Docker vs. VM (virtual machines): Understanding the Key Differences

Docker vs. VM (virtual machine): What’s the difference between Docker and a VM? What do they have in common, and when should you use which virtualisation technology? Find out in this article.

In the constantly evolving field of IT infrastructure, two revolutionary technologies have gained prominence: Docker and Virtual Machines. These technologies have transformed the deployment, management, and scaling of applications, providing unparalleled flexibility and efficiency. This article will explore the important differences between Docker and VMs, highlighting their benefits, practical applications, and implications for contemporary IT environments.

Docker vs. VM

The graphic illustrates the contrasting architectures of Virtual Machines and Docker containers. On the left, VMs are shown as self-contained entities, each emulating a complete operating system on top of a hypervisor. This provides isolation at the OS level, but also introduces higher resource overhead. On the right, Docker containers are shown as lightweight units that encapsulate applications and dependencies, all sharing the same OS kernel. Docker relies on a container engine to efficiently manage and orchestrate the creation, deployment and execution of containers.

Docker: Lightweight Containerisation

In the world of modern software delivery, Docker has emerged as a revolutionary technology that’s changing the way applications are packaged, shipped and run. Unlike traditional virtual machines, Docker takes a containerisation approach, encapsulating applications and their dependencies into lightweight and isolated units called containers. These containers share the host system’s operating system kernel but operate in isolated user spaces, resulting in efficient resource utilisation and fast boot times. Docker’s agility and consistency have led to its widespread adoption, allowing developers to seamlessly develop and deploy applications across different environments. To illustrate, consider a simple Docker file example for a Python web application:

# Use an official Python runtime as a base image
FROM python:3.10-slim

# Set the working directory in the container
WORKDIR /app

# Copy the current directory contents into the container at /app
COPY . /app

# Install any needed packages specified in requirements.txt
RUN pip install --no-cache-dir -r requirements.txt

# Make port 80 available to the world outside this container
EXPOSE 80

# Define environment variable
ENV NAME World

# Run app.py when the container launches
CMD ["python", "app.py"]

In this example, the Dockerfile instructs Docker to create a container image, starting with the official Python 3.10 image. The application code is copied into the container, dependencies are installed from requirements.txt, port 80 is exposed, an environment variable is set, and finally the app.py script is run on container startup. This demonstrates how Docker simplifies the process of packaging, deploying and running applications and demonstrates its significant advantages over traditional virtual machines.

By the way: With the Docker Init command, you can containerise an application within seconds.

Virtual Machines: Emulated Environments

Unlike Docker containerisation, virtual machines work on a different principle. Virtualisation involves the creation of self-contained instances, or ‘virtual machines’, each running a complete operating system on a hypervisor that’s hosted on the physical hardware. These VMs are isolated entities, effectively segmenting the resources of the host machine. However, this isolation comes at the cost of increased resource consumption, as each VM requires its own operating system and system libraries. As a result, VMs can be slower to start up and may require more memory and storage than Docker containers. This method is ideal for scenarios where strong isolation and compatibility with different operating systems are essential.

Docker vs. virtual machine: Key Differences

• Resource Utilisation: Docker containers share the host OS kernel, which makes them very lightweight and efficient. VMs, on the other hand, are heavier in terms of resource consumption due to the need for emulated OS instances.
• Isolation: Isolation is provided by Docker containers at the process level, with applications isolated from each other while sharing the OS kernel.
• Performance: VMs provide greater isolation by running separate guest OS instances, making them more appropriate for running different operating systems on the same host.In terms of performance, Docker containers have less overhead since they do not require a full OS, resulting in faster start-up times and overall improved performance. VMs, on the other hand, due to their emulation of complete OS environments, tend to have slightly higher overhead.
• Portability: With regards to portability, Docker containers are more portable than VMs as they package only the necessary dependencies, making them easier to move from one system to another. Docker containers are very portable and consistent across different environments, which makes it easy to deploy applications. VMs can be difficult to move between environments due to potential compatibility issues with different hypervisors.
• Scaling: Docker is excellent for scaling applications as it allows for the rapid deployment and scaling of individual services within containers. VMs are better suited to run multiple applications that require different OS environments.

Docker is ideal for microservices architectures, continuous integration and deployment (CI/CD) pipelines, and scenarios where lightweight and fast-scaling containers are crucial.

On the other hand, Virtual Machines are well-suited for scenarios that require strong isolation, compatibility with various OS environments, and the need to run legacy applications.

FAQ

Conclusion: Docker vs. VM

Your specific use case, performance requirements, scalability needs, and existing infrastructure should dictate your choice between the two technologies. Docker provides lightweight containerization for efficient scaling, whereas Virtual Machines offer stronger isolation and compatibility with diverse operating system environments. By comprehending the fundamental distinctions between these technologies, you will become better equipped to make knowledgeable decisions that align with your IT objectives.