What is a Virtual Machine? Types, Benefits, and Use Cases

Virtual machines (VMs) are a core component of IT infrastructure. They are software-based emulations of physical computers that provide logistical and computational flexibility.

In this article, I will explain virtual machines, how they work, their benefits, common use cases, and more!

What is a Virtual Machine (VM)?

A virtual machine is a technology that emulates complete computing systems from the CPU, memory, storage, network interfaces, and OS. 

VMs borrow resources from the physical computer to generate these virtual computers. For instance, if a computer has 8 CPUs and 16 GBs of RAM, we can virtualize an environment with 4 CPUs and 8 GBs of RAM, split from the physical hardware. 

We rely on hypervisors, software that controls the virtualization of hardware resources and manages multiple virtual environments, to manage multiple VMs on a single set of hardware.

Virtual Machines vs. Physical Machines

It is important to understand how a virtual machine may differ from a physical one.

Let’s start by clarifying the difference between hardware and software. Hardware refers to the physical components of a system, such as the motherboard, CPU, memory, GPU, and storage. Software, such as the operating system or other programs, runs on the hardware. 

Physical machines run directly on hardware. On the other hand, VMs run software that creates “virtualized” hardware. As we mentioned before, the base system may be running on 64 GB of RAM, but we can virtualize 32 GB of RAM to share with the virtual machine.

Since VMs can share hardware resources, we can efficiently allocate just the necessary resources a VM needs. For instance, if we have a powerful server, we can run multiple VMs that do many tasks in parallel with just the resources needed for each VM to perform its task. This can improve overall resource utilization and cost. 

The following table compares virtual and physical machines side by side:

Types of Virtual Machines

There are two main kinds of virtual machines: system and process. One emulates an entire operating system, whereas the other emulates a single application: 

System virtual machines

System VMs are what we think of most often when we talk about VMs. They simulate an entire operating system, such as a whole Linux computer. A single piece of hardware can simulate multiple OS instances in this way. This is useful if we need multiple environments to do different things.

Cloud virtual machines are a common example. In them, entire OS environments are hosted and accessed remotely via the Internet, making them ideal for scalable infrastructure.

Process virtual machines

Process VMs are singular processes running on a host operating system. They are not an entire system in themselves but smaller environments that allow any computer to run an application that may not be native to the base operating system. For example, the Java Virtual Machine allows any machine to run Java applications natively.

Process VMs are lightweight compared to system VMs and are widely used for running specific isolated applications, especially in development and debugging scenarios.

Components of a Virtual Machine

Every virtual machine has a few core components. While the exact implementation may differ, they should all include similar parts. Let’s review them in this section.

1. Hypervisor

Generally speaking, a hypervisor is the software layer that manages and initializes virtual machines. It manages the resources between the VM and the physical machine. 

There are two different types of hypervisors:

• Type 1 hypervisors sit on top of bare metal and run off the server itself. They usually have direct access to the server's resources. 
• Type 2 hypervisors are generally installed on a host operating system. They do not have full control of the computer’s resources and are instead managed by the host operating system.

2. Virtual hardware

The hypervisor will allocate virtual hardware to the VM. This means virtually separating the physical resources from the machine and giving them to the virtual environment. That might mean splitting the RAM, CPU cores, and other computing resources so that the VM can run processes.

3. Guest operating system

The guest operating system runs inside the VM. It does not have to be the same operating system as the host and can be any operating system. Different VMs on the same hypervisor or server may even have different operating systems depending on their use cases.

4. Virtual disk

VMs often have virtual disks to store information temporarily while they are running. Sometimes, we transfer data from a virtual disk to the host computer’s actual storage system, but that is done carefully to prevent damage to the host.

Architecture diagram of a server running three virtual machines. Image source: DataCamp.

Virtual Machines vs. Containers

Another popular method of virtualization is containerization. While they may share similar goals, virtual machines, and containers are pretty different in implementation. Let’s see their differences.

• Virtual machines are designed to replicate the entirety of a device, including its hardware. That means a VM will replicate things like a motherboard, CPU, networking device, and so on to ensure that any applications running on the VM appear to be running on independent hardware. 
• Containers, however, are designed to run specific software applications regardless of the environment. They don’t initialize their resources but run on the host computer’s resources.

Architecture diagram of a server running three containers. Image source: DataCamp.

When to use VMs vs. containers

Use VMs when you need to run multiple operating systems in parallel and require discrete resource management. VMs are also preferable when you need a consistent and predictable amount of resources for your processes.

Containers, on the other hand, are ideal for lightweight application deployment. Since containers share resources, it’s important to ensure your server can handle multiple containers at once and allocate resources appropriately.

If you’re new to these concepts, you might find the course on containerization and virtualization concepts helpful for understanding their use cases. For a deeper dive into how VMs and containers differ, check out the blog post comparing containers vs. virtual machines.

