What are Docker Containers?
Docker containers are a form of "lightweight" virtualization They allow a
process or process group to run in an environment with its own file system,
chroot jails , and also with its own process table, users and
groups and, optionally, virtual network and resource limits. For most purposes,
the processes in a container think they have an entire OS to themselves and do
not have access to anything outside the container (unless explicitly granted).
This lets you precisely control the environment in which your processes run,
allows multiple processes on the same (virtual) machine that have completely
different (even conflicting) requirements, and significantly increases isolation
and container security.
In addition to containers, Docker makes it easy to build and distribute images
that wrap up an application with its complete runtime environment.
For more information, see
What are containers and why do you need them?
What Do Containers Have to Do with DevOps, Anyway?.
Containers vs Virtual Machines (VMs)
The difference between the "lightweight" virtualization of containers and
"heavyweight" virtualization of VMs boils down to that, for the former, the
virtualization happens at the kernel level while for the latter it happens at
the hypervisor level. In other words, all the containers on a machine share the
same kernel, and code in the kernel isolates the containers from each other
whereas each VM acts like separate hardware and has its own kernel.
Containers are much less resource intensive than VMs because they do not need
to be allocated exclusive memory and file system space or have the overhead of
running an entire operating system. This makes it possible to run many more
containers on a machine than you would VMs. Containers start nearly as fast as
regular processes (you don't have to wait for the OS to boot), and parts of the
host's file system can be easily "mounted" into the container's file system
without any additional overhead of network file system protocols.
On the other hand, isolation is less guaranteed. If not careful, you can
oversubscribe a machine by running containers that need more resources than the
machine has available (this can be mitigated by setting appropriate resource
limits on containers). While containers security is an improvement over normal
processes, the shared kernel means the attack surface is greater and there is
more risk of leakage between containers than there is between VMs.
For more information, see Docker containers vs. virtual machines: What's the
difference? and DevOps Best
How Docker Containers Enhance Continuous Delivery Pipelines
There are, broadly, two areas where containers fit into your devops
workflow: for builds, and for deployment. They are often used together,
but do not have to be.
Synchronizing build environments: It can be difficult to keep
build environments synchronized between developers and CI/CD
servers, which can lead to unexpected build failures or changes in
behaviour . Docker images let you specify exactly the build tools,
libraries, and other dependencies (including their versions)
required without needing to install them on individual machines, and
distribute those images easily. This way you can be sure that
everyone is using exactly the same build environment.
Managing changes to build environments: Managing changes to
build environments can also be difficult, since you need to roll
those out to all developers and build servers at the right time.
This can be especially tricky when there are multiple branches of
development some of which may need older or newer environments than
each other. With Docker, you can specify a particular version of the
build image along with the source code, which means a particular
revision of the source code will always build in the right
Isolating build environments: One CI/CD server may have to build
multiple projects, which may have conflicting requirements for build
tools, libraries, and other dependencies. By running each build in
its own ephemeral container created from potentially different
Docker images, you can be certain that these builds environments
will not interfere with each other.
Runtime environment bundled with application : The CD system
builds a complete Docker image which bundles the application's
environment with the application itself and then deploys the whole
image as one "atomic" step. There is no chance for configuration
management scripts to fail at deployment time, and no risk of the
system configuration to be out of sync.
Preventing malicious changes: Container security is improved by
using immutable SHA digests to identify Docker images, which means
there is no way for a malicious actor to inject malware into your
application or its environment.
Easily roll back to a previous version: All it takes to roll
back is to deploy a previous version of the Docker image. There is
no worrying about system configuration changes needing to be
manually rolled back.
Zero downtime rollouts: In conjunction with container
orchestration tools like Kubernetes, it is easily to roll out new
image versions with zero downtime.
High availability and horizontal scaling: Container
orchestration tools like Kubernetes make it easy to distribute the
same image to containers on multiple servers, and add/remove
replicas at will or automatically.
Sharing a server between multiple applications: Multiple
applications, or multiple versions of the same application (e.g. a
dev and qa deployment), can run on the same server even if they have
conflicting dependencies, since their runtime environments are
Isolating applications: When multiple applications are deployed
to a server in containers, they are isolated from one another.
Container security means each has its own file system, processes,
and users there is less risk that they interfere with each other
intentionally. When data does need to be shared between
applications, parts of the host file system can be mounted into
multiple containers, but this is something you have full control
For more information, see:
Implementing Containers into Your DevOps Workflow
Containers can be integrated into your DevOps toolchain incrementally.
Often it makes sense to start with the build environment, and then move
on to the deployment environment. This is a very broad overview of the
steps for a simple approach, without delving into the technical details
very much or covering all the possible variations.
- Docker Engine installed on build servers and/or application servers
- Access to a Docker Registry. This is where Docker images are stored
and pulled. There are numerous services that provide registries, and
it's also easy to run your own.
Containerizing the build environment
Many CI/CD systems now include built-in Docker support or easily enable
it through plugins, but
docker is a command-line application which
can be called from any build script even if your CI/CD system does not
have explicit support.
Determine your build environment requirements and write
Dockerfile based on an existing Docker image, which is the
specification used to build an image for build containers. If you
already use a configuration management tool, you can use it within
the Dockerfile. Always specify precise versions of base images and
installed packages so that image builds are consistent and upgrades
Build the image using
docker build and push it to the Docker
docker push .
Dockerfile for the application that is based on the build
image (specify the exact version of the base build image). This file
builds the application, adds any required runtime dependencies that
aren't in the build image, and tests the application. A multi-stage
Dockerfile can be used if you don't want the application
deployment image to include all the build dependencies.
Modify CI build scripts to build the application image and push it
to the Docker registry. The image should be tagged with the build
number, and possibly additional information such as the name of the
If you are not yet ready to deploy with Docker, you can extract the
build artifacts from the resulting Docker image.
It is best to also integrate building the build image itself into your
devops automation tools.
This can be easier if your CD tool has support for Docker, but that is
by no means necessary. We also recommend deploying to a container
orchestration system such as Kubernetes in most cases.
Half the work has already been done, since the build process creates and
pushes an image containing the application and its environment.
If using Docker directly, now it's a matter of updating deployment
scripts to use
docker run on the application server with the
image and tag that was pushed in the previous section (after
stopping any existing container). Ideally your application accepts
its configuration via environment variables, in which case you use
-e argument to specify those values depending on which
stage is being deployed. If a configuration file are used, write it
to the host file system and then use the
-v argument to mount
it to the correct path in the container.
If using a container orchestration system such as Kubernetes, you
will typically have the deployment script connect to the
orchestration API endpoint to trigger an image update (e.g. using
kubectl set image , a Helm chart, or better yet, a
Once deployed, tools such as Prometheus are well suited to docker
container monitoring and alerting, but this can be plugged into existing
monitoring systems as well.
FP Complete has implemented this kind of DevOps workflow, and
significantly more complex ones, for many clients and would love to
count you among them! See our Devops Services page.
For more information, see How to secure the container
lifecycle and Containerizing
a legacy application: an
Subscribe to our blog via email
Email subscriptions come from our Atom feed and are handled by Blogtrottr. You will only receive notifications of blog posts, and can unsubscribe any time.
Do you like this blog post and need help with DevOps, Rust or functional programming? Contact us.