Virtualization is the process of creating a virtual version of a physical IT resource, like a server or a desktop.
Virtual machines (VM) behave like real physical systems, with their own operating systems and applications. However, they share the same underlying hardware with the physical guest device and other VMs.
Virtualization allows organizations to run more workloads with fewer devices, reducing the space, cost, and resource utilization required. Modern businesses run heavily virtualized systems for the same reason.
- Higher resource efficiency: Most physical servers barely utilize their full hardware capacity. Virtualization allows teams to run multiple workloads from the same device, maximizing value from the existing hardware.
- Faster deployment: New VMs can be deployed (or spun up) instantly.
- Better resilience: VMs can be migrated, replicated, or restored during outages.
- Easier management: Administrators can create, manage, and decommission servers centrally rather than maintaining individual machines.
The history of virtualization
Virtualization has evolved from a niche efficiency technique into a foundational technology that powers modern IT infrastructure, cloud computing, and scalable digital services. The evolution of virtualization can be understood as five technology stages, each solving a major infrastructure limitation.
- 1960s to 1980s: IBM built experimental systems to partition expensive computer resources. These technologies were later commercialized and popularized.
- 1990s: The standard Intel x86 chips lacked virtualization support. VMware solved this in 1998 and released desktop virtualization. They also released VMware ESX server in 2001 as an enterprise virtualization technology.
- 2000s to 2010s: Virtualization was expanded with the launch of new open source technologies (Xen and KVM), commercial vendors (Microsoft Hyper-V), hardware extensions (Intel VT-x and AMD-V).
- 2010s to present: Containerization becomes popular with the launch of Docker and Kubernetes, and cloud-based software as a service (SaaS) becomes popular with hyperscalers like Google Cloud, Amazon Web Services, and Microsoft Azure.
Modern organizations rely on hybrid architectures allow workloads to move across on-premises and cloud environments.
Virtualization terms explained
Host device
The physical server hardware that provides CPU, RAM, storage, and network interfaces across multiple VMs.
Virtual machine (VM)
VMs are software-defined devices hosting applications. Each VM runs its own guest operating system (OS) that interacts with the hypervisor.
Hypervisor
A hypervisor fills the gap between a device's hardware and the guest OS. It is usually a software, hardware, or firmware system that sits between the OS and the hardware. It allocates system resources like CPU, memory, and disk space from the physical server to the virtualized devices.
Hypervisors are also known as virtual machine monitors (VMMs). Based on the way they are deployed, hypervisors can be classified into two:
- Type 1: These are known as native or bare metal hypervisors. They are deployed directly on top of the server hardware.
- Type 2: They are known as hosted hypervisors. They are deployed as software applications running on top of a host-device OS.
| Aspect | Type 1 Hypervisor (Bare-Metal) | Type 2 Hypervisor (Hosted) |
|---|---|---|
| Installation | Installed directly on physical hardware | Installed on top of an existing OS |
| Performance | Higher (direct hardware access) | Slightly lower (depends on host OS) |
| Use Case | Enterprise production environments | Testing, development, labs |
| Security | Stronger isolation | Dependent on host OS security |
Types of virtualization
Full virtualization
In this type of virtualization, the hypervisor takes the host resources, partitions them, and presents it to the VMs. The VMs are isolated from the host hardware. They are unmodified and unaware of their status as virtual devices. Hypervisors use a technology known as binary translation to allocate resources between the VMs and the host hardware. This is more secure and portable and can be implemented on any OS. But as binary translation is used, it is slower.
Para virtualization
The VMs are not completely isolated from the host server. The VMs take care of resource allocation themselves. The VMs are modified and aware of themselves. They communicate with both the hypervisor and the host system. Para virtualization is faster but less portable. Moreover, as the guest OSs are modified, the number of OSs on which this can be implemented is limited.
