This document provides pre-configured Google Kubernetes Engine YAML files to help you optimize Cloud Storage FUSE performance for your specific workload. Whether you're using Cloud GPUs or Cloud TPU for training, serving, or checkpointing, you can use the sample configurations provided in this page to quickly deploy your GKE pods and access your Cloud Storage bucket.

Configure and deploy GKE workloads with Cloud Storage FUSE using sample YAML files

To utilize sample configurations, perform the following steps:

1. Verify that the Cloud Storage FUSE CSI driver for Google Kubernetes Engine is running on GKE clusters of GKE versions 1.32.2-gke.1297001 or later.

2. Verify that the Google Kubernetes Engine service account possesses the necessary permissions to access the target Cloud Storage bucket.

3. Locate the sample configurations you want to apply based on your machine type and workload by using one of the following YAML files:

4. Deploy the corresponding pod specification that accesses the PersistentVolumeClaim using one the following YAML files:

5. Deploy the PersistentVolume and PersistentVolumeClaim by applying the PersistentVolume file.

   The GKE pod admission webhook inspects the PersistentVolume attributes to apply potential optimizations such as the injection of sidecar containers before the pod is scheduled.

   kubectl apply -f PERSISTENT_VOLUME_YAML_FILE_NAME
   

   Replace the following:

   • PERSISTENT_VOLUME_YAML_FILE_NAME is the name of the PersistentVolume YAML filename. For example, serving-pv.yaml.

6. Deploy the pod specification that references the PersistentVolumeClaim:

   kubectl apply -f POD_YAML_FILE_NAME
   

   Replace the following:

   • POD_YAML_FILE_NAME is the name of the pod YAML configuration file. For example, serving-pod.yaml.

What's next

• Learn how to monitor Cloud Storage FUSE performance using metrics.