Kolo Rahl's Blog

Containers are a win: Using Docker and docker-compose

Published 2018 Sep 20, 18:18

This is the second part in a multi-part series about the path to containerized services. You can read the prologue article to get an overview of what the project this series pertains to was trying to accomplish and a high-level overview of how we got to the finish line.

This article assumes you have at least basic knowledge of Docker and docker-compose.

Docker good, docker-compose better

For small projects where you don’t need a collection of services that speak to each other, Docker is great. It’s all you really need to get a reliable app environment up and running and deployed. But most projects, especially those for for businesses, are not isolated applications that don’t communicate with others.

At some point you will almost definitely need to have at least one service that needs to communicate with another service. Most commonly that would be an application interacting with a database. So at a minimum you now have two containers to run: your main application and your database. You could use docker build and docker run to launch both containers, but then you would need to perform a little extra effort to ensure both containers can speak to each other, especially since the IP address and exposed ports can change depending on your configurations. Thankfully you can bypass the manual effort with docker-compose!

Let’s look at a bare-bones Compose YAML file.

version: "3"
    build: ./
      - "4000"
      - database
    image: database-service
      - "pgdb:/var/run/postgres"

The version tells docker-compose what API version we are using and therefore determines which syntax we are using. Under that is where the magic happens.


The services property holds a list of named services that you want docker-compose to be able to build, run, and manage. In this example we have two services: web for our main application and database for our database. You can think of a service as a container. The Compose YAML is creating a “container definition” that can be used to easily build, rebuild, and run your containerized services.

Build Directives

The web service uses the build property to create the container image. This means that invoking docker-compose build to docker-compose up --build will trigger the full build directive based on the details of the build property. In our example, build: ./ is synonymous to docker build ./. You can use an extended build format to specify the exact details more precisely:

  context: docker/custom/
  dockerfile: Dockerfile.custom

The context property refers to the build context, which is the root folder that the build will be executed from. The dockerfile property allows you to specify custom Dockerfiles for builds. The above extended example is synonymous to docker build -f <dockerfile> <context>.

In contrast, the database service uses the image property. This means that “building” the service is synonymous to docker pull. If the image exists locally, it is used as-is. If the image does not exist locally, it will use docker pull to obtain it. This is useful for services that you don’t change frequently or don’t have control over. You wouldn’t, for example, want to rebuild Postgres frequently because you aren’t modifying the Postgres build, just the data that it stores, and that’s something you handle outside of the build flow (explained in the “Volumes” section below).

Exposing Ports

Easily done through the ports property, just list which ports you want to expose. In the example we have a list of only one port, 4000, but we could expose multiple ports and even specify ranges (e.g. "62700-64200").


In the example, we use depends_on to tell docker-compose that our web service requires database to be running before it can be started. Notice that we use the list format, because we can specify multiple dependencies. For example, if we also were using memcached or Redis, we could create a service for it and add that as another dependency. This is especially common for web applications that use both a database and a caching service.

Note: Although depends_on will determine the order in which services are started, there is no guarantee placed on code execution within the container. For example, the database container could start up and attempt to run postgres, but something stalls and it takes five minutes before the server is actually running and available for incoming connections. In such a case, docker-compose will not wait those five minutes before starting the web container. This is because, according to docker-compose, the container is up and running so we’re good to move on to the next service. When creating a system that requires interactions between external services such as this, retrying for a connection should be the default behavior, but if you application can’t do that then you will need to create a custom startup flow.


Sometimes you want to persist data between builds/runs of your services. This is typically achieved by mounting a volume, which means connecting a local file or folder to a file or folder in your container. This is especially useful for databases, and we can see the use of it with volumes in the example.

The short format is HOST:CONTAINER, so in our example we say that the local pgdb folder should be mounted to /var/run/postgres on the container. Anything in pgdb will be available immediately to the database service and anything changed in /var/run/postgres will be reflected in pgdb.

Personally, I also use this when I’m programming in other environments at home. If I need to program something in Python and I’m on my Windows desktop, I’ll create a small docker-compose file, even if it’s just a single service running an environment with Python installed, and mount a volume. Now I can use editors on my Windows machine (such as Atom or Visual Studio) to create and modify my Python code files and have the changes reflected in a running container so that I can immediately test and iterate on my development. It can also be a simple method for dumping files from your container to your host, e.g. mounting a folder with log data so that you can inspect and manipulate it from your host machine.

Simple Networking

One thing that we did not need to do: expose the database container to the web container. In this example, both containers are automatically connected using their service name. For our web application we can use database:5432, for example, to connect to the database container; docker-compose handles all the messy details with that setup.


Coming up next is Automate All The Things! With Jenkins!. For repeatable tasks you do not want to run them by hand. Not only do such tasks tend to be tedious and time-consuming, but they are also tremendously error-prone. Even when you’re running a simple script, things can go wrong, and so it’s ideal to have a system that can run repeatable tasks based on triggers. Sometimes these triggers are events such as code commits and other times they are simply scheduled to repeat at certain times. Although I’ll be talking about Jenkins specifically, the content should be useful regardless of which tool you end up using.