Hardware-assisted virtualization
This approach combines the speed of para virtualization with the flexibility of full virtualization with hardware extensions. Instead of using binary translation, extensions like Intel VT-x or AMD-V intercepts communications between the VMs and the hardware. This allows a greater range of unmodified OSs to run at near native hardware speed.
OS virtualization
The OS acts as a hypervisor and creates virtual spaces within the system that are independent of each other. The OS partitions the system resources into isolated instances. These isolated virtual spaces are also called containers. They are faster to boot, however, they share the same host kernel. A kernel-level exploit could compromise the entire cluster. Moreover, you cannot run different OSs like Windows and Linux within the same host.
Kernel-level virtualization
The OS's own kernel is converted into a bare-metal hypervisor. They are generally implemented on Linux kernel modules like KVM (Kernel-based virtual machine).
Virtualized vs non-virtualized systems
| Technology | Guest OS Status | Performance | Portability & Compatibility | Key Risks or Limitations |
|---|---|---|---|---|
| Non-Virtualized | Direct hardware access; unmodified OS | Highest raw performance (zero virtualization overhead) | N/A (tied directly to specific physical hardware) | Poor resource utilization efficiency |
| Full Virtualization | Unmodified and unaware of virtualization | Slower (due to binary translation overhead) | High security and high portability; can run on any OS | Performance overhead from binary translation |
| Para-Virtualization | Modified and aware of virtualization | Faster than full virtualization | Less portable; limited choice of guest OSs due to required modifications | Requires modifying the guest operating system kernel |
| Hardware-Assisted Virtualization | Unmodified and unaware of virtualization | Near-native hardware speed | High flexibility and wide range of supported OS | Requires specific hardware/CPU extensions to function |
| OS Virtualization (Containers) | Isolated container instances sharing the host kernel | Fast to boot and lightweight | Limited; cannot run different OS families (e.g., Windows and Linux) on the same host | A kernel exploit can compromise the entire cluster. |
| Kernel-Level Virtualization | Integrated directly into the host kernel layer | High performance (bare-metal level) | Tied closely to the host kernel architecture | Restricted to environments supporting the specific kernel modules |
Virtualization improves hardware utilization, scalability, and flexibility by running multiple VMs on a single physical server using a hypervisor. Traditional infrastructure assigns one application per server, resulting in lower efficiency, higher costs, and slower provisioning.
Virtualization technologies
Virtualization technologies are implemented across IT infrastructure layers. They are classified based on the virtualized component. Each type improves efficiency, scalability, and manageability at its respective layer.
1. Server virtualization
Server virtualization is the process of dividing one physical server into multiple isolated VMs. It allows organizations to maximize hardware utilization by running multiple workloads simultaneously instead of dedicating one server per application. This significantly reduces infrastructure costs and energy consumption.
It forms the foundation of modern data centers by enabling rapid provisioning, workload mobility, and high availability without requiring additional physical hardware.
2. Desktop virtualization
Desktop virtualization separates a user’s desktop environment from their physical device. It enables secure access to corporate desktops from any location or device, supporting remote work strategies and reducing dependency on physical office infrastructure.
Centralized desktop management allows IT teams to apply updates, enforce policies, and maintain compliance across thousands of endpoints from a single console.
3. Storage virtualization
Storage virtualization combines multiple physical storage systems into a unified logical pool. Storage pools and LUNs work on the basis of this. A storage area network (SAN) is a dedicated network that connects storage devices. A SAN is not connected to a LAN but has its own set of SAN switches to connect storage arrays.
A redundant array of independent disks (RAID) is a storage virtualization technology where disks are combined to form a virtual storage unit. Multiple levels of RAIDs are available with varying levels of speed, capacity, fault tolerance, and reliability.
Centralized storage control simplifies backup, replication, and disaster recovery processes while allowing seamless expansion without downtime.
4. Network virtualization
Network virtualization creates software-defined networks independent of physical hardware. Administrators can configure routing, segmentation, and security policies programmatically, reducing manual configuration and deployment time.Software defined networking and virtual LANs are applications of this.
