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Run a pipeline with Wave and Fusion with Google Kubernetes Engine

Summary

This example shows how to use Wave to provision the Fusion file system and run it in a Google Kubernetes Engine (GKE) cluster using a Google Storage bucket as pipeline work directory.

NOTE: it requires Nextflow 23.02.1-edge or later.

Cluster preparation

  1. Create a GKE "standard" cluster ("Autopilot" is not supported yet). See Google documentation for details.
  2. Make sure to use instance types with 2 or more CPUs and providing SSD instance storage (families: n1,n2,c2, m1, m2, m3)
  3. Make sure to enable the Workload identity feature when creating (or updating) the cluster.
    • "Enable Workload Identity" in the cluster "Security" setting
    • "Enable GKE Metadata Server" in the node group "Security" settings
    • Configure the cluster following the See the Google documentation for details.
    • The following values were used in this example (replace them with values corresponding your environment):
      • CLUSTER_NAME: the GKE cluster name e.g. cluster-2
      • COMPUTE_REGION: the GKE cluster region e.g. europe-west1
      • NAMESPACE: the GKE namespace e.g. wave-demo
      • KSA_NAME: the GKE service account name e.g. wave-sa
      • GSA_NAME: the Google service account e.g. gsa-demo
      • GSA_PROJECT: the Google project id e.g. my-nf-project-261815
      • PROJECT_ID: the Google project id e.g. my-nf-project-261815
      • ROLE_NAME: the role to grant access permission to the Google Storage bucket e.g. roles/storage.admin
  4. Create the K8s role and rolebinding required to run Nextflow applying the manifest include in this directory: 
    kubectl apply -f gke.yml

Config file

Nextflow configuration template for the deploying a Nextflow pipeline in a GKE cluster using Wave and Fusion.

wave {
  enabled = true
}

fusion {
  enabled = true
}

process {
   executor = 'k8s'
   scratch = false
}

k8s {
    context = '<YOUR-GKE-CLUSTER-CONTEXT>'
    namespace = 'wave-demo'
    serviceAccount = 'wave-sa'
    pod.nodeSelector = 'iam.gke.io/gke-metadata-server-enabled=true'
}

Run it

nextflow run rnaseq-nf \
  -work-dir gs://<YOUR-BUCKET>/work

Make sure to specify a Google Storage bucket to which you have read-write access as work directory.