Developer Basics: Docker

Modified 2020-05-26 by Andrea F. Daniele

Docker is used to perform operating-system-level virtualization, something often referred to as “containerization”. While Docker is not the only software that does this, it is by far the most popular one.

Containerization refers to an operating system paradigm in which the kernel allows the existence of multiple isolated user space instances called containers. These containers may look like real computers from the point of view of programs running in them.

A computer program running on an ordinary operating system can see all resources available to the system, e.g. network devices, CPU, RAM; However, programs running inside of a container can only see the container’s resources. Resources assigned to the container become thus available to all processes that live inside that container.

Modified 2020-05-26 by Andrea F. Daniele

Containers are often compared to virtual machines (VMs). The main difference is that VMs require a host operating system (OS) with a hypervisor and a number of guest OSs, each with their own libraries and application code. This can result in a significant overhead.

Imagine running a simple Ubuntu server in a VM on Ubuntu: you will have most of the kernel libraries and binaries twice and a lot of the processes will be duplicated on the host and on the guest OS. Containerization, on the other hand, leverages the existing kernel and OS and adds only the additional binaries, libraries and code necessary to run a given application. See the illustration bellow.

Because containers don’t need a separate OS to run they are much more lightweight than VMs. This makes them perfect to use in cases where one needs to deploy a lot of independent services on the same hardware or to deploy on not-especially powerful platforms, such as Raspberry Pi - the platform the Duckietown community uses.

Containers allow for reuse of resources and code, but are also very easy to work with in the context of version control. If one uses a VM, they would need to get into the VM and update all the code they are using there. With a Docker container, the same process is as easy as pulling the container image again.

Modified 2020-05-26 by Andrea F. Daniele

You can think that Docker containers are build from Docker images which in turn are build up of Docker layers. So what are these?

Docker images are build-time artifacts while Docker containers are run-time constructs. That means that a Docker image is static, like a .zip or .iso file. A container is like a running VM instance: it starts from a static image but as you use it, files and configurations might change.

Docker images are build up from layers. The initial layer is the base layer, typically an official stripped-down version of an OS. For example, a lot of the Docker images we run in Duckietown have ubuntu:18.04 as a base.

Each layer on top of the base layer constitutes a change to the layers below. The Docker internal mechanisms translate this sequence of changes to a file system that the container can then use. If one makes a small change to a file, then typically only a single layer will be changed and when Docker attempts to pull the new version, it will need to download and store only the changed layer, saving space, time and bandwidth.

In the Docker world, images get organized by their repository name, image name and tags. As with Git and GitHub, Docker images are stored in image registers. The most popular Docker register is called DockerHub and it is what we use in Duckietown.

An image stored on DockerHub has a name of the form:

[repository/]image[:tag]

The parts repository and tag are optional and they default to library (indicating Docker official images) and latest (special tag always pointing to the latest version of an image). For example, the Duckietown Docker image

duckietown/dt-core:daffy-arm32v7

has the repository name duckietown, the image name dt-core, and the tag daffy-arm32v7, which carries both the name of the Duckietown software distribution that the image contains, i.e., daffy, and the CPU architecture that this image is targeting, i.e., arm32v7. We will talk about different CPU architectures and why they need to be part of the Docker image tag in the section Section 4.4 - Different CPU architectures.

All Duckietown-related images are in the duckietown repository. Though images can be very different from each other and for various applications.

Modified 2020-05-26 by Andrea F. Daniele

Since Docker images contain binaries, they are not portable across different CPU architectures. In particular, binaries are executable files that are compiled to the level of CPU instructions. Different CPU architectures present different instructions sets.

Many modern computers use the amd64 architecture, used by almost all modern Intel and AMD processors. This means that it is very likely that you can find a Docker image online and run it on your computer without having to worry about CPU architectures.

In Duckietown, we use low-end computers like the Raspberry Pi (officially used on any Duckietown device) and Nvidia Jetson. These low-cost computers employ Arm processors that are based on the arm32v7 instructions set.

Modified 2020-05-26 by Andrea F. Daniele

If you want to get a new image from a Docker registry (e.g. DockerHub), you have to pull it. For example, you can get an Ubuntu image by running the command:

laptop $ docker pull ubuntu

According to Section 4.3 - How does Docker work?, this will pull the image with full name library/ubuntu:latest which, as of May 2020, corresponds to Ubuntu 20.04.

You will now be able to see the new image pulled by running:

laptop $ docker image list

If you don’t need it anymore or you are running out of storage space, you can remove an image with,

laptop $ docker image rm ubuntu

You can also remove images by their IMAGE ID as printed by the list command above. A shortcut for docker image rm is docker rmi.

Sometimes you might have a lot of images you are not using anymore. You can easily remove them all with:

laptop $ docker image prune

This will remove all images that are not supporting any container. In fact, you cannot remove images that are being used by one or more containers. To do so, you will have to remove those containers first.

If you want to look into the heart and soul of your images, you can use the commands docker image history and docker image inspect to get a detailed view.

