Wave containers

New in version 22.10.0.

Wave is a container provisioning service integrated with Nextflow. With Wave, you can build, upload, and manage the container images required by your data analysis workflows automatically and on-demand during pipeline execution.

Getting started

Nextflow installation

If you have already installed Nextflow, update to the latest version using this command:

nextflow -self-update

If you don’t have Nextflow already installed, install it with the command below:

curl get.nextflow.io | bash

Wave configuration

Wave can be used in any Nextflow pipeline by adding the following snippet to your nextflow.config file:

wave {
  enabled = true
}

tower {
  accessToken = '<your access token>'
}

Note

The Seqera Platform access token is not mandatory, but it is recommended in order to access private container repositories and pull public containers without being affected by service rate limits. Credentials should be made available to Wave using the credentials manager in Seqera Platform.

Use cases

Authenticate private repositories

Wave allows the use of private repositories in your Nextflow pipelines. The repository access keys must be provided in the form of Seqera Platform credentials.

Once the credentials have been created, simply specify your personal access token in your pipeline configuration file. If the credentials were created in a Seqera Platform organization workspace, specify the workspace ID as well in the config file as shown below:

tower {
  accessToken = '<your access token>'
  workspaceId = '<your workspace id>'
}

Build module containers

Wave can build and provision container images on-demand for your Nextflow pipelines.

To enable this feature, add the Dockerfile of the container to be built in the module directory where the pipeline process is defined. When Wave is enabled, it automatically uses the Dockerfile to build the required container, upload to the registry, and it uses the container to carry out the tasks defined in the module.

Tip

Make sure the process does not declare a container directive, otherwise it will take precedence over the Dockerfile definition.

If a process uses a container directive and you still want to build the container using the Dockerfile provided in the module directory, add the following setting to the pipeline config file:

wave.strategy = ['dockerfile','container']

This setting instructs Wave to prioritize the module Dockerfile over process container directives.

Warning

When building containers, Wave currently does not support ADD, COPY, or any other Dockerfile commands that access files in the host file system.

Build Conda based containers

Wave allows the provisioning of containers based on the conda directive used by the processes in your pipeline. This is a quick alternative to building Conda packages in the local computer. Moreover, this enables the use of Conda packages in your pipeline when deploying in cloud-native platforms such as AWS Batch and Kubernetes, which do not allow the (easy) use of the Conda package manager.

With Wave enabled in your pipeline, simply define the conda requirements in the pipeline processes, provided the same process does not also specify a container directive or a Dockerfile.

In the latter case, add the following setting to your pipeline configuration:

wave.strategy = ['conda']

The above setting instructs Wave to use the conda directive to provision the pipeline containers and ignore the container directive and any Dockerfile(s).

Tip

Some configuration options in the conda scope are used when Wave is used to build Conda-based containers. For example, the Conda channels and their priority can be set with conda.channels:

wave.strategy = 'conda'
conda.channels = 'conda-forge,bioconda'

Build Spack based containers

Warning

Spack based Wave containers are currently in beta testing. Functionality is still sub-optimal, due to long build times that may result in backend time-out and subsequent task failure.

Wave allows the provisioning of containers based on the spack directive used by the processes in your pipeline. This is an alternative to building Spack packages in the local computer. Moreover, this enables to run optimised builds with almost no user intervention.

Having Wave enabled in your pipeline, there’s nothing else to do other than define the spack requirements in the pipeline processes provided the same process does not also specify a container or conda directive or a Dockerfile.

In the latter case, add the following setting to your pipeline configuration:

wave.strategy = ['spack']

The above setting instructs Wave to only use the spack directive to provision the pipeline containers, ignoring the use of the container directive and any Dockerfile(s).

In order to request the build of containers that are optimised for a specific CPU microarchitecture, the latter can be specified by means of the arch directive. The architecture must always be specified for processes that run on an ARM system. Otherwise, by default, Wave will build containers for the generic x86_64 architecture family.

Note

If using a Spack YAML file to provide the required packages, you should avoid editing the following sections, which are already configured by the Wave plugin: packages, config, view and concretizer (your edits may be ignored), and compilers (your edits will be considered, and may interfere with the setup by the Wave plugin).

Build Singularity native images

New in version 23.09.0-edge.

Nextflow can build Singularity native images on-demand either using Singularityfile, Conda packages or Spack packages. The Singularity images are automatically uploaded in a container registry OCI compliant of your choice and stored as a ORAS artefact.

Note

This feature requires of Singularity (or Apptainer) version supporting the pull of images using the oras: pseudo-protocol.

For example to enable the provisioning of Singularity images in your pipeline use the following configuration snippet:

singularity.enabled = true
wave.enabled = true
wave.freeze = true
wave.strategy = ['conda']
wave.build.repository = 'docker.io/user/repo'

In the above configuration replace docker.io/user/repo with a repository of your choice where Singularity image files should be uploaded.

Note

When using a private repository, the repository access keys must be provided via the Seqera Platform credentials manager (see above).

Moreover the access to the repository must be granted in the compute nodes by using the command singularity remote login <registry>. Please see Singularity documentation for further details.

Note

In order to build Singularity native images, both singularity.ociAutoPull and singularity.ociMode need to be disabled in the configuration (see the Scope singularity section).

Push to a private repository

Containers built by Wave are uploaded to the Wave default repository hosted on AWS ECR at 195996028523.dkr.ecr.eu-west-1.amazonaws.com/wave/build. The images in this repository are automatically deleted 1 week after the date of their push.

If you want to store Wave containers in your own container repository use the following settings in the Nextflow configuration file:

wave.build.repository = 'example.com/your/build-repo'
wave.build.cacheRepository = 'example.com/your/cache-repo'

The first repository is used to store the built container images. The second one is used to store the individual image layers for caching purposes.

The repository access keys must be provided as Seqera Platform credentials (see Authenticate private repositories above).

Run pipelines using Fusion file system

Wave containers allows you to run your containerised workflow with the Fusion file system.

This enables the use of an object storage bucket such as AWS S3 or Google Cloud Storage as your pipeline work directory, simplifying and speeding up many operations on local, AWS Batch, Google Batch or Kubernetes executions.

See the Fusion documentation for more details.

Advanced settings

Wave advanced configuration settings are described in the Wave section on the Nextflow configuration page.