Hyperscale data centers, operated by large companies known as hyperscalers, have emerged as the primary providers of digital infrastructure, encompassing cloud services and supporting the seamless functioning of the internet. As a result, these hyperscalers play a critical role in meeting the growing demands for computing power, storage, and network capabilities in today’s data-driven world.

Hyperscale refers to a computing infrastructure’s ability to rapidly and efficiently scale with demand, especially in data centers and cloud platforms, by adding resources like servers and storage. Key hyperscalers include AWS, Microsoft Azure, Google Cloud, Meta Platforms, Apple, and TikTok.

Dgtl Infra delves deeper into the concept of hyperscale, its implications for data centers, and the companies driving this trend, including cloud providers and large internet companies. Continue reading to uncover the innovations behind hyperscale servers and how they are reshaping the future of cloud computing and internet services.

What is Hyperscale?

Hyperscale refers to the ability of computing infrastructure to expand rapidly and efficiently in response to increasing demand. This concept is often associated with data centers and cloud computing platforms, where systems are designed to seamlessly scale-out by adding more resources, such as servers, storage, and networking components, as needed.

Hyperscale Forms Backbone of Digital Cloud Computing Over Earth At Night

Hyperscale data centers have become the backbone of many cloud service providers (CSPs). Companies like Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP) utilize hyperscale computing to offer businesses and individuals affordable, on-demand computing resources.

Hyperscale computing has also attracted the interest of enterprises, particularly large internet companies, such as Meta Platforms (Facebook). As big data, artificial intelligence (AI), and the Internet of Things (IoT) continues to grow, many hyperscalers are investing in scalable, flexible, and efficient hyperscale data centers.

Hyperscale Data Centers

Hyperscale data centers, also known as cloud data centers, are massive, centralized, highly-efficient, and custom-built computing facilities that are operated by a single company. These facilities support primarily cloud service providers (CSPs) and large internet companies with enormous compute, storage, and networking requirements.

Example of Hyperscale Data Center Exterior of Google Cloud in Lenoir Caldwell County North Carolina
Google’s Hyperscale Data Center in Lenoir, Caldwell County, North Carolina.

The hyperscale data center market is significant by any measurement. In 2023, the global leasing of data center power capacity exceeded 6 gigawatts (GW), including rights of first refusal (ROFRs), rights of first offer (ROFOs), and reservations. Notably, over 4.5 GW of this demand originated from North America and the bulk of these leases were for hyperscale data centers. Furthermore, global data center capital expenditures in 2023 surpassed $200 billion, with hyperscale developers contributing over $125 billion (more than 60%) towards building these massive facilities.

The key characteristics and benefits of hyperscale data centers are size and scalability, distributed computing, energy efficiency, high computing power, automation, and cost-effectiveness.

1) Size and Scalability

Hyperscale data centers are immense in size and have the ability to seamlessly scale infrastructure in response to demand. They are much larger in scale compared to typical enterprise data centers.

These hyperscale facilities often house tens of thousands or even millions of servers, storage devices, and networking components, providing vast amounts of computing resources. Furthermore, through the use of server virtualization, hyperscale data centers can operate millions of virtual machines (VMs), enhancing their computing capabilities to support numerous customers and applications.

Hyperscale data centers are typically built with scalable power capacity for requirements of 5 to 100 megawatts (MW) across 50,000 to 1+ million square feet of space. As such, these hyperscale data center facilities can cost upwards of $1 billion to construct.

To scale capacity efficiently, hyperscale data centers employ a modular design approach, utilizing standardized, pre-fabricated components for rapid deployment, expansion, and simplified maintenance – without compromising performance. This design strategy enhances flexibility, allowing individual components, such as power and cooling modules, to be replaced or upgraded without disrupting the entire system.

2) Distributed Computing

Distributed computing is a key characteristic of hyperscale data centers, where computing tasks are broken down into smaller, manageable tasks that are processed simultaneously across multiple servers or nodes to ensure efficient and reliable processing. These servers are interconnected by high-speed networking switches, forming a pool of resources that enables enterprises to build, manage, and deploy applications anywhere, from large cloud data centers to smaller edge locations.

