A virtual machine (VM), also called a virtual instance, is a software-based version of a physical computer. Instead of running directly on hardware, a VM operates inside a program that emulates a complete computer system, including a processor, memory, storage, and network connections. This allows multiple VMs to run on a single physical machine, each with its own operating system and applications, as if they were independent computers.
VMS are useful because they provide flexibility, isolation, and scalability. Since each VM is self-contained, it can run different operating systems (like Windows, Linux, or macOS) on the same hardware without affecting other VMs or the host machine. This makes them ideal for testing software, running legacy applications, or efficiently using server resources in data centers. Because VMs exist as software, they can be easily copied, moved, or backed up, making them a powerful tool for both individuals and businesses.
Read on to learn about types of VMs, their benefits, common use cases, and how to choose the right VM provider for your needs.
How do VMs work?
A virtual machine (VM) runs inside a program called a hypervisor, which acts as an intermediary between the VM and the actual computer hardware. Every time a VM needs to perform an action—such as running software, accessing storage, or using the processor—the hypervisor intercepts these requests and decides how to allocate resources like CPU power, memory, and disk space. You can think of a hypervisor as an operating system for VMs, managing multiple virtual machines on a single physical computer. Popular hypervisors like VirtualBox and VMware enable users to run multiple operating systems simultaneously while providing strong isolation.
Modern hypervisors optimize performance by giving VMs direct access to certain hardware components when possible, reducing the need for constant intervention. However, some level of overhead remains because the hypervisor still needs to manage and coordinate resources efficiently. This means that while VMs can leverage most of the system’s hardware, they can’t use 100% of it, as some processing power is always reserved for managing virtualization itself. This small trade-off is often worth it, as hypervisors keep each VM isolated and secure, preventing one VM from interfering with another.
VM layers
Figure 1 illustrates the layers of a system virtual machine setup. The layer model can vary depending on the hypervisor. Some hypervisors include a built-in host operating system, while modern hardware offers native virtualization support. Many hypervisors can also manage multiple physical machines and VMs efficiently.VM snapshots are an essential feature in cloud computing, allowing users to quickly restore a virtual machine to a previous state.
Hypervisors that emulate hardware architectures different from what the guest OS expects have a bigger overhead, as they can’t relay commands directly to the hardware without first translating them.
VM snapshots
VM snapshots are an essential feature in cloud computing, allowing users to quickly restore a virtual machine to a previous state. The hypervisor can save the complete state of the VM and restore it at a later time to skip the boot process of the guest OS. The hypervisor can also move these snapshots between different physical machines, making the software running in the VM completely independent from the underlying hardware.
What are the benefits of using VMs?
Virtual machines offer benefits including resource efficiency, isolation, simplified operations, easy migration, faster deployment, cost savings, and security. Let’s look at these one by one.
Multiple VMs can run on a single physical machine, making sharing resources between various guest operating systems easier. This is especially important when each guest OS needs to be isolated from the others, such as when they belong to different customers of a cloud service provider. Sharing resources through VMs makes running a server cheaper because you don’t have to buy or rent a whole physical machine, but only parts of it.
Since VMs abstract the underlying hardware, they also improve resilience. If the physical machine fails, the hypervisor can perform a quick recovery by moving the snapshots to another machine without changing the guest OS installations to minimize downtime. This abstraction also allows operations teams to focus their deployment efforts on a standardized VM instead of considering different physical implementations.
Migrations become easier with snapshots as you can simply move them to a faster machine without modifying the software running inside the VM.
Faster deployments are possible because starting a VM is just a software execution instead of setting up a physical server in a data center. While you had to buy a server or rent it for months, with fast deployments, you can now rent a machine for hours, minutes, or even seconds, which allows for quite some savings.
Modern CPUs have built-in virtualization features that enable easy resource sharing and enforce the isolation at the hardware layer. This prevents the services of one VM from accessing the resources of the others, improving security compared to running multiple apps inside one OS.
Common use cases for VMs
VMs have a range of use cases. Let’s look at the most popular ones.
