Docker (and Singularity) for reproducible and automated data analysis
The course will give an introduction to containers (Docker & Singularity) which are great components to achieve portability and reproducibility of your analysis. You will learn how to use containers and how to build a container from scratch, share it with others and how to re-use and modify existing containers. After an extensive explanation on Docker containers, Singularity will be highlighted as well.
Objectives
- Learn the concept of and the difference between Docker & Singularity containers
- Write a Docker recipe, build and run a Docker image and containers
- Pull and push Docker container to / from Docker hub
- Docker files and layers; Docker cashing
- Working with volumes
- Pull Docker containers as a Singularity image