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Understanding Data Center Costs and How they Compare to the Cloud

Alon Berger

Product Marketing Manager, Intel Granulate

Data centers are the backbone of modern businesses, housing the critical IT infrastructure that supports an organization’s digital operations. They are complex facilities that require significant resources to build, maintain, and operate. Understanding the costs involved in building and maintaining data centers can help organizations budget effectively and optimize their spending.

We’ll provide a breakdown of data center costs, covering infrastructure and construction costs, servers and storage units. The goal is to provide you with a clear understanding of the financial commitment involved in setting up a data center, and compare it with other relevant options such as running IT operations in the cloud.

In this article:

5 Main Components of Data Center Costs 

1. Infrastructure and Construction costs

Building an entire data center from scratch requires a substantial financial investment. This begins with securing land in a location that is not prone to natural disaster risks and has access to necessary utilities. The building needs to be robust, capable of withstanding natural and man-made disasters, and should be scalable to accommodate future growth.

However, smaller organizations can create a data center as part of an existing office space. A single server room, properly equipped, can serve as an initial data center for a startup or smaller company, and can be scaled up as needed.

The design of a data center greatly contributes to its setup cost. This includes the layout of the server rooms, cabling systems, access points, and security systems. Additional costs might be incurred for installing fire suppression systems, redundant power supplies, and HVAC systems.

2. Servers and Storage Units

Servers and storage units form the backbone of any data center. The type and number of servers needed will depend on the intended use of the data center. For a small business, a few servers might suffice, but larger enterprises may require hundreds, if not thousands of servers. 

Similarly, the storage requirements will vary, with larger businesses requiring more extensive and more expensive storage solutions. It’s also important to remember that these servers and storage units will need to be replaced or upgraded periodically, adding to the overall cost.

3. Software Licenses

Software licenses are a critical component of data center costs, encompassing the operating systems, database management systems, networking software, and various applications needed for data center operations. These licenses can be expensive, particularly for enterprise-level software, and often require renewal on an annual or multi-year basis. Additionally, the cost can increase significantly as the number of users or the scale of operations grows.

Besides the direct costs of purchasing software licenses, organizations must also consider the costs of compliance and software audits. Non-compliance with software licensing agreements can lead to hefty fines and legal issues. Proper management of software assets, therefore, becomes crucial, and may involve additional investments in software asset management tools and expertise.

4. Power

Power consumption is one of the most significant ongoing costs in a data center. The energy required to run servers, storage units, networking equipment, and other IT hardware constitutes a major portion of operational expenses. Data centers consume large amounts of electricity, not only to power the IT equipment but also to run the cooling systems that prevent overheating.

The cost of electricity varies depending on the geographical location of the data center and the local energy prices. To mitigate these costs, some data centers invest in energy-efficient technologies or alternative energy sources like solar or wind power. Energy-efficient practices and equipment can reduce power usage effectiveness (PUE), a key metric for assessing a data center’s energy efficiency.

5. Network Connectivity

Network connectivity costs in a data center encompass the expenses related to internet bandwidth, internal networking equipment like switches and routers, and the labor costs of network management and maintenance. High-speed and reliable connectivity is essential for modern data centers, especially those handling large volumes of data or offering cloud services.

The cost of network connectivity can vary widely, depending on the bandwidth requirements, the quality of service agreements, and the geographic location of the data center. For instance, data centers located in areas with limited connectivity options may face higher costs. Additionally, as data centers scale up, the complexity and cost of maintaining a robust network infrastructure also increase.

6. Cooling

Cooling is a crucial and often expensive part of data center operations. The heat generated by servers and other equipment must be efficiently dissipated to prevent hardware malfunctions and extend the lifespan of the equipment. Cooling systems, such as HVAC (heating, ventilation, and air conditioning) units, require significant energy consumption, contributing further to the operational costs.

The cost of cooling a data center can vary based on several factors, including the size of the facility, the climate in which it’s located, and the type of cooling technology used. Advanced cooling techniques, such as liquid cooling or the use of ambient air, can offer more energy-efficient solutions but may require higher initial investments. As such, balancing cooling needs with cost and energy efficiency is a critical aspect of data center management.