Cloud service providers (CSPs), such as Amazon Web Services (AWS), play a crucial role in enabling distributed computing by constructing and maintaining cloud regions and availability zones (AZs) across the globe. Simultaneously, edge computing services, such as AWS Outposts, extend CSP infrastructure, services, APIs, and tools to virtually any data center, colocation facility, or on-premises location.

Diagram of Cloud Regions with Three Availability Zones Example for Hyperscaler

Distributed computing enhances performance for a wide range of applications and workloads, as well as provides redundancy and fault tolerance. In the event of a hardware failure, tasks can be automatically redistributed to other servers, minimizing the impact on the overall system.

3) Energy Efficiency

Energy efficiency is a crucial consideration for hyperscale data centers, as their enormous size and power requirements can lead to significant environmental impacts and operational costs. Dynamic provisioning of resources, advanced cooling systems (e.g., liquid cooling, free cooling, or adiabatic cooling), energy-efficient servers, and the use of renewable energy sources are all employed to minimize energy consumption and reduce the overall carbon footprint of these facilities.

Energy Efficiency in Data Center Shown Through Glass Windows Overlooking Wind Turbines in Field

Energy consumption for data centers is typically measured using an efficiency metric known as power usage effectiveness (PUE). Specifically, PUE is the ratio of the total amount of electricity consumed by a data center, including power distribution and cooling, to the amount of electricity delivered to its IT equipment – with a metric closer to 1.0 being optimal.

As shown below, hyperscale data center operators like Microsoft Azure, Google Cloud, Alibaba Cloud, and Meta Platforms (Facebook) all report a substantially lower PUE – in the range of 1.05 to 1.25 – as compared to the average enterprise data center, which achieves a PUE of 1.58, according to the Uptime Institute’s Global Data Center Survey.

Power Usage Effectiveness (PUE) Comparison

Data Center OperatorPower Usage Effectiveness (PUE)
Alibaba Cloud1.22
Meta Platforms (Facebook)1.08
Data Center – Average1.58

Major hyperscalers Amazon, Microsoft, Google, and Meta Platforms (Facebook) have all undertaken extensive renewable energy projects, utilizing solar and wind power to reduce their carbon footprints, promote sustainable operations, and power their data centers.

These initiatives involve investing in and constructing on-site solar panels and wind turbines, often with capacities of several hundred megawatts, as well as purchasing renewable energy directly via Power Purchase Agreements (PPAs) or via market-based instruments, such as Renewable Energy Certificates (RECs).

4) High Computing Power

Hyperscale data centers are designed to deliver immense computing power, capable of processing and storing vast amounts of data at high speeds. This is achieved through the use of powerful servers, high-speed networking, and specialized hardware, such as solid-state drives (SSDs) and graphics processing units (GPUs).

Superior computing performance enables hyperscale facilities to support a wide range of demanding applications, including artificial intelligence (AI) and machine learning (ML) workloads, big data analytics, augmented reality (AR) & virtual reality (VR), and video rendering.

To support these demanding applications, hyperscale data centers often operate at power densification levels of 10 kW per rack to 14 kW per rack, which is higher than traditional data centers at approximately 5 kW per rack. These data centers support more complex IT requirements and benefit from economies of scale to implement sophisticated infrastructure and power-intensive, high-density computing.

5) Automation

Automation is a core characteristic of hyperscale data centers, enabling them to efficiently manage and optimize their vast infrastructure. This includes automated monitoring, maintenance, and resource allocation, as well as the use of artificial intelligence (AI) and machine learning (ML) to predict and respond to potential issues. Automation helps to reduce the operational complexity and human intervention required to manage these large-scale facilities, as compared to enterprise data centers.

Software-defined networking (SDN) is an example of how automation is used in hyperscale data centers, particularly because it enables centralized management and configuration of network behavior through software. SDN allows operators to swiftly provision and adjust network resources in response to changing demands, ensuring efficient resource utilization and streamlined management in large-scale computing environments.

6) Cost-Effectiveness

Hyperscale data centers are cost-effective due to their ability to leverage economies of scale, modular design, and energy-efficient technologies, significantly reducing both capital expenditures and operational expenditures. The large scale of these facilities allows them to procure hardware and software at lower costs, while the modular design approach and use of standardized components also contribute to cost savings by simplifying deployment, maintenance, and upgrades.

