I recently went down the rabbit hole trying out the newest bioinformatics workflow manager, redun. While installation and running workflows locally went off without a hitch, I experienced some trouble getting jobs deployed to AWS Batch. Here’s a list of my troubleshooting steps, in case you experience the same issues. To start, I followed the instructions for the “05_aws_batch” example workflow.

I was deploying the workflow on my AWS account at Loyal. This may change if you’re using a new AWS account, or have different security policies in place.

Building docker images

Docker needs root access to build and push images to a registry. In practice, this often means using “sudo” before every command. You can fix this with the command sudo chmod 666 /var/run/docker.sock

Or see the longer fix in this stack overflow post.

Submitting jobs to AWS Batch

I experienced the following error when submitting jobs to AWS Batch:

upload failed: - to s3://MY-BUCKET/redun/jobs/ca27a7f20526225015b01b231bd0f1eeb0e6c7d8/status
An error occurred (AccessDenied) when calling the PutObject operation: Access Denied
fatal error: An error occurred (403) when calling the HeadObject operation: Forbidden

I thought this was due to an error in the “role” setting, and that was correct. I first tried using the generic role

arn:aws:iam::ACCOUNT-ID:role/aws-service-role/batch.amazonaws.com/AWSServiceRoleForBatch

but that didn’t work.

I then added a custom IAM role to AWS with S3, EC2, ECS and Batch permissions. I added the following permissions as well:

{
  "Version": "2012-10-17",
  "Statement": [
    {
      "Sid": "",
      "Effect": "Allow",
      "Principal": {
        "Service": "ecs-tasks.amazonaws.com"
      },
      "Action": "sts:AssumeRole"
    }
  ]
}

And then everything worked as expected.

ECS unable to assume role

I heard from someone else trying redun for the first time that they were able to get the batch submission working with the (similar) instructions at this stack overflow post

I hope this helps anyone trying to deploy redun to AWS Batch for the first time!

Workflow managers form the cornerstone of a modern bioinformatics stack. By enabling data provenance, portability, scalability, and re-entrancy, workflow managers accelerate the discovery process in any computational biology task. There are many workflow managers available to chose from (a community-sourced list holds over 300): Snakemake, Nextflow, and WDL… each have their relative strengths and drawbacks.

The engineering team at Insitro saw all the existing workflow managers, and then decided to invest in building their own: redun. Why? The motivation and influences docs pages lay out many of the reasons. In short, the team wanted a workflow manager written in Python that didn’t require expressing pipelines as dataflows.

I spent a few days trying out redun – working through the examples and writing some small workflows of my own. I really like the project and the energy of open source development behind it. I’m not at the point where I’m going to re-write all of my Nextflow pipelines in redun, but I’m starting to consider the benefits of doing so.

The positives I immediately noticed about redun include:

• redun is Python. Not having to learn a domain-specific language is a huge advantage.
• The ability to execute sub-workflows with a single command. This is helpful if you want to enter a workflow with an intermediate file type.
• I can see redun working as a centralized way to track workflow execution and file provenance within a lab or company.
• There are several options for the execution backend, and redun is easy to deploy to AWS Batch (with some tweaks).
• The tutorial and example workflows were helpful for demonstrating the key concepts.

A few drawbacks, as well:

• There hasn’t been much investment in observability or execution tracking. Compared to Nextflow Tower and other tools, redun is in the last century.
• Similarly, there isn’t yet much community investment in redun, like there is in nf-core.
• While redun is extremely flexible, I bet it will be more challenging for scientists to learn than Snakemake.

There will certainly be other items to add to these lists as I get more familiar with redun. For now, it’s fair to say I’m impressed, and I want to write more pipelines in redun!