Introduction to Docker

Introduces docker- a tool for software containerization.

Pull images with docker pull <image-id>

List all images on the computer and other information with docker images

Image tags distinguish releases or version and are appended to the image name with a colon

Run containers with docker run <image-id>

Monitor containers with docker ps

Exit interactive sessions using the exit command

Restart stopped containers with docker start

Copy files with docker cp

Mount volumes with docker run -v <path on host>:<path in container> <image>

Dockerfiles are written as text file commands to the Docker engine

Docker images are built with docker build

Docker images can have multiple tags associated to them

Docker images can use COPY to copy files into them during build

Remove containers with docker rm <CONTAINER NAME>

Remove images with docker rmi <IMAGE ID>

Perform faster cleanup with docker container prune, docker image prune, and docker system prune

Breaks are helpful in the service of learning

gitlab CI allows you to re-build a container that encapsulates the environment each time new commits are pushed to the analysis repo.

This functionality is enabled by adding a Dockerfile to your repo that specifies how to build the environment, and an image-building stage to the .gitlab-ci.yml file.

Containerized analysis environments allow for fully reproducible code testing and development, with the convenience of working on your local machine.

Fortunately, there are tools to help you automate all of this.

Singularity needs to be used for running containers on LXPLUS.

To run your own container, you need to run Singularity manually.

CMD provide defaults for an executing container

CMD can provide options for ENTRYPOINT

ENTRYPOINT allows you to configure commands that will always run for an executing container

Python packages can be installed in Docker images along with ubuntu packages.

It is possible to publish and share Docker images over github packages.