Intro to Docker
This is going to be a hands-on interactive session. We’re going to use an image on Jetstream that already has Docker installed (go ahead and kick that off now if you haven’t already), but if you’d like to install docker locally on your laptop here are a few links:
Docker Hub Account
You’ll want to create a Docker Hub account in order to easily share your containers with other researchers.
To create an account, go to https://hub.docker.com/, click Sign up for Docker Hub,
and create a username/password to associate with your email.
Typically, accessing the docker daemon requires root or to be in the docker group. For the purposes of this introduction, we can simply do everything as the root user. Login to your virtual machine and switch to the root user:
ssh $USERNAME@$IP_ADDRESS
sudo su - root
Make sure you can access the docker daemon; you can verify this by checking the version:
$ docker version
Client:
Version: 18.09.7
API version: 1.39
Go version: go1.10.1
Git commit: 2d0083d
Built: Wed Jul 3 12:13:59 2019
OS/Arch: linux/amd64
Experimental: false
Server:
Engine:
Version: 18.09.7
API version: 1.39 (minimum version 1.12)
Go version: go1.10.1
Git commit: 2d0083d
Built: Mon Jul 1 19:31:12 2019
OS/Arch: linux/amd64
Experimental: false
Create a test directory to contain your docker work:
$ mkdir docker; cd docker
We’ll also want to login to your Docker Hub account so we can push images:
docker login
# Enter username/password
Docker Images and Tags, Docker Hub, and Pulling Images
A Docker image is a container template from which one or more containers can be run. It is a rooted filesystem that, by definition, contains all of the file dependencies needed for whatever application(s) will be run within the containers launched from it. The image also contains metadata describing options available to the operator running containers from the image.
One of the great things about Docker is that a lot of software has already been packaged into Docker images. One source of 100s of thousands of public images is the official docker hub: https://hub.docker.com.
The docker hub contains images contributed by individual users and organizations as well as “official images”. Explore the official docker images here: https://hub.docker.com/explore/
Most modern programming languages offer an official image. For example, there is an official image for the Python programming language: https://hub.docker.com/_/python/
Docker supports the notion of image tags, similar to tags in a git repository. Tags identify a specific version of an image.
The full name of an image on the Docker Hub is comprised of components separated by slashes. The components include a “repository” (which could be owned by an individual or organization), the “name”, and the “tag”. For example, an image with the full name
jstubbs/test:0.1
would be the “test” in the “jstubbs” repository and have a tag of “0.1”. TACC maintains multiple repositories on the Docker Hub including:
tacc
taccsciapps
agaveapi
abaco
Official images such as the python official image are not owned by a repository, but all other images are.
To pull an image off Docker Hub use the docker pull command
$ docker pull python
Using default tag: latest
latest: Pulling from library/python
cc1a78bfd46b: Pull complete
. . .
As indicated in the output, if no tag is specified the “latest” tag is pulled. You can verify that the image is
available on your local machine using the docker images command:
$ docker images
REPOSITORY TAG IMAGE ID CREATED SIZE
jstubbs/test latest 9dfe5a2c4b43 52 minutes ago 81.2 MB
python latest a5b7afcfdcc8 3 hours ago 912 MB
Running a Docker Container
We use the docker run command to run containers from an image. We pass a command to run in the container. Similar
to running other programs on Unix systems, we can run containers in the foreground (attached) or in the backgrouns.
Running and Attaching to a Container
To run a container and attach to it in one command, use the -it flags. Here we run bash in a container from the ubuntu image:
docker run -it ubuntu bash
root@c10f52ac8ba2:/# ls
root@c10f52ac8ba2:/# exit
ls
Running a Container in Daemon mode
We can also run a container in the background. We do so using the -d flag:
docker run -d ubuntu sleep infinity
docker ps
docker ps -a
Installing and Running the Containerized Classifier Application
We have packaged up a self-contained image classifier application based on the TensorFlow library. Our image is available from the DockerHub. To download it, issue the following commnand:
$ docker pull jurrutia/classify_image:1.0.0
What you are downloading is a complete application that will run an image classifier algorithm on an image that is publicly available from the internet.
