Wave containers

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

Note

This feature requires Nextflow 22.10.0 or later.

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 use of the Tower access token is not mandatory, however, it’s recommended to enable the access of private container repositories and to allow the pull of public containers without being affected by service rate limits. Credentials should be made available to Wave using the credentials manager feature in your Tower account.

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 Nextflow Tower credentials.

Once the credentials have been created, simply specify your Tower account access token in your pipeline configuration file. If the credentials were created in a Tower 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 use 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 instructs Wave to prioritize the module Dockerfile over process container directives.

Warning

When building containers, Wave currently does not support ADD, COPY and 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).

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 Tower credentials (see Authenticate private repositories above).

Run pipelines using Fusion file system

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

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

See Fusion documentation for more details.

Advanced settings

The following configuration options are available:

Name	Description
wave.enabled	Enable/disable the execution of Wave containers
wave.endpoint	The Wave service endpoint (default: https://wave.seqera.io)
wave.build.repository	The container repository where images built by Wave are uploaded (note: the corresponding credentials must be provided in your Nextflow Tower account).
wave.build.cacheRepository	The container repository used to cache image layers built by the Wave service (note: the corresponding credentials must be provided in your Nextflow Tower account).
wave.build.conda.mambaImage	The Mamba container image is used to build the Conda-based container. This is expected to be the micromamba-docker image.
wave.build.conda.commands	One or more commands to be added to the Dockerfile used to build a Conda-based image.
wave.build.conda.basePackages	One or more Conda packages that should always added in the resulting container e.g. conda-forge::procps-ng.
wave.strategy	The strategy to be used when resolving ambiguous Wave container requirements (default: 'container,dockerfile,conda')

More examples

See the Wave showcase repository for more Wave containers configuration examples.