Hyperscale Data Centers: The Future of Computing

Mar 21,2022 by Janvi Anand
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There has never been a greater need for computer infrastructure and data centers than today, with billions of people and tens of billions of devices online. What’s allowing businesses to grow operations more quickly than ever before? Data centers that are hyperscale.

What is the definition of a hyperscale data center?

Traditional data centers are centralized buildings that house vital data and applications for businesses. They store data and provide users with access to resources by utilizing computing and networking systems and equipment.

Hyperscale data centers are substantially bigger than regular data centers, with the ability to hold millions of servers and virtual machines. They provide a highly responsive, scalable, and cost-effective infrastructure that simplifies and streamlines corporate processes. As enterprises’ data storage and use requirements grow, hyperscale data centers will become increasingly important.


Hyperscale data centers are at least 10,000 square feet in size and host over 5,000 servers connected by ultra-high-speed fiber networks. In Fort Worth, Texas, Facebook’s fifth hyperscale data center will consist of five buildings totaling more than 2.5 million square feet.

Hyperscale data centers employ a novel server architecture that has bigger racks that can hold more components and are easily interchangeable to enable flexibility. This allows servers to have various power supplies and hard drives, for example, and hyperscale providers such as Facebook and Google may create supercomputers to meet their demands.


Scaling is used in hyperscale data centers to accept, process, and route traffic. Horizontal scaling to expand the number of machines and vertical scaling to improve the power of machines already in use are examples of this.


A hyperscale data center enables enterprises to control all areas of production through constant automation. This involves managing high-traffic websites and complex workloads such as encryption, genomic sequencing, and three-dimensional graphics that require specialized processing.

The hyperscale’s size

The capacity of a computer system to adapt to rising demand is referred to as “hyperscale.” Computers rely on the resources of a single node or a group of nodes. Increasing processing power, memory, networking infrastructure, or storage resources is often the result of scaling some aspect of our computer system.

The purpose of scaling is to keep constructing a stable system, whether that system is based on the cloud, big data, distributed storage, or a mix of all three, as is becoming more common these days. Of course, “hyper” means “extreme” or “excessive.” Hyperscale is not merely being able to scale, but being able to scale massively and swiftly.

We frequently conceive of scaling “up,” which is a vertical architectural strategy that involves adding additional power to existing devices. However, “scaling out,” or using a horizontal strategy, such as increasing the overall number of devices in your computing environment, is another technique to boost capacity.

Companies deal with hyperscaling in three areas: the physical infrastructure and distribution systems that support data centers, the ability to scale computing tasks (orders of magnitude, both in overall performance and in advancing the company’s status quo), and the financial power and revenue sources of companies that require such hyperscale systems.

Hyperscale’s Rebirth

As our world grows more technologically advanced, the demand for storage and computing services has increased, as needs for facilities to meet these demands.

Large-scale IT infrastructure has been necessitated by two developments. When cloud computing platforms first became popular in the late 2000s, they served as demand aggregators for companies wishing to migrate their on-premises IT workloads to the cloud. Users may provide resources and grow swiftly using cloud platforms, which can be done remotely and almost instantly. These service providers might then estimate future demand and “purchase in bulk” to satisfy it.

Furthermore, the fast emergence of SaaS, streaming, and social media propels the sector forward. To fulfill the demands of their consumers, all three of these sorts of businesses require vast quantities of storage, computing, and bandwidth.

Enterprise vs. hyperscale data centers

A data center, or any structure that houses computer systems and related components such as storage systems and telecommunications, is at the heart of most businesses. These settings also have redundancies in case of power, environmental variables, or security systems failure. The size of your organization and the size of your computing power dictate the size and number of data centers required, however, it is normal for a single data center for a large-scale firm to consume the same amount of electricity as a small town. It’s also very uncommon for a company to merely need one or two of these data centers.

It takes a lot of effort to keep a business data center running smoothly. You’re continuously maintaining the data center’s environment to guarantee uniform machine behavior, setting a patching plan that allows for consistent patches while minimizing downtime, and scrambling to address any type of unavoidable breakdown.

Compare and contrast a small business with a Google or IBM. While there isn’t a single, all-encompassing definition for HDCs, we do know that they are substantially larger facilities than traditional business data centers. When a data center has more than 5,000 servers and covers more than 10,000 square feet, it is considered “hyperscale,” according to market research firm International Data Corporation. Of course, these are the places that only meet the criteria for an HDC. Hundreds of thousands, if not millions, of servers, are housed in some hyperscale data centers.

But, according to IDC, there’s more that distinguishes these types of facilities. Greenfield applications — projects with no limitations – require an architecture that allows for a homogeneous scale-out of hyperscale data centers. Add to it a massive infrastructure that is becoming progressively disaggregated, higher-density, and energy-efficient.

