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Getting Started with Docker Part 1: Running Containers

Containers and container architecture are fast-growing subjects in development and infrastructure today. Docker seems to be the canonical implementation of container technology, though it is not the only one. I have recently been getting increasingly interested in containers and their uses. This post is part 1 in a series that serves as a brief introduction to containers and a primer on getting up and running with Docker. We will cover the following topics in this post:

  • Overview of containers and Docker
  • Installing Docker
  • Running a container

Feel free to open your command prompt and favorite text editor before we get going. The last section walks you through some hands-on activities. These exercises assume some familiarity in working with command line tools and some basic knowledge of Linux system administration. You can get by without much of either.

Overview of Containers and Docker

First, what problems are containers attempting to solve? One of the primary objectives of containers is to normalize the environment that applications run in. The feared "it works on my machine" bug is a product of some of the challenges of having environmental differences between development, testing, and production. Containers provide one avenue to smooth out those differences.

If you have ever worked with a tool like Vagrant, you have seen a similar solution in action. The difference is that Vagrant is oriented around standing up a complete virtual machine (VM) whereas container solutions stand up much smaller virtualized systems in a host environment. You can see in these diagrams from Docker that VMs have a few more layers than containers, including the hypervisor and guest operating system. Most issues with performance in VMs stem from the heft of these two layers. You can see from the following diagrams that replacing the hypervisor and guest OS with Docker Engine results in a leaner tech stack.

   

Figure 1. Differences between virtual machines and containers, source: What is Docker?

The biggest benefit to the difference in virtualization strategy between VMs and containers is that containers are lighter, faster, and leaner than VMs. Containers share the host kernel rather than running separate kernels on top of the hypervisor.

When you install Docker on your machine, you install the Docker Engine virtualization layer along with the Docker command-line client. This CLI is what you typically work with when developing with Docker. The client communicates with the host Docker program via an HTTP API, so the included Docker CLI is just one possible client of Docker Engine.

Figure 2. Docker client-server components, source: Docker docs

Installing Docker

The installation process for Docker varies depending on your target platform, but to install it on your local development machine you can typically use Docker for Windows or Docker for Mac. Instructions for Linux depend on your distribution.

Note: Both installation methods above have specific operating system requirements, so check the Docker documentation before proceeding. Also, note that if you use VirtualBox for other day-to-day work, you may want to check out the legacy installation method for Windows and Mac: Docker Toolbox. Docker Toolbox differs from Docker for Mac and Docker for Windows in that it sets up a Linux host in a VirtualBox VM and installs Docker Engine there. The native installers use newer virtualization technologies that allow Docker Engine to run a little "closer to the metal" and can be more performant.

The installation instructions on the Docker website typically also include a step to run a hello-world container. Go ahead and try this to verify that everything works. When you can successfully run the hello-world container, proceed with the rest of the guide below where we get to work with different components of Docker.

Running a Container

At this point, you should have been able to run at least one Docker container after installing Docker on your machine. The hello-world container is very simple, but it demonstrates one function Docker can perform: running a one-off program. Here is what happens when you execute docker run hello-world from the command line:

  1. The Docker CLI tells Docker Engine on the host that you want to spin up a container from an image called "hello-world".
  2. Docker Engine on the host looks for an image by that name in its local cache, and failing to find one, it reaches out to known Docker registries to look for it. The default registry is Docker Hub.
  3. Finding the image on Docker Hub, Docker Engine downloads a copy, and executes it in the host environment.
  4. Output from the container is streamed to the local command line.
  5. The main process inside the container terminates, signaling Docker Engine to stop the container.

Figure 3. Docker client-server components, source: Docker docs

Long-Running Containers

The hello-world container stops immediately because it does not host a long-running process. Many containers kick off a process that is meant to stay running. For example, databases and web servers are common long-running processes because they need to keep listening for new connections or requests. In the following examples, we will work with nginx, a lightweight web server. The nginx Docker image starts the program in such a way that it does not terminate immediately. In this case, Docker Engine leaves the container up and streams logs to our console. We can try this by running docker run --rm -p 8080:80 nginx from our command line.

