Virtual Machines vs. Containers: How They Differ and When to Use Each

Updated June 30, 2026

Virtual machines (VMs) and containers are both virtual environments that use software instead of a physical machine to isolate applications into a self-contained unit. But VMs and containers are built and run differently, which affects their capabilities and the costs of using them. Understanding the key differences between these technologies can help organizations choose the right architecture for their applications and infrastructure.

Servers

To understand VMs, let’s start with a basic understanding of servers. They’re called servers because they serve up applications, information, or other services to other computers. VMs are actually virtual servers in that they serve up an application to other computers. VMs are deployed on a physical computer or server, called the host. You could run a VM on your personal computer, but companies, which run dozens or hundreds of VMs, typically house their VMs on a physical server.

Before hosting company applications in the cloud, companies housed them on physical servers, which were stored in racks in a company’s data center. In contrast to commercial applications like Word and Excel, company applications are created by companies to allow employees and customers to do things like download documents or order items or services. Each individual company application would sit on an individual physical server. Each time IT planned to create a new application, the team would have to decide how big of a server to buy to host the application. Deciding on the size of the server to purchase was always a conundrum as IT could never be sure how much computer resources—computation (CPU), memory, and storage—would be needed to host a new application. If IT ordered a server that had far more resources than was needed to host a particular application, IT could get scolded for spending too much money without cause. IT could almost always buy a server that fit the application’s needs for the first few months. But if the application turned out to be more popular than expected, in time the server’s resources would not be enough to handle the traffic, which would hinder the application’s performance. Hence, IT could get scolded for not thinking ahead and planning for growth in traffic.

When an application on a physical server lacks needed resources to handle increased traffic, the application slows down or, worse, crashes. If you’ve ever tried to complete a form on a website and sat there waiting for the app to let you proceed from one question to the next, you know how frustrating it is to interact with an app that lacks resources to work well. But those problems became rare when companies began using VMs because more resources could easily be allocated to handle nearly any amount of traffic.

Virtual Machines

A virtual machine is a software-based computer that functions like a physical computer. Although you can’t physically touch a virtual machine, it contains everything needed to run applications, including an operating system, storage, memory allocation, networking components, and virtual hardware. 

To understand a virtual machine, consider a Word document. A Word document contains text, images, and formatting instructions. Similarly, a virtual machine contains application code, configuration settings, operating system files, and supporting resources. Both are digital assets that can be copied, stored, and moved between systems. Organizations use virtualization platforms such as VMware vSphere, VMware Workstation, Microsoft Hyper-V, KVM (Kernel-based Virtual Machine), Oracle VirtualBox, and Proxmox to create and manage virtual machines. 

At a high level, a virtual machine follows this architecture: 
Physical Hardware → Host Operating System (or Bare Metal) → Hypervisor → Guest Operating System → Applications 

This layered design allows multiple VMs to run on the same host machine while remaining isolated from one another. Because each VM contains its own guest OS, it can run a different operating system than the host machine. For example, one VM may run Windows Server while another runs Linux. This ability to support multiple operating systems is one of the biggest advantages of virtualization. 

Creating a VM

Using a physical computer and software, a user can create a VM. The VM can reside on a physical computer, but VMs take up a lot of resources, so users at organizations typically use their computer to create a VM but save it on a VM server, which is a physical server. These days, VM servers are just referred to as servers, but they’re called VM servers because they were purpose-built to house virtual machines. VM servers can host dozens of VMs and can be located in a company’s data center, in a data center the company rents, or in a data center belonging to a cloud service provider like Amazon Web Services (AWS) or Microsoft Azure.

Just as you can create many instances of the exact same Word document and can save them in different folders on your computer, on other computers, on storage devices, or in the cloud like in Dropbox, you can also create different instances of a VM containing an application that can be stored on various computers, servers, storage devices, and in the cloud. The benefit of having different instances of a VM is that if one gets too much traffic at any point, you can spin up another instance of the VM quickly to handle the extra traffic. And if one VM breaks, another VM can come on line automatically and take over seamlessly, so users are totally unaware of the troubles behind the scenes.

VM Architecture: Hypervisors, Host OS, and Guest OS 

A computer or server that hosts a VM is known as the host machine, while the virtual machines running on it are known as guest systems. Between the physical hardware and the guest operating systems sits a layer of software called the hypervisor. The hypervisor creates, manages, and allocates resources to virtual machines. It determines how CPU, memory, storage, and networking resources are distributed among multiple VMs. Hypervisors generally fall into two categories: •

• Type 1 hypervisors run directly on hardware and include VMware ESXi, Microsoft Hyper-V Server, and KVM. 
• Type 2 hypervisors run on top of an existing operating system and include VMware Workstation and Oracle VirtualBox. 

Because every virtual machine includes a complete guest operating system, VMs consume more resources than containers. Each VM requires its own OS files, drivers, services, and system processes, regardless of whether the application uses them. 