Hyperscale businesses that rely on these data centers have hyperscale requirements as well. While most commercial businesses may rely on off-the-shelf equipment from technology providers, hyperscale businesses must customize practically every component of their computing environment. Adding specialized capabilities at huge sizes, customizing every element of the computing experience, and tinkering with every setting No one can do it better than the corporation can do it for itself at this magnitude. The expense of these demands is what determines who is eligible to join the hyperscale club.

Of course, pricing may be a barrier to entry for organizations that run hyperscale data centers, but it isn’t the issue. That’s what automation is.

Companies that build hyper data centers instead concentrate on automating, or “self-healing,” a word that implies an environment in which unavoidable failures and delays occur, but the system is so well-controlled and automated that it will adjust to the right itself. This self-healing automation is crucial since it promotes great data efficiency.

What Types of People Use Hyperscale?

Hyperscale providers currently own and run three times as many large-scale data centers as they did in 2013. It’s not difficult to guess which firms would be at the top of that list.

Amazon, Microsoft, Google, and IBM all have hyperscale data centers in every major area of the globe, with Facebook, Apple, Oracle, and Alibaba, the Chinese cloud behemoth, not far behind.

At any given time, these A-listers may take down over 70 megawatts and hundreds of thousands of square feet.

Companies with smaller current requirements, but who still desire the opportunity to develop a few megawatts at a time, are next in line. Salesforce, SAP, Dropbox, Twitter, Uber, and Lyft are among its members.

A hyperscale data center’s interior

Quincy, a tiny town in Washington State’s rural core, is home to many hyperscale data centers for firms such as Microsoft, Yahoo, and Dell. The region appeals to these businesses for the same reasons that its farmers do: relatively cool weather, low land prices, and plenty of open space. When you consider how enormous these are, the wide-open expanses are remarkable. Microsoft’s Quincy HDC, one of more than 45 throughout the world, has 24,000 miles of network cable. For a more human-scale comparison, that’s only marginally less than the diameter of the Earth or six Amazon Rivers.

Another Azure-supporting Microsoft HDC is in Singapore, which isn’t exactly a major city. There’s enough concrete in that hyperscale data center to construct a 215-mile-long walkway connecting London and Paris. A hyperscale data center is defined by its scale and complexity. Because so much of the technology is automated, many HDCs employ fewer tech specialists than many business data centers, which rely on a big full-time workforce across a variety of specialties. Indeed, because the data in these centers is the product, it’s likely that hyperscale corporations employ more security personnel than technical personnel at HDCs.

Is Hyperscale Better Than Colocation?

As previously stated, the major data center users all use a build-and-lease method. Many variables influence this, including time, cost, future demands, and others. These colocation providers have gotten more inventive in their pursuit of hyperscale firms, ranging from acting as their development arm to designing to their requirements to just offering a powered shell and allowing the user to supply the inside equipment.

Colocation services are generally used by smaller, but still hyperscale, businesses. These businesses behave more like standard colocation clients, although they usually have long-term expansion plans.

5 Hyperscale Data Centers with the Most Capacity

As of 2021, there will be over 600 hyperscale data centers. We compare the five largest hyperscale data centers and the regions they serve to the traditional definition of a hyperscale data center, which is 5,000 servers in 10,000 square feet. 

The Inner Mongolian Information Center is a place where people may get information about their own country

  • 10.7 million square feet is the total area of the building.
  • The Inner Mongolian Information Hub, one of six data centers in Hohhot owned by China Telecom, is the biggest.

Hohhot Data Center is located in Hohhot, China.

  • 7.7 million square feet in total
  • The second-largest data center is China Mobile’s Hohhot Data Center, which is likewise located in Hohhot’s Information Hub.

The campus of the Citadel

  • 7.2 million square feet in total
  • The Citadel Campus, owned by the multinational technology corporation Switch and located in northern Nevada, is the world’s biggest data center. Up to 650 megawatts of renewable energy are used to power it (MW). Silicon Valley has a latency of 4.5 milliseconds (ms), Silicon Beach has a latency of 9 ms, and Las Vegas has a delay of 7 ms.

Langfang, China-based Range International Information Hub

  • 6.6 million square feet is the total area.
  • The Range International Information Hub is a fourth-generation super data center built in conjunction with IBM and located in Langfang, China, between Beijing and Tianjin.

Las Vegas, Nevada: Switch SuperNAP

  • 3.3 million square feet is the total area of the property.
  • Switch also owns SuperNAP, which is based in Vegas. Up to 531 MW of green energy is used in the SuperNAP.

Hyperscale in the Future

Hyperscale firms continue to dominate the environment, influencing the design, location, and pricing across the board. Even though particular firms may change, the underlying trends of digitization, IoT, and data generation will continue to fuel the demand for more data centers in the future. And hyperscale will make up a significant fraction of these.

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