Additionally, hyperscale data centers employ advanced cooling systems, energy-efficient hardware, and sophisticated power management techniques, reducing energy consumption and lowering operational costs over time. Finally, a hyperscale facility is often located on the outskirts of a major city, providing cost advantages in power procurement and land for construction.

Hyperscale Companies

Hyperscale companies, also known as hyperscalers, include both cloud service providers (CSPs) and large internet companies with enormous compute, storage, and networking requirements. Currently, over 25 companies worldwide are recognized as hyperscalers, collectively operating more than 500 data centers.

Hyperscale Cloud Providers

Hyperscale cloud providers offer a wide range of services that cater to various computing needs, such as Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). These cloud service models enable customers to access scalable and cost-effective computing resources, storage, and networking capabilities.

Examples of Major Hyperscalers Amazon Web Services Microsoft Azure Google Cloud GCP

The most prominent hyperscale cloud providers are Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP), and Oracle Cloud, which are highlighted below:

Amazon Web Services (AWS)

Amazon Web Services (AWS), the cloud computing service of Amazon.com, is the largest hyperscale cloud provider globally. AWS has 32 cloud regions and 102 availability zones in operation, with plans to launch 4 more cloud regions and 12 more availability zones.

Globally, the data center portfolio of AWS totals 33.5 million square feet, of which the company leases 18.0 million square feet (54% of total) and owns 15.4 million square feet (46% of total).

READ MORE: Amazon Web Services (AWS) Data Center Locations

Microsoft Azure

Microsoft Azure is the cloud computing services arm of Microsoft. Azure is the second largest hyperscale cloud provider globally with 62 cloud regions and 120 availability zones in operation.

Globally, the data center portfolio of Microsoft Azure totals over 200 facilities, which are linked together by more than 175,000 miles of fiber optic lines.

READ MORE: Microsoft Azure’s Data Center Locations

Google Cloud Platform (GCP)

Google Cloud Platform (GCP), part of Alphabet Inc, is the third largest hyperscale cloud provider globally.

There are currently 39 cloud regions and 118 availability zones in operation by Google Cloud. These cloud regions and availability zones are situated throughout the United States, Americas, Europe, and Asia Pacific.

READ MORE: Google Cloud’s Data Center Locations

Oracle Cloud

Oracle Corporation’s cloud computing unit, known as Oracle Cloud Infrastructure (OCI), is a key provider of cloud services globally.

There are presently 46 cloud regions and 56 availability zones in operation by Oracle Cloud. These cloud regions and availability zones are located throughout the United States, Canada, Europe, the Middle East, & Africa (EMEA), Latin America, and Asia Pacific.

READ MORE: Oracle Cloud’s Data Center Locations

Large Internet Companies

Large internet companies utilize hyperscale data centers to deliver their products and services to end users. These hyperscale companies include Meta Platforms (Facebook), Apple, TikTok (ByteDance), Uber, Twitter, Salesforce, NVIDIA, and LinkedIn.

Meta Platforms (Facebook)

Meta Platforms owns and operates 24 hyperscale data center campuses globally, comprising over 53 million square feet. Geographically, these hyperscale data centers are located throughout the United States, as well as parts of Europe (Denmark, Ireland, Sweden) and Asia Pacific (Singapore). Additionally, Meta leases further data center capacity, in additional locations, from third-party operators like Digital Realty and CyrusOne.

Meta designs and builds its data centers and technical infrastructure so that it can serve its products, which include Facebook, Instagram, Messenger, Threads, and WhatsApp.

READ MORE: Meta Platforms (Facebook) Data Center Locations


Apple operates eight hyperscale data centers located in the United States, Denmark, and China. At full build-out, these facilities will collectively comprise approximately 10 million square feet. Additionally, two more data centers are under development by Apple, in the United States and Europe, which would bring the company’s total portfolio to 10 data centers upon completion.

Apple’s data centers help power the company’s growth in services, including iCloud, App Store, Apple Maps, Apple Music, Apple Pay, Apple TV+, iMessage, and Siri.

READ MORE: Apple’s Data Center Locations

Other Large Internet Companies

Many large internet companies do not build-out their own infrastructure. Instead, they outsource and lease hyperscale data center capacity from third-party service providers such as Digital Realty, CyrusOne, and CloudHQ. Examples of the large internet companies that lease the majority of their hyperscale data center capacity include TikTok (ByteDance), Uber, Twitter (X), Salesforce, NVIDIA, and LinkedIn.

