Basic introduction to software containers

Application in scientific practice

Docker and Singularity

Toni Hermoso Pulido

Bioinformatics Unit

CRG, Barcelona

Reproducibility Crisis

According to a 2016 poll of 1,500 scientists reported in the journal Nature, 70% of them had failed to reproduce at least one other scientist's experiment (50% had failed to reproduce one of their own experiments).  ​Ref

Reproducibility Crisis

According to a 2016 poll of 1,500 scientists reported in the journal Nature, 70% of them had failed to reproduce at least one other scientist's experiment (50% had failed to reproduce one of their own experiments).  ​Ref

Containers

Containers in science

  • Mantainability
  • Portability
  • Reproducibility

Virtual machines vs containers

Virtualisation

Pros and Cons

 

  • PRO: Very similar to a full OS
  • PRO: With current solutions, high OS diversity
  • CON: Need of more space and resources
  • CON: Slower than containers
  • CON: Not as good automating

Containerisation

Pros and Cons

 

  • PRO: Faster
  • PRO: No need of full OS installation. Less space.
  • PRO: Current solutions allow easier distribution of recipes. More portability
  • PRO: Easier automation
  • CON: Some cases might not be exactly the same as a full OS
  • CON: With current solutions, still less OS diversity

Docker

Docker

  • Platform for developing, shipping, and running applications
  • Infrastructure as application/code
  • Established Open Container Initiative

 

As a software:

Docker architecture

Docker image

  • Read-only templates.
  • Containers are run from them
  • Images are not run
  • Images have several layers

Docker image - Instructions

  • Recipe file:

  • Instructions
    • Every instruction generates an image layer
    • FROM: use a base image (notice tag)
    • ADD, COPY: add files to image filesystem
    • RUN: execute command in image
    • ENV, ARG: Run and build environment variables
    • CMD, ENTRYPOINT: Command to execute when generated container starts

Docker container

  • Generated from an image (template)
  • Image: read-only
  • Container: read-write
  • Can be converted into image
    • docker commit
  • 1 imatge -> n diverse containers
    • Diversity:
      • Volumes / Mounting points
        • Different data or configs
      • Different exposed ports

Run container

$ docker run biocorecrg/c4lwg-2018 /bin/echo "Hello world!"

Docker registry and

Docker hub

  • Images are stored locally
  • They can also be shared in a registry
  • Main Public one: Docker hub

Examples:

Singularity

containers for HPC

Singularity vs Docker

  • Docker -> Microservices
  • Singularity -> HPC

Summarising

Singularity architecture

Singularity - Strenghts

  • No dependency of a daemon
  • Can be run as a simple user
  • Image/container is a file (or directory)
    • More easily portable
  • Two type of images
    • Read-only (production)
    • Writable (development)

Singularity - Weaknesses

  • At the time of writing only good support in Linux
    • Not a big deal in HPC environments, though
  • For some uses you need root account (or sudo)
  • Still young project compared to other solutions

Singularity - run

$ singularity exec c4lwg-2018.simg /bin/echo 'Hello world'
$ singularity exec -e c4lwg-2018.simg /bin/echo 'Hello world'

Execute a command

Execute a command (with clean environment)

Execute a shell

$ singularity shell c4lwg-2018.simg
$ singularity run c4lwg-2018.simg

Execute defined runscript (parameters can be used)

Scientific containers

good pratices

  • Put data and configuration files outside of images
    • Mount them if necessary
  • Choose specific software/distribution versions
    • Not latest tags
  • Save container recipes
  • Save also binary container/images if possible

Further reading

Basic Introduction to containers in scientific practice. Docker and Singularity

By Similis.cc

Basic Introduction to containers in scientific practice. Docker and Singularity

Basic introduction presentation that shows what containers are, two technological implementations (Docker and Singularity) and their rellevance in scientific practice.

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