To this point we’ve discussed server virtualization, but many other IT infrastructure elements can be virtualized to deliver significant advantages to IT managers (in particular) and the enterprise as a whole. In this section, we'll cover the following types of virtualization:

Desktop virtualization lets you run multiple desktop operating systems, each in its own VM on the same computer.

There are two types of desktop virtualization:

For more information on virtual desktops, see “Desktop-as-a-Service (DaaS).”

Network virtualization uses software to create a “view” of the network that an administrator can use to manage the network from a single console. It abstracts hardware elements and functions (e.g., connections, switches, routers, etc.) and abstracts them into software running on a hypervisor. The network administrator can modify and control these elements without touching the underlying physical components, which dramatically simplifies network management.

Types of network virtualization include software-defined networking (SDN), which virtualizes hardware that controls network traffic routing (called the “control plane”), and network function virtualization (NFV), which virtualizes one or more hardware appliances that provide a specific network function (e.g., a firewall, load balancer, or traffic analyzer), making those appliances easier to configure, provision, and manage.

Storage virtualization enables all the storage devices on the network— whether they’re installed on individual servers or standalone storage units—to be accessed and managed as a single storage device. Specifically, storage virtualization masses all blocks of storage into a single shared pool from which they can be assigned to any VM on the network as needed. Storage virtualization makes it easier to provision storage for VMs and makes maximum use of all available storage on the network.

For a closer look at storage virtualization, check out "What is Cloud Storage?"

Modern enterprises store data from multiple applications, using multiple file formats, in multiple locations, ranging from the cloud to on-premise hardware and software systems. Data virtualization lets any application access all of that data—irrespective of source, format, or location.

Data virtualization tools create a software layer between the applications accessing the data and the systems storing it. The layer translates an application’s data request or query as needed and returns results that can span multiple systems. Data virtualization can help break down data silos when other types of integration aren’t feasible, desirable, or affordable.

Application virtualization runs application software without installing it directly on the user’s OS. This differs from complete desktop virtualization (mentioned above) because only the application runs in a virtual environment—the OS on the end user’s device runs as usual. There are three types of application virtualization: 

Data center virtualization abstracts most of a data center’s hardware into software, effectively enabling an administrator to divide a single physical data center into multiple virtual data centers for different clients.

Each client can access its own infrastructure as a service (IaaS), which would run on the same underlying physical hardware. Virtual data centers offer an easy on-ramp into cloud-based computing, letting a company quickly set up a complete data center environment without purchasing infrastructure hardware.

CPU (central processing unit) virtualization is the fundamental technology that makes hypervisors, virtual machines, and operating systems possible. It allows a single CPU to be divided into multiple virtual CPUs for use by multiple VMs.

At first, CPU virtualization was entirely software-defined, but many of today’s processors include extended instruction sets that support CPU virtualization, which improves VM performance.

A GPU (graphical processing unit) is a special multi-core processor that improves overall computing performance by taking over heavy-duty graphic or mathematical processing. GPU virtualization lets multiple VMs use all or some of a single GPU’s processing power for faster video, artificial intelligence (AI), and other graphic- or math-intensive applications.

Linux includes its own hypervisor, called the kernel-based virtual machine (KVM), which supports Intel and AMD’s virtualization processor extensions so you can create x86-based VMs from within a Linux host OS.

As an open source OS, Linux is highly customizable. You can create VMs running versions of Linux tailored for specific workloads or security-hardened versions for more sensitive applications.

As noted above, the cloud computing model depends on virtualization. By virtualizing servers, storage, and other physical data center resources, cloud computing providers can offer a range of services to customers, including the following: 

If you’d like to learn more about these cloud service models, see our guide: “IaaS vs. PaaS vs. SaaS.”