This time, when we ran a container, we provided two additional options to the docker run command: --rm and -p 8080:80. The --rm option tells Docker Engine to remove the container when it stops. This is not a required option flag, of course, but it is a good habit to get into in order to keep our Docker environment clean. Containers are meant to be thrown away. The -p 8080:80 option tells Docker Engine to map port 8080 on the engine to port 80 on the container. This allows us to view the nginx page in the browser. By default, Docker Engine does not do any port mapping regardless of what ports containers declare that they expose. We should see the following output from the command:

Unable to find image 'nginx:latest' locally
latest: Pulling from library/nginx
Digest: sha256:f2d384a6ca8ada733df555be3edc427f2e5f285ebf468aae940843de8cf74645
Status: Downloaded newer image for nginx:latest

The container should have started, so let’s open our browser and navigate to http://localhost:8080 (or your Docker host IP in the case of Docker Toolbox. You can retrieve Docker’s IP address by inspecting the DOCKER_HOST environment variable in the Quickstart Terminal). We should see the nginx welcome page. If we check back in our console, we should see a log entry for the HTTP request we just made:

192.168.99.1 - - [07/Feb/2017:16:01:08 +0000] "GET / HTTP/1.1" 304 0 "-" "Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/56.0.2924.76 Safari/537.36 OPR/43.0.2442.686 (Edition beta)" "-"

Now we type Ctrl+C or Cmd+C to stop following the logs of the container. Note that the container is still running. Execute docker ps to view a list of active containers:

CONTAINER ID        IMAGE               COMMAND                  CREATED             STATUS              PORTS                           NAMES

80a02fcbb904        nginx               "nginx -g 'daemon ..."   6 minutes ago       Up 6 minutes        443/tcp, 0.0.0.0:8080->80/tcp   vigilant_lamarr

Here we can see several key properties of the container including the image it is from, exposed and mapped ports, as well as a name that Docker assigned to the image. We can customize the name by adding an option flag like --name my_nginx_container to our docker run command. Now let’s stop our container by running docker stop vigilant_lamarr. Make sure to use the container name that we retrieved from the console output of docker ps. If we run docker ps again, we should see an empty table.

Images like nginx that execute a long-running process are meant to be run with the -d option flag. This starts the container just like before, except Docker returns us to the command prompt immediately without streaming the logs. We can still access the logs from a container by running docker logs vigilant_lamarr (again, remember to use your container name).

Interactive Containers

Some images are meant to be run as interactive containers with the flags -i and -t. For instance, what if we want to work on a base Ubuntu image from the command line to try out a couple of utilities? We could launch an Ubuntu container straight into bash with the command docker run --rm --name ubuntu_test -it ubuntu bash. When Docker finishes downloading the image, it reads the last argument we provided and starts that program for you in the container. In this case, we will be launched into a bash terminal with root privileges inside the container.

Note: On Windows, you may need an alternative terminal to successfully run an interactive container. Try using Cmder with the full installation. You may need to manually set Docker environment variables for your Docker CLI to work properly. You can use the docker-machine env command to print out the variables and values you need to set.

We can go ahead and try out a few commands (ex. whoami, ls, apt), and when we are done, we can run the command exit. Now we are back in our local command line. We can run docker ps to check the status of the container we just ran. The container should not actually be listed here. Remember how we executed docker run with the --rm? When we ran exit from inside the container, the bash session ended, signaling Docker to stop the container, and the --rm option informed Docker to also remove the container once it stopped.

Next Steps

Now that we have Docker installed and are familiar with running a few types of containers, we can take the next step by building images and learning about container orchestration. The next post in this series covers both of these topics. In the meantime, try substituting a Docker container for one of your applications dependencies like a shared cache, messaging service, or database. If you look into databases, make sure to read up on managing data in Docker volumes to persist your database between container instances.



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About The Author

Senior Consultant

Marc is a Senior App Dev Consultant in Cardinal’s Raleigh office. He has experience with enterprise Java solutions and a variety of front-end web technologies. These days, Marc is most interested in fine-tuning his craft as a Javascript developer.