Once the download is complete, we can run one or more containers from our image. This particular image requires
an environment variable, $URL, containing the address to a publicly available image, to be passed in at run time.
For example, we can run our image classifier program on the 3 different images:
$ docker run -it --rm -e URL=https://raw.githubusercontent.com/TACC/taccster18_Cloud_Tutorial/master/classifier/data/dog.jpeg jurrutia/classify_image:1.0.0
$ docker run -it --rm -e URL=https://www.dropbox.com/s/f93aixy0r5f1fz1/jimo.jpeg?raw=1 jurrutia/classify_image:1.0.0
$ docker run -it --rm -e URL=https://www.dropbox.com/s/80o4vbzrz4eyzp0/mpackard.jpg?raw=1 jurrutia/classify_image:1.0.0
Additional Remarks on Running Containers
Running Additional Commands in a Running Container
Finally, we can execute commands in a running container using the docker exec command. First, we need to know the container id, which we can get through the docker ps command:
~ $ docker ps
CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
e372ff3fde69 ubuntu "sleep infinity" 2 minutes ago Up 2 minutes jovial_lewin
Here we see the container id is e372ff3fde69. To execute bash in this container we do:
docker exec -it e372ff3fde69 bash
ls
exit
At this point we are attached to the running container. If our bash session exits, the container will keep running because the sleep infinity command is still running.
*Note: The docker ps command only shows you running containers - it does not show you containers that have exited. In order to see all containers
on the system use docker ps -a.
root@js-104-88:~/docker# docker ps -a
CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
e372ff3fde69 ubuntu "sleep infinity" 2 minutes ago Up 2 minutes jovial_lewin
c10f52ac8ba2 ubuntu "bash" 7 minutes ago Exited (0) 6 minutes ago focused_payne
Removing Docker Containers
You can stop the container with the docker stop command. Pass either the container ID or the Name to docker stop:
docker stop e372ff3fde69
docker stop jovial_lewin
We can remove a docker container using the docker rm command (optionally passing -f to “force” the removal if the container is running). You will need the container name or id to remove the container:
$ docker rm -f e372ff3fde69
These IDs will be unique for your container.
Building Images From a DockerFile
We can build images from a text file called a Dockerfile. You can think of a Dockerfile as a recipe for creating images. The instructions within a dockerfile either add files/folders to the image, add metadata to the image, or both.
The FROM instruction
We can use the FROM instruction to start our new image from a known image. This should be the first line of our Dockerfile. We will start our image from an official Ubuntu image:
FROM ubuntu:latest
The RUN instruction
We can add files to our image by running commands with the RUN instruction. We will use that to install wget via apt. Keep in mind that the the docker build cannot handle interactive prompts, so we use the -y flag in apt. We also need to be sure to update our apt packages.
The Dockerfile will look like this now:
FROM ubuntu:latest
RUN apt-get update && apt-get install -y wget
The ADD instruction
We can also add local files to our image using the ADD instruction. We can add a file test.txt in our local directory to the /root directory in our container with the following instruction:
ADD test.txt /root/text.txt
A complete Dockerfile for the classify_image application as well as the necessary scripts and supporting files is available from the Tutorial gihub repo: https://github.com/TACC/taccster18_Cloud_Tutorial/tree/master/classifier
Building the Image
To build an image from a Dockerfile we use the docker build command. We use the -t flag to tag the image: that is, give our image a name. We also need to specify the working directory for the buid. We specify the current working directory using a dot (.) character:
docker build -t classify_image .
Note that this command requires all the files in the classifier directory in the Tutorial github repo (https://github.com/TACC/taccster18_Cloud_Tutorial/tree/master/classifier)
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