Modified 2020-05-26 by Andrea F. Daniele

Containers are the run-time equivalent of images. When you want to start a container, Docker picks up the image you specify, creates a file system from its layers, attaches all devices and directories you want, “boots” it up, sets up the environment up and starts a pre-determined process in this container. All that magic happens with you running a single command: docker run. You don’t even need to have pulled the image beforehand, if Docker can’t find it locally, it will look for it on DockerHub.

Here’s a simple example:

laptop $ docker run ubuntu

This will take the ubuntu image with latest tag and will start a container from it.

The above won’t do much. In fact, the container will immediately exit as it has nothing to execute. When the main process of a container exits, the container exits as well. By default the ubuntu image runs bash and as you don’t pass any commands to it, it exits immediately. This is no fun, though.

Let’s try to keep this container alive for some time by using the -it flags. This tells Docker to create an interactive session.

laptop $ docker run -it ubuntu

Now you should see something like:

root@73335ebd3355:/#

Keep in mind that the part after @ will be different — that is your container ID.

In this manual, we will use the following icon to show that the command should be run in the container:

container $ command to be run inside the container

You are now in your new ubuntu container! Try to play around, you can try to use some basic bash commands like ls, cd, cat to make sure that you are not in your host machine.

You can check which containers you are running using the docker ps command — analogous to the ps command. Open a new terminal window (don’t close the other one yet) and type:

laptop $ docker ps

An alternative (more explicit) syntax is

laptop $ docker container list

These commands list all running containers.

Now you can go back to your ubuntu container and type exit. This will bring you back to you host shell and will stop the container. If you again run the docker ps command you will see nothing running. So does this mean that this container and all changes you might have made in it are gone? Not at all, docker ps and docker container list only list the currently running containers.

You can see all containers, including the stopped ones with:

laptop $ docker container list -a

Here -a stands for all. You will see you have two ubuntu containers here. There are two containers because every time you use docker run, a new container is created. Note that their names seem strangely random. We could have added custom, more descriptive names—more on this later.

We don’t really need these containers, so let’s get rid of them:

laptop $ docker container rm container name 1 container name 2

You need to put your container names after rm. Using the containr IDs instead is also possible. Note that if the container you are trying to remove is still running you will be asked to stop it first.

You might need to do some other operations with containers. For example, sometimes you want to start or stop an existing container. You can simply do that with:

laptop $ docker container start container name
laptop $ docker container stop container name
laptop $ docker container restart container name

Imagine you are running a container in the background. The main process is running but you have no shell attached. How can you interact with the container? You can open a terminal in the container with:

laptop $ docker attach container name

Modified 2020-05-26 by Andrea F. Daniele

Often we will ask you to run containers with more sophisticated options than what we saw before. Look at the following example: (don’t try to run this, it will not do much).

laptop $ docker -H hostname.local run -dit --privileged --name joystick --network=host -v /data:/data duckietown/rpi-duckiebot-joystick-demo:master18

Table 4.1 shows a summary of the options we use most often in Duckietown. Below, we give some examples

Examples

Modified 2020-05-26 by Andrea F. Daniele

Set the container name to joystick:

--name joystick

Mount the host’s path /home/myuser/data to /data inside the container:

-v /home/myuser/data:/data

Publish port 8080 in the container as 8082 on the host:

-p 8082:8080

Allow the container to use the device /dev/mmcblk0:

-d /dev/mmcblk0

Run a container on the Duckiebot:

-H duckiebot.local

Modified 2020-05-26 by Andrea F. Daniele

Pruning images

Modified 2020-05-26 by Andrea F. Daniele

Sometimes your docker system will be clogged with images, containers, networks, etc. You can use docker system prune to clean it up.

laptop $ docker system prune

Keep in mind that this command will delete all containers that are not currently running and all images not used by running containers. So be extremely careful when using it.

Portainer

Modified 2020-05-26 by Andrea F. Daniele

Often, for simple operations and basic commands, one can use Portainer.

Portainer is itself a Docker container that allows you to control the Docker daemon through your web browser. You can install it by running:

laptop $ docker volume create portainer_data
laptop $ docker run -d -p 9000:9000 --name portainer --restart always -v /var/run/docker.sock:/var/run/docker.sock -v portainer_data:/data portainer/portainer

Note that Portainer comes pre-installed on your Duckiebot, so you don’t need to run the above command to access the images and containers on your robot. You still might want to set it up for your computer.

Modified 2020-05-26 by Andrea F. Daniele

Before you can do any software development in Duckietown, you need to get comfortable with Docker and its tools.

Complete the following steps before proceeding to the next section:

1. Install Docker
2. Orientation and Setup
3. Build and run your image
4. Share images on Docker Hub

If you still feel like there is something that you are missing about Docker, you might want to spend some time going through this guide as well.

Modified 2020-05-26 by Andrea F. Daniele

If you need help with Docker basics or the use of Docker in Duckietown, join the Slack channel #help-docker.