Benefits of Virtual Machines

Virtual machines have many benefits, including increased resource efficiency and security. Properly using VMs can make your technology infrastructure simpler and more robust. Let’s take a closer look at their benefits:

Resource efficiency and cost savings

Since VMs share the same hardware, you can get much more utilization out of your physical servers by using VMs. Combining different environments reduces the need to purchase hardware specific to a certain use case and instead allows shared resource usage and overall cost savings.

Isolation and security

Since each VM runs independently from the host system, it is naturally isolated. This increases security by minimizing the risk of a single system crashing or being breached becoming an issue. There is usually no communication between VMs, and they are not reliant on each other, so it is easy to shut down problematic VMs or isolate security concerns quickly.

Flexibility and portability

VMs offer great flexibility for IT infrastructures because they can be easily replicated. This simplifies things when multiple environments need to be launched simultaneously, as they can share the same start-up instructions. This also allows for easy testing, backups, and disaster recovery.

Common Use Cases for Virtual Machines

Let’s discuss some of the more common uses for VMs. They can perform any task that can be done on a normal computer and are invaluable for a variety of operations!

Testing and development environments

Developers often use VMs to create testing and development environments for new software or patches. VMs make it easy to test changes to a program on various ecosystems for thorough testing without impacting the host machine. A single script can be used to deploy the same change across a wide variety of VMs for testing.

Server consolidation

Professionals consolidate multiple physical servers into fewer ones using VMs. This reduces overall hardware maintenance costs and saves some space in server rooms. It also improves resource utilization, as physical machines are no longer tied to a singular environment or task.

Running legacy applications

As technology changes, modern operating systems may no longer be able to support legacy processes. Using a VM can maintain these legacy applications while they are becoming modernized, so operations can continue without issue.

Disaster recovery and backups

With the growing volume of data and information, VMs can serve as quick backups of entire environments to increase robustness within a system. If a single VM crashes on one physical server, other copies of the same VM may continue to run or take over. This is a core component of cloud computing.

Cloud computing

The majority of the cloud runs on virtualization. Cloud platforms like AWS, Azure, and Google Cloud can provide scalable and flexible infrastructure because it is easy to spin up and close virtual machines. They can quickly make virtual copies of entire websites or programs to support growing demand and then spin them down when they are no longer needed.

To learn more about how cloud computing leverages virtualization, check out the course on understanding cloud computing.

Virtual Machines in Data Science

Thanks to their flexibility and utility, VMs are excellent tools for data science! Here are some of their many uses in this area:

Isolated development environments

Like software engineers may use VMs for building unique development environments, data scientists may use VMs to create isolated environments for different data projects. 

For example, you could use one VM to build a predictive model in Python and another to preprocess data with R. This separation allows for multiple computationally intensive projects to run on different environments simultaneously, improving efficiency.

Reproducibility in data science experiments

Data scientists will often need to be able to reproduce results. For instance, when training a deep learning model, you can share a VM with your coworkers that includes the same version of TensorFlow, libraries, and datasets. This ensures consistency in experiments and eliminates the risk of environmental differences affecting outcomes.

Scalability for big data projects

As projects grow, multiple clusters of virtual machines in the cloud may be required. Imagine training a natural language processing model on terabytes of text data; cloud providers like AWS can automatically distribute the workload across multiple VMs. For example, tools like Apache Spark can leverage virtual clusters to handle large-scale computations efficiently.

Popular Virtual Machine Software

There are many tools that allow you to run virtual machines on your computer and in enterprise environments. Here are some of the most popular ones:

VMware

VMware is one of the most popular virtualization tools for enterprise environments. It offers robust support and cloud-based solutions. VMware works with clients to provide tools for desktop and server virtualization, depending on their needs. Their main hypervisor is the VMware ESXi Type 1 hypervisor, which allows for easy server virtualization and comes with an easy-to-use HTML 5 interface.

Microsoft Hyper-V

Microsoft’s Hyper-V is a hypervisor tailored to the Windows Server environment. That means all virtualization requires a Windows OS to run and utilizes disc partitions. It allows for easy virtualization of virtual desktops in the Windows Server environment and is an excellent solution for those wanting to stay in the Windows ecosystem or even Azure.

VirtualBox

VirtualBox is one of the most popular open-source virtualization software. It allows users to create virtual desktops of any kind on their own computers. It offers a straightforward interface and can utilize disc images for easy reproducibility. This is a great introductory tool to the world of virtualization and highly recommended for practice and experience.

KVM (Kernel-based virtual machine)

The Linux kernel allows you to create machines called KVMs. Every modern Linux system comes with KVM and allows users to convert any Linux-based piece of hardware into a hypervisor. It leverages the existing hardware and is often managed using virtualization software such as Red Hat.

Conclusion

Virtual machines are an integral part of the IT ecosystem by allowing you to create multiple virtual environments from a single server quickly. They are often managed by hypervisor software, which creates and allocates resources as necessary.  This allows for greater resource utilization, reproducibility, resiliency, and efficiency, especially when multiple processes need to run in parallel.

To explore these concepts and understand how VMs compare with technologies like containers, check out the course on containerization and virtualization concepts. It’s a great way to deepen your understanding of these essential technologies!