A data center stack is a way to see how services and applications depend on layers of infrastructure beneath them. At the bottom are the site and facility systems, such as power and cooling; above them are physical compute, network, and storage resources; software abstracts and manages those resources; and services sit at the top. It is a useful mental model, not a universal blueprint: real data centers can draw boundaries differently or combine local infrastructure with cloud services.
How to read a data center stack
Read the stack from the bottom up: each layer supports the one above it. An application may look self-contained to its user, but it depends on service interfaces, managed resources, physical hardware, and the facility that keeps that hardware operating.
Applications and digital services
SaaS / platform services / infrastructure services
Service interfaces, provisioning, and service management
Resource abstraction and control
hypervisors, virtual machines, virtual storage, orchestration/management
Physical IT resources
compute, network, storage
Facility and site resources
power, HVAC/cooling, communications, physical environmentThis practical diagram separates the facility from the IT hardware so their dependencies are easy to see. NIST’s cloud reference architecture groups them together in a single physical-resource layer; its model is a reference architecture rather than a mandatory design for every facility. NIST SP 500-292
What each layer does
1. Facility and site resources
The stack begins with the site and the systems that make computing possible there: power, heating, ventilation and air conditioning (HVAC), cooling, and communications. These are operational parts of the infrastructure, not simply the building around it. A problem at this level can affect the IT resources and services above it.
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2. Physical IT resources
These are the hardware resources workloads ultimately use:
- Compute: servers and their processors and memory.
- Networking: routers, switches, firewalls, links, and network interfaces that move and control traffic.
- Storage: physical media and storage systems that retain data.
NIST’s reference architecture describes these as physical computing resources. The exact hardware mix and arrangement depend on the system’s design; the stack does not prescribe a particular server or rack configuration.
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3. Resource abstraction and control
Software can present physical resources as virtual machines, virtual storage, or managed pools. A hypervisor is one common way to create virtual machines, but abstraction and management can take other forms. This layer allows resources to be allocated and controlled for workloads without requiring each workload to manage the underlying hardware directly.
Orchestration and management tools can help provision and operate those resources. They do not replace the physical layer: they coordinate or abstract what the hardware provides.
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4. Services and access
At the top are the services people or workloads consume, along with the interfaces, provisioning, and service management used to access them. In NIST’s cloud service models, the offerings include Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). These are service models, not three required physical tiers in every data center. Depending on the design, a service may build on another service model or use cloud resources more directly. See NIST’s Cloud Computing Program for the broader cloud context.
Where storage fits—and why its design matters
Storage belongs to the physical IT foundation, but how it is presented and managed can span several layers. Data may be held in storage attached directly to a server, accessed across a network through storage interfaces and protocols, or exposed as a cloud storage service. More abstraction can make storage easier to provision, but it also adds configuration and management complexity.
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Storage decisions are therefore about more than capacity and performance. NIST SP 800-209, Security Guidelines for Storage Infrastructure, identifies security concerns that include:
- Protecting stored data.
- Keeping data and workloads appropriately isolated.
- Ensuring data can be restored when needed.
- Using encryption where appropriate.
Those questions apply whether storage is close to a server, shared over a network, or consumed as a cloud service. The operator’s specific responsibilities depend on the system and service arrangement.
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A hybrid deployment can span the whole stack
A hybrid environment combines local infrastructure with public-cloud services. In NIST NCCoE’s documented hybrid-cloud practice, the design includes server, storage, and networking hardware, virtualization, workload and storage encryption, monitoring and authentication, management components, and cloud services. That example shows how controls and operations can cross layers; it is not a standard recipe or a required vendor bill of materials. NIST NCCoE SP 1800-19 documentation summary
When comparing local and cloud-hosted components, useful questions include who owns and operates the physical facility, how resources are provisioned, how much abstraction and control the user receives, how services are accessed and managed, and who remains responsible for storage protection and recovery.
What can change in an AI-oriented data center?
The same broad layers—facility, physical resources, abstraction and control, and services—remain a useful way to orient yourself. However, design priorities can differ for AI-focused facilities. NIST’s SP 800-239, AI Data Center Security Analysis: A High-Performance Computing (HPC) Driven Approach, is an initial public draft that compares AI data centers with traditional HPC across areas including architecture, hardware, software stacks, workflows, and storage. It does not, on the available publication information, establish detailed design prescriptions for particular equipment or facility systems. NIST SP 800-239
Use the stack as a map, not a fixed blueprint
The model is most useful for tracing dependencies: a service relies on managed resources, those resources rely on physical compute, network, and storage, and that hardware relies on facility systems. It also helps locate questions—such as who provisions a resource or protects stored data—at the layer where they matter. Different architectures can combine, rename, or divide these layers without changing the basic dependency underneath.
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