Learn more in our detailed guides to:

  • Data center energy consumption (coming soon)
  • Data center energy efficiency (coming soon)

Building a Data Center: Cost Examples 

Now that we have a breakdown of the various costs involved in building and maintaining a data center, let’s look at some examples of how these costs might add up for different types of data centers. The figures below are only rough estimates, relevant for the United States. Actual data center costs can greatly vary depending on location and specific requirements. 

Small Data Center

A small data center, also known as a micro data center, typically serves small businesses or remote office locations, with a capacity of up to 10 racks. A typical rack has 42 units, and because the average server takes up three units (3U), a rack can typically house around 14 servers. This means a 10-rack data center can house in the region of 140 servers. 

The cost to build a small data center can range from $200,000 to $500,000. This includes costs for constructing the physical facility, purchasing and installing the necessary hardware, and setting up the cooling and power systems.

However, this is just the initial investment. Running the data center will also incur costs, such as electricity bills for powering the servers and cooling systems, maintenance and repair costs, and salaries for the IT staff managing the data center. These costs can add up to around $50,000 to $100,000 per year.

Mid-Sized Enterprise Data Centers

Mid-sized enterprise data centers have a capacity of up to 100 racks (or around 1,400 servers). The cost to build a mid-sized data center can range from $2 million to $5 million. Again, this includes the costs for building construction, hardware purchase and installation, and setting up the power and cooling systems.

The running costs for a mid-sized data center can be significantly higher than that of a small data center. Depending on the specific requirements and usage patterns of the business, these costs can range from $200,000 to $500,000 per year.

Large “Telco Room”

Lastly, we have the large “Telco Room,” which is essentially a large-scale data center that serves major telecommunications companies or large enterprises, with a capacity of over 250 racks (3,500 servers). The cost to build such a data center can easily run into tens of millions of dollars. The running costs can also be substantial, easily exceeding $1 million per year.

How Do Data Center Costs Compare to Cloud Costs?

In the past, setting up a data center was the only way organizations could manage large-scale computing operations. However, today an attractive alternative is cloud computing services like Amazon Web Services or Microsoft Azure. 

Here are a few key considerations for comparing data center cost and effort to the cost of hosting the same resources in the cloud:

  • Capital expenditure vs. operational expenditure: Data centers require significant capital expenditure (CapEx), as seen in the costs for infrastructure, servers, and licenses. Cloud computing often involves operational expenditure (OpEx), with costs based on usage. This model can be more flexible and scalable, adjusting to business needs without large upfront investments.
  • Maintenance and upgrade costs: Owning and maintaining a data center involves ongoing expenses for upgrades, maintenance, and staffing. Cloud services, managed by providers, eliminate the need for in-house maintenance and reduce the staff required for IT infrastructure management.
  • Scalability and elasticity: Cloud services offer greater scalability and elasticity. Businesses can quickly scale resources up or down as needed, a flexibility not readily available with physical data centers. This adaptability is particularly beneficial for businesses experiencing fluctuating or unpredictable workloads.
  • Energy and cooling costs: Energy consumption and cooling are major cost factors for data centers. Cloud providers, due to their scale, often employ more efficient and innovative energy management solutions, potentially offering a more eco-friendly option.
  • Security and compliance costs: Maintaining security and compliance in data centers is both complex and costly. Cloud providers generally offer high-level security and regular compliance updates, reducing the burden on individual businesses.
  • Location and accessibility: Cloud services provide global accessibility, an advantage over physical data centers which are geographically fixed. This can be crucial for businesses with a widespread workforce or client base.
  • Downtime and reliability costs: Cloud providers typically guarantee high uptime percentages, backed by Service Level Agreements (SLAs). Managing this in-house can be challenging and costly, requiring redundant systems and robust backup solutions.
  • Business focus and expertise: Managing a data center requires significant IT expertise. Cloud services allow businesses to focus on core activities rather than IT infrastructure management.

Cloud computing requires lower upfront costs and a much smaller organizational effort than setting up your own data center. However, in many cases the long-term total cost of ownership (TCO) of an in-house data center can be significantly lower than hosting the same resources in the cloud.

