Virtual Machines vs Containers

Virtual machines (VM) and containers are similar in concept, but very different in their implementation and use. Conceptually, both allow the running of multiple services on a single platform. Both are quicker and less expensive to deploy than physical servers. And, horizontal scaling is easier since there is no need to spin up and configure new physical infrastructure. That’s where the similarities end.

Virtual Machine Implementation Overview

Virtual machines are akin to software implementations of physical servers, thus virtualizing hardware servers. Many virtual machine instances can run on one physical machine. This is accomplished by a hypervisor.

A hypervisor application creates and maintains the virtual machines. Each VM is allocated CPU, memory, and storage. Each VM also has its own operating system, the Guest OS. VMs with different operating systems can run side by side. Applications that run on a virtual machine don’t see a difference between a VM and a physical server.

Here is a logical view of a virtual machine implementation:

Container Implementation Overview

Containers are run in native OS processes that share the same kernel. These containerized applications package all the required components together, which allows them to be deployed quickly in different environments. My recent Containers blog post goes into more detail on what these are.

Here is a logical view of containers on a server:

Notice that the container instances all share the underlying Host OS.

Here is a quick comparison of containers and virtual machines:

	Containers	Virtual Machines
Startup Time	Seconds	Minutes
OS	Shares OS	Has its own OS
Virtualization	OS-Level	Hardware
Memory	Less is required	More is required
Cost	Less	More

Let’s examine the above comparison traits.

Startup Time is much quicker with containers, mostly due to the virtual machine having its own operating system.

The OS is virtualized for containers. Virtual machines have their own allocated OS and virtualize their underlying hardware. Thus, VMs can run on a server that has different Guest OS types.

Virtualization for a container is a type of operating-system-level virtualization. This is because a program running inside a container does not have access to the underlying operating system. It only has access to what has been allocated to the container. VM is considered hardware virtualization since, looking in from the outside, a VM appears to be a physical server with it’s own CPU, memory and disk.

The memory footprint is smaller for containers. This means a physical server can run more containers than virtual machines.

Cost would normally be less when using containers. One reason is that a container does not require its own Guest OS, and thus, many more containers can run on a host server than on VMs. 

In the end, there are good reasons to use containers and VMs. Both can be supported on-premise or through a cloud-hosting option, such as Amazon, Google, Microsoft, IBM, and others. Both have their uses and related costs. And architects can help inform the appropriate choice.

Containing Your Container Excitement

Containers are becoming mainstream as companies aim to cut costs and increase performance. And, with increased use of PaaS (Platform as a Service) offered by vendors such as Microsoft, Amazon and Google, organizations take advantage of built-in support for containers.

So, what are containers?

Containers are a method of operating system virtualization that provides the ability to run an application in resource-isolated processes. Containers can help package an application’s code, configurations, and dependencies into easy-to-use building blocks that deliver environmental consistency, operational efficiency, developer productivity, and version control.

Why use them?

• Containers help ensure that applications deploy quickly, reliably, and consistently regardless of deployment environment.
• Containers provide more granular control over resources, and thus improve infrastructure efficiency.

How do they work?

A container engine must be running on a server. This engine manages the containers, and sits on top of the host server OS. It starts and stops the container instances running on the host server. Here is a logical view:

The container engine manages the container instances (eg, the starts and stops).

Container images are read-only template files that describe what the container’s running application will look and act like along with the dependencies such as required libraries and binaries. The container engine uses these image files to create the container instance.

The container instance is the running implementation of the container image. It can be any number of things, such as:

• Application
• Service
• Database

Pros to using Containers

• Allows easier movement of an application across environments
• Runs within a process, thus allowing more instances of an application
• Starts up and scales quickly

Cons to using Containers

• Security can be a concern, as containers share the OS and kernel
• Networking access within containers can be more complex

Now what?

Migrating to containers is not for everyone nor for every scenario. Some legacy applications are not easily migrated, and it might makes sense to only move new applications to containers.

Docker and Google Kubernetes are currently two popular container management products. And, if you don’t want to do an on-premise install of the container engine and associated applications, excellent cloud-based container options are available with Microsoft Azure and Amazon AWS.

I’ve only scratched the surface on what containers are. Many tutorials are available; and as with many technologies, you can experiment on your own by either downloading container software or getting a free account on Azure or AWS.

In my next blog post, I’ll describe the differences between containers and virtual machines — it can get confusing since there are similarities.