A simple breakdown of Containers and Virtual Machines, highlighting use cases for both technologies.
The availability of affordable, high-bandwidth internet and increase in computing power have introduced a shift towards virtualization and cloud technologies. Containers and Virtual Machines are essential tools used in modern cloud-based applications and services. When making decisions about virtualization, it’s critical to understand each method’s benefits and differences.
To compare these two technologies, let’s first explore what they are and what they do:
Containers create lightweight, isolated logical namespaces on the underlying operating system, usually within the Linux kernel. Popular Container runtimes commonly used in software engineering are Docker and LXC. Every container has its specific network stack and its own process space, including all of the underlying dependencies required to run the application or service.
The contents of a container are held in a binary file. Containers run independently from the operating system and other containers running on the system. Since they don’t contain the entire operating system, containers are very lightweight. Containers are a small computing unit, allowing a single operating system to run hundreds or even thousands of containers.
These virtualized hardware resources are created and managed by the Hypervisor. Type 1 Hypervisors run directly on the host machine hardware, while Type 2 Hypervisors run on top of the host machine’s operating system. Each Virtual Machine is an image of a complete operating system, so it tends to be a much larger computing unit, usually a couple of gigabytes.
Differences Between Containers and VMs
Now that we are familiar with both technologies, let’s look at some of their differences:
Virtual Machines present a more traditional approach to IT architecture. VMs create a single large computing unit containing the application or service and its resources and dependencies. Containers are examples of cloud IT architecture where a single workload is broken up and distributed into small, easily layered, and scriptable units.
The small units and workloads in containers are far more scalable and agile than large Virtual Machines, making them crucial for cloud-based architecture. Because of their compact size, containers start-up in a matter of seconds or even milliseconds. Virtual Machines, on the other hand, can take up to a couple of minutes to start. This elasticity makes containers more suitable for dynamic applications and highly-scalable workloads helping businesses achieve a faster time to market. Virtual Machines are better suited for more predictable workload environments.
Use Cases and Potential Challenges
Containers and VMs may have their various strengths and weaknesses, but they can both be the right solutions depending on the problem. Virtual Machines are the better choice if an application or a service needs more access to the underlying hardware. You might even have to use a bare-metal dedicated server for direct access to specific hardware, like graphics card features or specific CPU features, without any virtualization.
If you need to run different operating systems and applications on your servers or use remote desktop access to your applications, Virtual Machines are the way to go. Virtualizing an existing monolithic application is easily accomplished using Virtual Machines.
On the other hand, building a cloud application from scratch is much easier using Containers. If you want to run multiple instances of an application or service on your servers, containers are the way to go.
Each Virtual Machine contains an operating system, so increasing the number of Virtual Machines creates a maintenance challenge. Complex applications often end up running a large number of Containers. Multiple containers can run on a single operating system, but running hundreds or thousands of them can be harder to track and manage.
Most large scale container users turn to container orchestration platforms like Kubernetes. Kubernetes is an open-source system for automating deployment, scaling, and management of containerized applications. Most containers today run on the Kubernetes platform.
There is no single solution when choosing between Virtual Machines and Containers in a cloud environment because they address different use cases. Your cloud application architecture and its specific tasks and goals will ultimately determine the most suitable combination of technologies.