This architecture creates a strong security boundary. If one guest operating system becomes compromised, it generally cannot access the memory space or kernel of neighboring virtual machines. This isolation makes VMs a popular choice for regulated environments and workloads requiring strong separation. 

The tradeoff is overhead. Running multiple VMs requires significantly more memory, storage, and CPU resources than running containers. 

Running Monolithic Applications on Virtual Machines

Traditional applications were often built using a monolithic architecture. Rather than separating functionality into independent services, all application components were tightly coupled into a single codebase. [Keep existing monolithic application explanation and Figure 2.] If one service within a monolithic application fails, the failure can affect other services and potentially bring down the entire application. 

Virtual machines remain an excellent deployment option for monolithic applications because they provide a complete operating system environment with predictable resource allocation and strong isolation. 

Lift-and-Shift Cloud Migrations

One reason virtual machines continue to play a major role in cloud computing is their support for lift-and-shift migrations. Instead of rewriting an application as a containerized application, organizations can move an existing virtual machine from an on-premises environment into Microsoft Azure, AWS, or another cloud platform with minimal code changes. 

This approach works particularly well for legacy business applications, commercial software packages, databases, and workloads that depend on a specific operating system configuration. 

Modern Applications

Companies today typically build monolithic apps only for small applications. For example, if a company wanted to create an application for employees to update their contact information and add two people to contact in case of an emergency, that would be a small application, so it would make sense to create that using a monolithic architecture in a VM. But if an ecommerce were creating an application to sell its goods, that might include a variety of services. For example, when you go to the websites of the largest retailers, the catalog of goods alone consists of thousands of items. The shopping cart service alone may consist of suggestions for other items, discount codes, and loyalty points. Other parts of the application might include gift guides, subscriptions, deals of the day, gift cards, ordering, order history and much more. If all that were in a monolithic application, were one thing to go wrong, it could cause problems with other parts of the application. 

Instead of creating large applications all in one block of code where components are tightly coupled, companies are creating cloud native applications that use a microservice architecture, which breaks down large application structures into smaller, independent services that are not dependent upon a specific coding language. So instead of building one monolithic application with 100 services, using the programming language they are most comfortable coding in, developers create each one of those individual services as its own independent application. These small independent applications are typically created in containers or in a cloud provider’s serverless platform, such as AWS Lambda. These tiny applications could also be created in VMs, but because they consume so many resources, that would be tantamount to one person driving an 18-wheeler 300 miles to deliver one tiny package. 

Resources

A computer or server that hosts a VM is known as the host, while the VMs that reside on it are known as guests. There is a layer of software in between the host OS and the VM called the hypervisor, which creates and runs VMs on a server (See fig. 1).  The hypervisor allows one host to support multiple guest VMs by sharing the server’s resources—memory, processing and storage.

A system administrator allocates a portion of the server’s resources, depending on the application’s need, to each VM running on it. Resources consist of things like device drivers for a graphics card, sound card, network adapter, hard drives, keyboard and mouse, as well as the memory, storage, and CPU—which controls all the functions of the computer, so it can listen to instructions from your devices and software and execute those functions.

In addition to using a portion of the server’s operating system (OS), each VM has its own operating system (OS), which could be any brand—Mac, Linux, Windows, Ubuntu, or something else. The VM’s own OS can be entirely different from that of the server. As long as the VM has the necessary system components for an application, VMs can run any OS you want. The OS includes the various drivers like audio cards, which probably will never be used. All those resources—two operating systems—make VMs a heavyweight solution. Those heavy resources are not only redundant but there are associated costs: licensing fees for using the operating systems, money to run all those resources, and staff time waiting for all those resources to start up. If you don’t like waiting for your computer or mobile phone to start up, you can imagine what it’s like for a developer or systems administrator to sit and wait for their VMs to start.

VMs are typically thought of as being secure because each VM is separated from one another and does not communicate with any other VM. So if one gets attacked, it likely won’t affect the others. However, policies still must be put in place because services running on a VM’s OS could be used to inject malicious code into the host system. But you can use security features on your host and guest systems to help prevent that.

VMs and Applications

Traditional applications, often referred to as monolithic applications, were all written in one large chunk of code, all self-contained in one block, yet separated into different categories. Each category in a monolithic app is still closely tied to other categories and other services within any category (See fig. 2).

Containers

Containers are packages of software that include all the necessary elements to run an application in any environment whether that’s on software or hardware on-premises or in the cloud. Created just to do one single service, or function, and do it well, a container only comprises the application, the required binaries, libraries, and images: a file that includes executable code so it can run an isolated process. This small footprint allows you to host far more containers than VMs on a server.

In contrast to a VM, which includes its own OS, containers don’t have their own OS. That OS makes VMs heavy and causes their start-up time to be slow, often up to four minutes, whereas containers start up in milliseconds. But because VMs have their own OS, it doesn’t matter what OS the server is using. Containers, on the other hand, must be built to run on the OS of the server that will be hosting the container. So if a container is going to be run on Linux, it must be built to be compatible with Linux.

