Introduction

  • Docker is a set of products to deliver and run software in packages called containers.
  • Software containers are widely used these days in both industry and academic research.
  • We use software containers during the hands-on sessions to provide the a well-defined software environment for exercises.

Installing docker

  • For up-to-date details for installing Docker, the official documentation is the best bet.
  • Make sure you were able to download and run Docker’s hello-world example.
  • The concepts of image and container, plus the knowledge of certain Dockers commands, is all that is needed for the hands-on sessions.

Docker containers for CMS open data

  • You have now set up a docker container as a working enviroment for CMS open data.
  • You know how to pass files between your own computer and the container.
  • You know how to open a graphical window of ROOT or a jupyterlab in your browser using software installed in the container.

Docker containers for Monte Carlo generators and Rivet

  • You have now set up a docker container as a working enviroment Rivet and Pythia.
  • You know how to share a working area between your own computer and the container.

Building your own docker image

  • It is easy to build a new container image on top of an existing image.
  • You can install packages that you need if they are not present in an existing image.
  • You can add code and eventually compile it in the image so that it is ready to use when the container starts.

Sharing your docker image

  • It is easy to build a new container image on top of an existing image.
  • You can install packages that you need if they are not present in an existing image.
  • You can add code and eventually compile it in the image so that it is ready to use when the container starts.