It enables advanced architectures such as micro-segmentation and automated traffic optimization, improving performance, and strengthening security.
5. Application virtualization
Application virtualization isolates software from the underlying operating system. Applications run in self-contained environments, preventing compatibility conflicts and eliminating the need for traditional installation on individual machines.
Updates and patches can be deployed centrally, ensuring users always access the latest version without disrupting workflows.
6. Unified computing systems
A unified computing system (UCS) is a converged data center architecture that combines server virtualization, with network fabrics and storage networks. A UCS usually has a powered chassis with a cooling unit and slots to connect blade servers and rack servers. Virtual hosts can be connected to the server slots and interconnected with a virtualized network. A UCS can be connected to a SAN to provide virtualized storage capabilities.
7. Hyper-converged infrastructure (HCI)
HCI virtualizes networking, servers, and storage systems into a set of underlying physical devices. Administrators can manage compute, routing, and storage from a single environment. Unlike UCS, HCI is a software-defined framework. Modern HCI platforms like Nutanix can be hosted in Cisco UCS hardware.
Challenges of virtualization
Virtualization challenges include performance overhead, resource contention, management complexity, security risks, licensing considerations, and VM sprawl. These are operational challenges that can be mitigated with proper planning and monitoring.
- Performance overhead : The hypervisor layer consumes a portion of system resources. This can affect performance.
- Resource contention : Multiple VMs share the same hardware resources, so simultaneous demand spikes can lead to slowdowns.
- Security risks : Virtualization introduces additional layers such as hypervisors and management consoles that can be exposed to vulnerabilities.
- Licensing and cost planning : Some enterprise platforms use licensing models tied to CPU cores or advanced features, which can increase costs without capacity planning.
- VM Sprawl : Because VMs spun up easily. Forgotten instances often accumulate and consume storage and compute capacity.
Learn more about how to manage the challenges in virtualization.
Applications of virtualization
Virtualization is used across enterprise IT to optimize infrastructure, support cloud platforms, enable remote work, accelerate development, improve disaster recovery, and modernize legacy systems. Virtualization technologies are implemented in several use cases.
1. Server consolidation
A company running 50 physical servers for separate apps can reduce them to 5 high-capacity hosts using virtualization. This improves resource utilization while simplifying infrastructure management and monitoring.
2. Development & testing labs
Engineering teams create temporary virtual environments to test software, simulate failures, or validate updates. These environments can be deployed instantly and deleted after use. This accelerates release cycles and minimizes infrastructure waste.
3. Disaster recovery systems
Enterprises replicate VMs to backup locations so workloads can be restored quickly after outages or cyber incidents. Recovery time drops from hours or days to minutes, helping organizations meet uptime SLAs and avoid revenue loss.
4. Secure sandboxing
Security teams run suspicious files or applications inside isolated VMs to analyze their behavior. Even if malwares execute, they remains contained within the virtual environment.
5. Containerization
Containerization builds on virtualization concepts but operates at the operating-system level rather than emulating full hardware. VMs virtualize hardware to run multiple OS environments, whereas containers share a single kernel while isolating applications.
Platforms like Docker and orchestration systems such as Kubernetes rely on virtualization infrastructure underneath to scale efficiently across hosts.
6. Cloud computing
Virtualization is the foundational technology enabling cloud computing. Cloud providers use virtualization to divide physical servers into isolated environments.This abstraction makes it possible to deliver on-demand compute, storage, and networking resources without requiring dedicated hardware for each user.
7. Workspace virtualization
Workspace virtualization separates a user’s desktop and applications from the physical device, delivering them as a managed service. Users can access their desktops from any location, device, or platform.
8. VM migration
VM migration enables running workloads to move between hosts, storage systems, or data centers without downtime. This ensures continuous availability, automated load balancing, and improved disaster recovery resilience.