You can group many containers together in clusters to deploy a larger application. The clusters can be managed by container orchestrators like Kubernetes, allowing you to manage one cluster in one fell swoop.

Instead of running on top of a hypervisor as VMs do, containers run on a container engine, such as Docker or Oracle Cloud Infrastructure Compute, which runs the container (see fig. 3). On the host’s system, containers share a kernel—a piece of code in the OS that schedules programs to run. The container engine exposes parts of the host operating system into a partitioned area where the containers are, making them quick to start-up.

Whereas VMs are all isolated from one another on a server, containers share the memory of the host OS and that can be a security concern. To mitigate risk, network policies should be implemented and compliance requirements should be considered before production begins.

Reasons to Use VMs

• You can quickly create new iterations of VMs, so if one VM goes down, another one can either be created manually or automatically if the proper systems are in place for that.
• Recovery. You can quickly restore a VM from a snapshot. With frequent iterations of snapshots of the VM, you can reduce downtime.
• Economical. You can buy one server and host numerous VMs, and you can use VMs in a public cloud.
• Storage and backup. A VM backup consists of backing up an entire machine rather than just individual files.
• Application development. You can deploy new VMs quickly to develop new apps.
• Secure environment. If a VM gets tainted with malware, it’s separated from your other systems.
• Sandboxed environment. Executing code in a sandbox prevents any potential security issues from actually impacting the business servers.
• Safe testing environment. Before deploying an application on a main company server, you can test it and perfect it in a VM.   
• You can run multiple operating systems. One VM be running MacOS while another VM on the same server could be running Windows, and another may be running Linux.
• Portability. If they’re running on the same type of hypervisor, you can move VMs across virtual environments and from one physical server to another, including from your data center to another data center. As long as the application works in your environment, it should be able to work anywhere you move it.
• Compatibility. You can run a VM image on any OS host, such as Linux, Mac or Widows.

VM Tradeoffs: Slower Starts, Bigger Footprint, Higher Cost

Virtual machines provide flexibility and isolation, but they come with tradeoffs. Because every VM includes a full operating system, startup times are slower than containers. A typical Linux VM may take 30 seconds to two minutes to cold boot, while containers often start in milliseconds. 

 Virtual machines also consume more storage and memory. Depending on workload requirements, a host may support 10 to 30 virtual machines, while the same hardware could support hundreds or even thousands of containers. Licensing costs can also increase. Organizations running Windows Server environments may need to account for operating system licensing, Client Access Licenses (CALs), and other per-VM costs. 

The Rise of MicroVMs 

New technologies such as Firecracker and Kata Containers attempt to bridge the gap between traditional virtual machines and containers. These microVM platforms provide VM-level isolation while offering startup times and efficiency closer to containers. 

When to Pick Containers

Containers are often the preferred choice for modern cloud-native applications. Organizations commonly choose containers when they need:

• Rapid deployment
• Faster scaling
• Efficient resource utilization
• CI/CD automation
• Portability across different environments
• Support for multiple programming languages 

Because containers are lightweight, developers can quickly create, test, and deploy applications without managing multiple operating systems. Containerized applications also fit naturally into modern DevOps workflows. Infrastructure as Code (IaC), CI/CD pipelines, and container platforms allow teams to move software from development to production more quickly and consistently. 

Organizations that want hands-on experience with Docker, Kubernetes, and Red Hat OpenShift can benefit from structured training that covers real-world deployment scenarios and container management best practices. 

Challenges With Containers

• Container orchestrator needed. You’ll need an orchestrator like Kubernetes, Amazon Elastic Container Service, or Red Hat OpenShift to manage all those containers.
• Complexity. If a service fails, it could be difficult to detect where the problem lies as there could be hundreds of containers for one overarching application. Distributed tracing tools will be needed to identify problems.  
• Persistent storage. Container data typically disappears forever once the instance shuts down, so you’ll need an external storage component that’s compatible with your orchestrator.  

Running Containers on Virtual Machines 

In modern enterprise environments, virtual machines and containers frequently work together rather than compete. Many Kubernetes clusters run on virtual machines hosted in VMware environments, Microsoft Azure, AWS, or other cloud platforms. In this model:

• Virtual machines provide infrastructure isolation.
• Containers provide application portability and scalability.
• Kubernetes manages multiple containers across multiple VMs. 

Do Containers Replace Virtual Machines? No. Containers and virtual machines solve different problems. Virtual machines remain ideal for legacy applications, operating system isolation, and lift-and-shift migrations. Containers excel at cloud-native application development, microservices, and rapid scaling. For many organizations, the most effective strategy is using both technologies together. Interested in Virtual Machines? Browse Our Course Catalog  

Summary

VMs are a great way to move legacy and traditional applications to the cloud and to host small application. Containers work great for creating large applications, adopting a cloud native architecture and allowing developers to develop in the programming language of their choice.