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Docker Fundamentals | Arvin Bhurtun

Docker Fundamentals

02 Aug 2018

7 minute read

This tutorial will explain the fundamentals of Docker and start you with some basic usage.

What is Docker

Docker is open source software to pack, ship and run any application as a lightweight container. Containers are completely hardware and platform independent so you don’t have to worry about whether what you are creating will run everywhere.

In the past virtual machines have been used to accomplish many if these same goals. However, Docker containers are smaller and have far less overhead than VMs. VMs are not portable as different VM runtime environments are very different. Docker containers are extremely portable. Finally, VMs were not built with software developers in mind; they contain no concept of versioning, and logging/monitoring is very difficult. Docker images, on the other hand, are built from layers that can be version controlled. Docker has logging functionality readily available for use.

You might be wondering what could go into a “container”. Well, anything! You can isolate pieces of your system into separate containers. You could potentially have a container for nginx, a container for MongoDB, and one for Redis. Containers are very easy to setup. Major projects like nginx, MongoDB, and Redis all offer free Docker images for you to use; you can install and run any of these containers with just one shell command. This is much easier than using a virtual machine (even with something like Vagrant).


After you’ve installed Docker, open the terminal and type the following:

docker info

If your installation worked, you will see a bunch of information about your Docker installation. If not, you will need to revisit the install docs.

mkdir docker_demo

Creating Your First Docker Image

Every Docker container is an “instance” of a Docker image. There is a massive library of pre-built Docker images. However, in order to really understand Docker, you should create an image as an exercise.

Let’s create a Docker image for running Redis. Redis is an easy to use in-memory key/value store. It is commonly used as an object cache for many different platforms across many different environments and programming languages.

Remember how I said Docker images are built from layers? Well, every Docker image has to start with a base layer. Common base layers are Ubuntu and CentOS. Let’s use Ubuntu. (In production I would use Debian since it is much smaller.)

The following command will start a Docker container based on the Ubuntu:latest image. :latest is called the image tag and in this case refers to the latest version of Ubuntu. Please ensure you are using a linux container. The container will be started in a powershell terminal. Run the following:

docker pull ubuntu:latest
docker run --name my-redis -it ubuntu:latest bash

-it let’s us interact with our container via the command line. --name just gives us a convenient way to reference our container. You should now be inside your container in a bash terminal seeing something like this:


As you can see, you are logged in as root to the container so no need for sudo. The Ubuntu base image is very bare bones. An important strategy for creating Docker images is keeping them as light as possible. Therefore you have to install a lot of things you normally just have. First, let’s install wget:

apt-get update
apt-get install wget

We need a few other things to build Redis from source and run it:

apt-get install build-essential tcl8.5

Now let’s install Redis:

apt-get install redis-server

This downloads the newest version of Redis, builds it from source, and runs the installer. You will need to answer some configuration questions. Just use all the defaults. Now start Redis by running the following (it might already be started):


You now have Redis started in a Docker container. The next step is saving your image. We want to be able to save the image as it is so we can distribute it and use it elsewhere.

Note: this container is an example, and is missing some things to make it truly usable such as port mapping. We will make a production ready image in the next section.

Exit your container by running:


Note that your container is now stopped since you exited bash. You can easily configure containers to run in the background though.

Run the following command:

docker ps -a

This command shows us all of our docker containers, running or stopped. See the container tagged with my-redis. That’s the one we created! Now let’s commit our container as an image:

docker commit -m "Added Redis" -a "Your Name" my-redis username/my-redis:latest

This command compiles our container’s changes into an image. -m specifies a commit message, and -a let’s us specify an author. username/my-redis:latest is formatted author/name:version. Author refers to your username on Docker Hub. If you don’t want to push your image to the Docker Hub, then this doesn’t matter, and you can use anything you want. If you do, you will need to create an account and use docker push to push the image upstream.

Docker commit creates an image containing the changes we made to the original Ubuntu image. This makes distributing Docker containers super fast since people won’t have to re-download layers (such as Ubuntu:latest) that they already have. In a container, every time you run a command, add a file or directory, create an environmental variable, etc. a new layer is created. Docker commit groups these layers into an image. When distributing Docker images, you should carefully optimize your layers to keep them as small as possible. This tutorial does not cover layer optimization.

You might be thinking that this is somewhat messy since your container is basically a black box. What if you want to redo your image? Would you have to write down the steps to reproduce the entire thing? What if you wanted to recreate your image from CentOS instead of Ubuntu? Your thinking would be correct. Creating Docker images in this way is not the best idea. Instead you should use Dockerfiles.

Your First Dockerfile

A Dockerfile is a set of instructions written as a shell script for creating a Docker image. Let’s create a Dockerfile that generates an image like the one we just created manually but with some important additions.

Download docker_demo and open in vscode

There are some special things in this Dockerfile. FROM tells Docker which image to start from. RUN simply runs a shell command. EXPOSE opens up a port to be publicly accessible. ENTRYPOINT designates the command or application to be run when a container is created.

Now that we’ve written our Dockerfile, let’s build an image from it. Run the following command from within the folder of your Dockerfile:

You can build and run the sample in Docker using the following commands. The instructions assume that you are in the root of the repository.

cd docker_demo
docker build --pull -t dotnetapp .
docker run --rm dotnetapp Hello .NET Core from Docker

The commands above run unit tests as part docker build. You can also run .NET unit tests as part of docker run. The following instructions provide you with the simplest way of doing that.

docker build --target testrunner -t dotnetapp:test .

docker run --rm -it dotnetapp:test

That’s it! Now you have .net core application up-and-running on your machine.This container/image is production ready.


Docker is a powerful tool for creating and running distributable, lightweight applications both locally and in production.

There are many tools and services available to be used in Docker. For example, Dockunit is a tool powered by Docker that lets you test your software across any environment. This tutorial has just scratched the surface of the Docker world.

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