizing Predictive Analytics and Forecasting

Predictive analytics can use historical data to predict future growth for your resource usage. Even if your business doesn’t have historical data, predictive analytics can build on industry business trends to make informed predictions about future capacity needs. This places you in a proactive, instead of reactive, position.

Performing Continuous Monitoring and Optimization of Plans

Continuous monitoring and adjustments are necessary to optimize data center capacity planning. You can flag problems early and adjust as you go along to make your capacity plans even more effective over time.

Implementing Effective Data Center Capacity Planning Strategies

It’s easier said than done to implement effective capacity planning strategies in a data center. Working with a partner who’s seen it all and planned for it all can make a huge difference. Learn more about TierPoint’s data center services and how we can get you set up for now and later.