Hyperscale Servers

Hyperscale servers are high-performance, energy-efficient computing systems specifically designed to support the massive data processing and storage requirements of hyperscale data centers. These servers are built with a focus on scalability, modularity, and cost-effectiveness, and are purchased in volume by the hyperscalers, allowing them to negotiate better prices with suppliers.

Hyperscale Servers and Racks inside a Data Center of Google in Pryor Mayes County Oklahoma
Google’s Hyperscale Servers in Pryor, Mayes County, Oklahoma.

Hyperscale data centers account for more than 50% of all installed data center servers, and according to NVIDIA, approximately 9 million hyperscale servers are deployed each year.

Characteristics of Hyperscale Servers

The key characteristics of hyperscale servers are high-density computing, cost-optimization strategies, and energy efficiency.

1) High-Density Computing

Hyperscale servers are characterized by high-density computing, where a large number of powerful processors (CPUs, GPUs, ASICs), memory, and storage components are packed into a compact form factor. This design approach enables hyperscale data centers to accommodate more computing resources in a smaller footprint, providing the immense processing power needed to support demanding applications and workloads.

2) Cost-Optimization Strategies

Hyperscale data center operators employ various tactics to optimize server costs, including custom hardware designs, standardization, and the use of refurbished equipment.

  • Custom Hardware Designs: Hyperscale infrastructure operators often design their own server hardware tailored to their specific needs. This allows them to optimize server performance and efficiency, and eliminate unnecessary features that add to the cost. For example, AWS Graviton processors are designed to deliver cost-optimized performance for cloud workloads running in Amazon EC2
  • Standardization: Using standardized and modular server designs, hyperscale data center providers can simplify their infrastructure and reduce management overhead. The modular design of hyperscale servers also makes it easier to maintain, replace, and upgrade components as needed, helping to minimize overall costs
  • Refurbished Hardware: Some hyperscale facility operators purchase refurbished or used servers that still meet their performance requirements. This can help to further reduce costs, especially for non-critical workloads or secondary data centers

3) Energy Efficiency

Hyperscale servers are designed with energy-efficient components, such as high-efficiency power supply units (PSUs), voltage regulator modules (VRMs), and advanced cooling systems. These components help to reduce power consumption and improve overall efficiency for hyperscalers.

Hyperscale Server Architectures

Hyperscale server architectures are being designed by initiatives including the Open Compute Project (OCP) and Microsoft’s Project Olympus.

Open Compute Project (OCP)

The Open Compute Project (OCP) is an initiative launched by Facebook (now Meta Platforms), Intel, and Rackspace, among others, in 2011, with the aim of developing open-source hardware designs for data centers. The project focuses on creating highly efficient, cost-effective, and scalable server architectures that can be easily customized and adapted to various use cases.

OCP server designs prioritize energy efficiency, modularity, and simplified maintenance. Organizations can leverage OCP’s standardized server designs to build and deploy hyperscale data center infrastructure more efficiently.

As an example, Meta Platforms has developed the Open Rack enclosure, which is a 21-inch-wide rack design that allows for better airflow and more efficient power distribution compared to the traditional 19-inch-wide rack.

Project Olympus

Project Olympus is a server architecture initiative by Microsoft, contributing to the Open Compute Project (OCP). Launched in 2016, Project Olympus aims to create an open-source, modular, and flexible hardware design for hyperscale data centers. The project focuses on developing a universal motherboard and chassis design that can support various configurations of processors, memory, storage, and networking components.

By providing a customizable and adaptable server architecture, Project Olympus enables hyperscalers to optimize their infrastructure for specific workloads and easily scale their data center capacity as needed.

Mary Zhang covers Data Centers for Dgtl Infra, including Equinix (NASDAQ: EQIX), Digital Realty (NYSE: DLR), CyrusOne, CoreSite Realty, QTS Realty, Switch Inc, Iron Mountain (NYSE: IRM), Cyxtera (NASDAQ: CYXT), and many more. Within Data Centers, Mary focuses on the sub-sectors of hyperscale, enterprise / colocation, cloud service providers, and edge computing. Mary has over 5 years of experience in research and writing for Data Centers.


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