Learn more in our detailed guidea to:

  • Data center optimization (coming soon)
  • IT infrastructure costs  (coming soon)

Data Center Cost Optimization Strategies 

If you do decide to build your own data center, despite the appealing option of outsourcing the effort to a cloud provider, here are a few strategies to reduce and optimize your costs.

Virtualization and Server Consolidation

Virtualization and server consolidation are two effective strategies for optimizing data center costs. Virtualization involves running multiple virtual machines on a single physical server, thereby reducing the need for physical hardware. This not only reduces hardware costs but also saves on power and cooling, as fewer servers generate less heat.

Server consolidation involves combining multiple servers into a single, more powerful server. This reduces the number of servers needed, thereby saving on hardware, power, and cooling costs. Additionally, by reducing the physical footprint of the data center, businesses can also save on space and facility costs.

Improving Energy Efficiency

Energy consumption is one of the biggest costs associated with running a data center. Therefore, implementing energy efficiency measures is a key strategy for reducing data center costs. This can involve a range of actions, from adopting energy-efficient equipment, to improving the design and layout of the data center to optimize airflow and reduce cooling needs.

Other energy-saving measures include using renewable energy sources, implementing power management software, and adopting energy-efficient practices such as powering down idle equipment. By reducing energy consumption, businesses can not only save on utility bills but also reduce their carbon footprint and improve their environmental sustainability

Measuring Data Center Performance Metrics and KPIs

Performance metrics and key performance indicators (KPIs) are crucial tools for managing data center costs. They provide a quantifiable measure of the effectiveness and efficiency of data center operations, and can help identify areas for improvement. Common data center metrics include power usage effectiveness (PUE), server utilization, and availability.

By regularly monitoring these metrics, businesses can gain a better understanding of their data center performance and take proactive measures to improve it. For example, if the PUE is high, it may indicate that the data center is not using power efficiently, and energy-saving measures may be needed. Similarly, if server utilization is low, it may suggest that there is potential for server consolidation or virtualization.

Learn more in our detailed guide to data center KPIs (coming soon)

Adopting Modular Data Center Designs

Modular data centers are a newer design approach that can offer significant cost savings. Rather than building a large, monolithic data center, a modular design allows for the construction of smaller, standalone modules that can be added or removed as needed. This provides greater flexibility and scalability, allowing businesses to more closely match their data center capacity to their actual needs.

In addition to the cost savings associated with a smaller physical footprint, modular data centers also offer other benefits such as faster deployment times, improved energy efficiency, and reduced maintenance costs. By adopting a modular design, businesses can achieve a more agile and cost-effective data center strategy.

Learn more in our detailed guide to data center design (coming soon)

Right-Sizing and Demand Management

Right-sizing and demand management are two important strategies for optimizing data center costs. Right-sizing involves ensuring that the data center capacity is appropriate for the current and expected future needs of the business. This includes not only the physical capacity (such as the number of servers and storage devices), but also the network capacity and the ability to handle peak loads. By right-sizing their data centers, businesses can avoid over-provisioning and reduce unnecessary costs.

Demand management involves managing the demand for data center resources to match the available supply. This can involve techniques such as load balancing, demand forecasting, and capacity planning. By effectively managing demand, businesses can ensure that their data centers are not overwhelmed during peak periods, and that resources are not wasted during off-peak periods.

Implementing Automation and AI

Automation and artificial intelligence (AI) are two key technologies that can greatly enhance the efficiency of data center operations. By automating routine tasks such as server provisioning, incident management, and performance monitoring, businesses can significantly reduce the time and effort required to manage their data centers. This not only reduces labor costs but also minimizes the risk of human error, which can lead to costly downtime or data loss.

AI-based systems, commonly known as AIOps, can provide valuable insights into data center operations and identify opportunities for improvement. For example, machine learning algorithms can analyze performance data to detect anomalies, predict future trends, and recommend optimal configurations. By leveraging AI, businesses can make more informed decisions and proactively address potential issues before they become major problems.

Learn more in our detailed guide to data center automation (coming soon)

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