Working with container images

This page describes how to set up the runtime environment (e.g., the programs, libraries, and other dependencies needed to run a job) that a workflow step will be run in using Docker or Singularity. Docker and Singularity are tools for building and running containers that isolate applications from other applications running on the same node. For detailed information, see the Docker User Guide and the Introduction to Singularity.

Note that Arvados always works with Docker images, even when it is configured to use Singularity to run containers. There are some differences between the two runtimes that can affect your containers. See the Singularity architecture page for details.

This page describes:

  1. Create a custom image using a Dockerfile
  2. Uploading an image to Arvados
  3. Sources of pre-built bioinformatics Docker images


This tutorial assumes that you have installed the Arvados Command line SDK and Python SDK on your workstation and have a working environment.

You also need to ensure that Docker is installed, the Docker daemon is running, and you have permission to access Docker. You can test this by running docker version. If you receive a permission denied error, your user account may need to be added to the docker group. If you have root access, you can add yourself to the docker group using $ sudo addgroup $USER docker then log out and log back in again; otherwise consult your local sysadmin.

Create a custom image using a Dockerfile

This example shows how to create a Docker image and add the R package.

First, create new directory called docker-example, in that directory create a file called Dockerfile.

$ mkdir docker-example-r-base
$ cd docker-example-r-base
FROM ubuntu:bionic
RUN apt-get update && apt-get -yq --no-install-recommends install r-base-core

The “RUN” command is executed inside the container and can be any shell command line. You are not limited to installing Debian packages. You may compile programs or libraries from source and install them, edit systemwide configuration files, use other package managers such as pip or gem, and perform any other customization necessary to run your program.

You can also visit the Docker tutorial for more information and examples.

You should add your Dockerfiles to the same source control repository as the Workflows that use them.

Create a new image

We’re now ready to create a new Docker image. Use docker build to create a new image from the Dockerfile.

docker-example-r-base$ docker build -t docker-example-r-base .

Verify image

Now we can verify that “R” is installed:

$ docker run -ti docker-example-r-base
root@57ec8f8b2663:/# R

R version 3.4.4 (2018-03-15) -- "Someone to Lean On"
Copyright (C) 2018 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

Upload your image

Finally, we are ready to upload the new Docker image to Arvados. Use arv-keepdocker with the image repository name to upload the image. Without arguments, arv-keepdocker will print out the list of Docker images in Arvados that are available to you.

$ arv-keepdocker docker-example-r-base
2020-06-29 13:48:19 arvados.arv_put[769] INFO: Creating new cache file at /home/peter/.cache/arvados/arv-put/39ddb51ebf6c5fcb3d713b5969466967
206M / 206M 100.0% 2020-06-29 13:48:21 arvados.arv_put[769] INFO:

2020-06-29 13:48:21 arvados.arv_put[769] INFO: Collection saved as 'Docker image docker-example-r-base:latest sha256:edd10'

$ arv-keepdocker images
REPOSITORY                      TAG         IMAGE ID      COLLECTION                     CREATED
docker-example-r-base           latest      sha256:edd10  zzzzz-4zz18-0tayximqcyb6uf8    Mon Jun 29 17:46:16 2020

You are now able to specify the runtime environment for your program using DockerRequirement in your workflow:

    dockerPull: docker-example-r-base

Uploading Docker images to a shared project

Docker images are subject to normal Arvados permissions. If wish to share your Docker image with others you should use arv-keepdocker with the --project-uuid option to add the image to a shared project and ensure that metadata is set correctly.

$ arv-keepdocker docker-example-r-base --project-uuid zzzzz-j7d0g-xxxxxxxxxxxxxxx

Sources of pre-built images

In addition to creating your own contianers, there are a number of resources where you can find bioinformatics tools already wrapped in container images:



Docker Hub

Previous: CWL Resources Next: Guidelines for Writing High-Performance Portable Workflows

The content of this documentation is licensed under the Creative Commons Attribution-Share Alike 3.0 United States licence.
Code samples in this documentation are licensed under the Apache License, Version 2.0.