Hello, I have been running nf-core/rnaseq pipeline in VM with fixed computing resources, now try to use it with AWS batch to have a more flexible resource allocation. From this document https://docs.seqera.io/platform-cloud/compute-envs/aws-batch, seems like there is an automatic way to set up the compute environment with Forge. I am wondering to be able to use this approach/Forge, do I have to subscript the service? Thanks!

Forge is part of Seqera Platform: https://seqera.io/platform/ Which is a paid-for offering by Seqera. There's a bit of trial/ free usage included but for anything substantial you'd need to be a customer, or your institute would need to enrolled in the academic program. nf-core has an example config (https://nf-co.re/configs/awsbatch/) but no particular best practice as far as I'm aware. This blog from Seqera is a bit old now, but probably mostly still valid: https://seqera.io/blog/nextflow-and-aws-batch-inside-the-integration-part-1-of-3/

@Jonathan Manning Thanks, Jonathan, for the information. I found https://seqera.io/blog/nextflow-and-aws-batch-inside-the-integration-part-1-of-3/ is very useful. I am particularly interested in figuring out how to integrate nf-core pipelines with AWS batch which was not specifically documented. Normally nf-core pipelines automatically pull in software docker images, handle computing resources for each process, I would like nf-core do the same when integrate with AWS batch, so I don't have to manually install these dependencies or change the settings. Do you know whether it is possible and how to make it happen? What is the best AWS compute environment for nf-core pipelines, ec2 on-demand, ec2 spot, fargate, or fargate spot? I recently failed nf-core/rnaseq with fargate, the error points to running out ram, disk space, software dependencies issues et. al. I am thinking whether I should switch to ec2 on-demand or ec2 spot?