Docker and virtual machines (VMs) are powerful cloud computing technologies that help companies optimize their compute resources through virtualization, or the process of creating a virtual representation of something. In this case, the thing being virtualized is a computer.
The key difference is that VMs virtualize the computer hardware, while Docker virtualizes only the operating system. Another way to put it is that Docker allows multiple workloads to run on a single OS instance, while VMs allow the running of multiple OS instances. Since they’re complementary technologies, Docker is commonly used with VMs to optimize cloud-computing resources and performance (particularly in Kubernetes-based deployments; more on that later).
To better understand the difference between Docker and VM technology, how they’re used, and why they’re beneficial to companies, let’s first define our terms.
What Is Docker and What Are Containers?
Docker is an open source platform for building and running applications inside of containers. Containers are standardized units of software containing all the code and dependencies—including binaries, libraries, and configuration files—needed for an app to run.
Although container technology has been around for a long time, Docker’s debut in 2013 made containerization mainstream. Today, however, Docker is no longer the only or dominant container runtime in use. Most modern containerized environments now rely on Open Container Initiative (OCI)-compliant runtimes such as containerd (an industry-standard runtime originally extracted from Docker), runC, and CRI-O, which offer better Kubernetes integration and more lightweight, modular architectures.
Originally developed for Linux, containers have become an industry standard for application and software development. They solve the issue of environment inconsistency, allowing developers to write code locally (say, on their laptop) and then deploy it anywhere, in any environment, without having to worry about the bugs and other issues caused by environmental differences such as versions, permissions, and database access.
Containers today are typically deployed in Kubernetes-managed environments that support not only developer flexibility but also large-scale orchestration, networking, and persistent storage needs.
What Is a Virtual Machine?
A VM is a computing resource that uses software, instead of a physical computer, to run programs and deploy apps. Through VMs, one or more virtual “guest” machines can run on a physical “host” machine. For example, a virtual MacOS machine can run on a physical PC. However, a hypervisor is needed to virtually share the resources of the host machine.
What Is a Hypervisor?
A hypervisor, also known as a virtual machine monitor (VMM), is software that creates and runs virtual machines. A hypervisor enables a single host computer to support multiple guest VMs by virtually sharing resources such as memory and processing. Hypervisors can run several virtual machines on one physical machine’s resources, which allows for more efficient use of physical servers. IT teams can shift workloads and allocate networking, memory, storage, and processing resources across multiple servers as needed.
Figure 1: Docker architecture vs. VM architecture
Source: Docker
Docker vs. VM: Advantages and Disadvantages
By encapsulating software into virtual self-contained units, a Docker container allows you to run an app in a virtual environment without the heavy resource requirements of a hypervisor. With a container, instead of having to virtualize an entire OS and server, you only need to virtualize the software and hardware dependencies required for a particular app to run while using the OS kernel of the host machine. For this reason, Docker containers are far less taxing on your physical servers than VMs. Containers can also launch and scale in a matter of seconds because they don’t need their own full operating system.
That said, VMs offer certain advantages over Docker. Since they’re truly independent of the host machine, VMs are very isolated and secure. They also offer robust management tools and can make all OS resources available to all apps. And since they can run different operating systems on one physical machine, they offer cost savings as well by not requiring the use of multiple physical servers.
Modern approaches such as Firecracker (developed by AWS) and Kata Containers are now emerging as lightweight VM alternatives that offer a middle ground between container speed and VM-level isolation.
Similarly, technologies like virtual kubelet allow integration of virtualized environments into Kubernetes clusters for seamless scaling across hybrid infrastructure.
Docker vs. VM Use Cases
Both Docker and VMs make running multiple applications in production easier. The difference is that where VMs help you optimize your infrastructure resources by maximizing the number of machines you can get out of your hardware and software, Docker containers help you maximize your development resources by enabling things like microservices and DevOps best practices.
Since many cloud providers depend on VM technology to provide users with their personal servers, running Docker containers in the cloud usually means running them on top of VMs that have been provisioned for you. Hence, it’s not so much a question of Docker or VMs but of Docker and VMs or just VMs alone.
Since most cloud-native applications now run on Kubernetes, it’s common to see containers orchestrated via Kubernetes clusters running atop VM-based infrastructure. This model combines the flexibility of containers with the operational control of VMs.
The goal should be to reduce computing costs by using container technology to improve deployment density and make applications more lightweight and portable so you can run multiple applications on a single VM rather than having to use multiple VMs.
You can also consider container-optimized operating systems such as Google’s Container-Optimized OS or AWS Bottlerocket for running secure, minimal-footprint workloads.
You should use Docker containers with VMs to:
- Maximize the number of apps running on a single OS kernel
- Deploy multiple instances of a single app
- Prioritize compute and storage resources
You should use VMs alone for:
- Prioritizing isolation and security
- Running multiple apps with different OS dependencies on a single server
- Running an app that needs all the resources and functionalities of an OS
- Handling legacy workloads that aren’t container-friendly
In short, if you have monolithic applications that you don’t need to refactor into microservices, using VMs alone should work. However, Docker containers (with VMs) are better for developing and deploying newer, cloud-native applications on a microservices architecture.
Get the Most Out of Container Orchestration with Portworx
Docker containers work best when used in conjunction with container orchestration tools.
Portworx® by Pure Storage is Pure’s industry-leading Kubernetes data services platform designed for container-native storage, disaster recovery, backup, and automated capacity management. It offers greater flexibility, performance, and availability than traditional orchestration tools and is optimized for modern Kubernetes environments.
Portworx integrates natively with Kubernetes and supports:
- Dynamic provisioning of persistent storage
- Cross-cloud and hybrid cloud elasticity
- Zero-downtime migration and disaster recovery
- Automated backup and recovery workflows
- Policy-driven data placement and tiering
Granular multi-tenant storage management for large enterprise clusters
Container data security is also a top priority. With Portworx, enterprises gain access to built-in encryption, role-based access control (RBAC), and secure CSI (Container Storage Interface) integration—key features for maintaining supply chain security and compliance in modern DevSecOps workflows.
Learn more about how Portworx can future-proof your containerized application environments.