Cloud computing
The most popular use case is cloud computing, where VMs allow the secure sharing of the cloud provider’s resources, enabling their customers to rent only the resources they need for the period their workload will run.
Software development and testing
Software development often requires specific tools and libraries that aren’t available on a production machine, so having a development VM with all these tools preinstalled can be helpful. An example is cloud IDEs, which look and feel like regular IDEs but run on a cloud VM. A developer can have one for each project with the required dev tools installed.
VMs also allow a developer to set up a machine for software testing that looks exactly like the production environment. Here, the opposite of the development VM is required; it should not have any development tools installed because they would also be missing from production.
Cross-platform development
A special case of the software development use case is cross-platform development. When you implement an app for Android or iOS, for example, you usually don’t do this on a mobile device but on your computer. With VMs, developers can simulate different hardware environments, enabling cross-platform testing without requiring physical devices.
Legacy system support
If the hardware your application requires is no longer in production, a VM might be the only way to keep running your software without reimplementing it. This is similar to the cross-platform development use case, as the VM emulates different hardware, but the difference is that the hardware no longer exists.
How to choose the right VM provider
To find the right provider for your workload, the most important factor to assess is your own workload requirements. Ask the following questions and compare the answers to what providers offer.
Is your workload compute or I/O-bound?
Many workloads, like web servers, are I/O-bound. They don’t make complex calculations but rather simply load data and send it over the network. If you need a VM for an I/O-bound workload, you care more about disk and memory size, as well as network speed.
However, compute-heavy workloads, such as AI inference or Kubernetes clusters, require careful resource allocation. If you’re evaluating whether to run Kubernetes on bare metal or VMs, check out our white paper on Bare Metal vs. VM-based Kubernetes Clusters for an in-depth comparison.
If your workload is compute-bound instead, you need a high-performance CPU or a GPU and loads of memory. An AI inference engine, for example, only sends a bit of text to a client, but it does many calculations to generate this text.
How long will your workload run?
Web servers usually run indefinitely, but some workloads only run a few hours or minutes. If you’re doing AI training, you don’t want to pay for your huge VM cluster 24/7 if it only runs a few hours or days a week. In such cases, looking for a provider that allows renting your desired VM type hourly on a pay-as-you-go model might be worthwhile.
Certain cloud providers offer cost-effective spot instances, which provide lower prices for non-critical workloads that can tolerate interruptions. These cheap VMs can get shut down at any time with minimal notice, but if your calculations aren’t time-critical, you might save quite a bit of money here.
How does your workload scale?
Scaling in the cloud is usually done horizontally. That is, by adding more VMs and distributing the work between them. Workloads can have different requirements for when and how fast they must be added and removed.
In the AI training example, you might know in advance that one training takes more resources than the other, so you can provision enough VMs when starting. However, a web server workload might change its requirements constantly. Hence, you need a load balancer that automatically scales the instances up and down depending on the number of clients that want to access your service.
Do you handle sensitive data?
You might have to comply with specific laws and regulations depending on your jurisdiction(s) and industry. This means you must check whether the cloud provider also complies. How secure are their data centers? Where are they located? Do they support encryption in transit, at rest, and in process?
What are your reliability requirements?
Reliability is a question of costs and, again, of compliance. You might get into financial or regulatory troubles if your workload can’t run. Cloud providers often boast about their guaranteed uptimes, but remember that 99% uptime a year still means over three days of potential downtime. Check your needs and then seek a provider that can meet them reliably.
Do you need customer support?
If your organization doesn’t have the know-how for operating VMs in the cloud, you might need technical support from the provider. Most cloud providers are self-service, offering you a GUI and an API to manage resources. If your business lacks the resources to operate VMs, seek out a provider that can manage VMs on your behalf.
Summary
VMs are a core technology for cloud computing and software development alike. They enable efficient resource sharing, improve security with hardware-enforced guest isolation, and simplify migration and disaster recovery. Choosing the right VM provider starts with understanding your workload requirements, from resource allocation to security and scalability.
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