Virtualization vendors
The virtualization ecosystem includes enterprise-grade hypervisors, cloud-integrated platforms, open-source alternatives, and monitoring solutions that ensure operational visibility.
| Type of vendor | Examples | Pros |
|---|---|---|
| Enterprise / Proprietary Virtualization | • VMware (Broadcom) • Microsoft Hyper-V • Oracle VM VirtualBox (Enterprise) • IBM PowerVM | • High performance, reliability, and mature feature sets (live migration, advanced clustering, high availability). • Robust enterprise support and extensive ecosystem integration. • Excellent security and compliance management tools. |
| Hyper-converged Infrastructure (HCI) | • Nutanix (AHV) • Scale Computing • Dell VxRail • Cisco HyperFlex | • Combines compute, storage, and networking into a single unified system. • Highly scalable with simplified deployment and management. • Reduced footprint and streamlined lifecycle management. |
| Open Source & Community-Driven | • KVM (Kernel-based Virtual Machine) • Proxmox VE • Xen Project • Apache CloudStack | • No expensive licensing fees (free to use and modify). • High transparency, flexibility, and avoidance of vendor lock-in. • Active global communities and rapid feature innovation. |
| Cloud-Native & Container-Adjacent Virtualization | • Red Hat OpenShift Virtualization (KubeVirt) • Amazon EC2 / AWS Nitro • Google Cloud Platform (KVM-based) • Azure Virtual Machines | • Bridges traditional VMs and modern container/Kubernetes workflows. • Unified management for microservices and monolithic applications. • Highly elastic with seamless integration into modern CI/CD pipelines. |
| Desktop & Client-Side Virtualization | • VMware Workstation / Fusion • Parallels Desktop • Oracle VM VirtualBox (Desktop) | • Allows running multiple operating systems locally on a single workstation. • Ideal for software testing, development, and legacy application support. • User-friendly setup on desktop operating systems (macOS, Windows, Linux). |
Virtualization monitoring
Unlike physical devices, VMs are logical units without physical distinction. Without monitoring, resource contention, performance degradation, and capacity bottlenecks remain hidden. Virtualization monitoring tools provide insights into VM performance, resource utilization, and network impact. As virtualization environments grow more complex, visibility across virtual technologies is essential.
ManageEngine OpManager is network monitoring software that is specialized for monitoring virtualized environments. OpManager discovers virtual environments, collects performance metrics, analyzes them, and presents them to you in graphs and reports on a single, powerful console.
Explore OpManager's virtualization monitoring capabilities.
| Server virtualization | Network virtualization | Storage virtualization |
|---|---|---|
| Host hardware health | Hardware health | Storage hardware health |
| CPU, memory, and disk utilization | CPU, memory, and disk utilization | Storage capacity |
| In, out, and overall traffic | In, out, and overall traffic | Input/output operations per second (IOPS) |
| Processes and services | Packet loss, jitter, and mean opinion score | Volume utilization |
| Virtual events (VM migration, host relocation, etc.) | Availability and response time | Storage pool utilization |
| CPU ready, CPU wait, active memory, etc. | VPN, VLAN, SDN, and SD-WAN metrics. | Logical unit number monitors |
| Read more about VM monitoring | Read more about network monitoring | Read more about storage monitoring |
Frequently asked questions
How many virtual machines can run on a single physical server?
There is no fixed number. It depends on host CPU cores, memory, storage speed, and what the workloads actually do. A host running light web services might support 30 or more VMs comfortably. The same hardware running database workloads might struggle past 10. Memory usually becomes the limiting factor before CPU does. Rather than targeting a VM count, plan around sustained resource utilization and leave headroom for failover, so that when one host goes down the rest can absorb its workloads.
What is CPU ready time, and why does it matter?
What is resource overcommitment, and is it safe?
What does live migration need in order to work?
How do I choose between VMs and containers?
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