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Work in progress

(30 April 2025)

The contents of this tutorial are currently being reworked to be up-to-date with recent developments in CernVM-FS, and to be well integrated in the EESSI documentation.

It is based on the "Best Practices for CernVM-FS in HPC" tutorial that was held on 4 Dec 2023, see also https://multixscale.github.io/cvmfs-tutorial-hpc-best-practices.

Containers and CernVM-FS

CernVM-FS can also be used to distribute container images, providing many of the same benefits that come with any CernVM-FS installation. Especially the on-demand download of accessed files means that containers start nearly instantly, and are more efficient for large images when only a fraction of the files are read, which is typically the case.

Any CernVM-FS repository can be used to distribute container images (although often, dedicated repositories are used, like /cvmfs/unpacked.cern.ch).

In order to provide de-duplication and on-demand download, images must be stored unpacked. This requires some dedicated tools, provided by CernVM-FS itself - see the section "Ingesting container images" below.

Accessing containers hosted in CernVM-FS via Apptainer

Apptainer is the recommended way to run containers from CernVM-FS, as it can start a container directly from an unpacked root file system, which is ideal for CernVM-FS.

Docker can be used as well but the setup is more complicated, requiring the CernVM-FS graphdriver plugin.

For example, to run the tensorflow/tensorflow:2.15.0-jupyter image from Docker Hub that has been unpacked in /cvmfs/unpacked.cern.ch, use the following commands:

container="registry.hub.docker.com/tensorflow/tensorflow:2.15.0-jupyter"
python_code="import tensorflow as tf; print(tf.__version__)"
apptainer run /cvmfs/unpacked.cern.ch/${container} python -c "${python_code}"

This directory just contains the root file system of the image:

ls /cvmfs/unpacked.cern.ch/registry.hub.docker.com/tensorflow/tensorflow:2.15.0-jupyter

Ingesting container images

CernVM-FS provides a suite of container unpacking tools called cvmfs_ducc (provided by the cvmfs-ducc package). This can be used to unpack and ingest container images by simply running

cvmfs_ducc convert recipe.yaml
where recipe.yaml is a 'wishlist' of container images available in external registries that should be made available:

version: 1
user: cvmfsunpacker
cvmfs_repo: 'unpacked.repo.tld'
input:
    - 'https://registry.hub.docker.com/tensorflow/tensorflow:2.15.0-jupyter'
    ...

For more information, see the CernVM-FS documentation.

Using /cvmfs inside containers

The easiest way to access CernVM-FS repositories from a container is to set it up on the host and bind-mount it inside the container:

docker run -it --volume /cvmfs:/cvmfs:shared ubuntu ls -lna /cvmfs/atlas.cern.ch

For Apptainer, the same can be done by setting the $SINGULARITY_BIND (or $APPTAINER_BIND) environment variable: 

export SINGULARITY_BIND="/cvmfs"

(next: Creating a CernVM-FS repository)