I have created a persistent volume claim where I will store some ml model weights as follows:
apiVersion: v1
kind: PersistentVolumeClaim
metadata:
name: models-storage
spec:
accessModes:
- ReadWriteOnce
storageClassName: model-storage-bucket
resources:
requests:
storage: 8Gi
However this configuration will provision a disk on a compute engine, and it is a bit cumbersome to copy stuff there and to upload/update any data. Would be so much more convenient if I could create a PersistentVolume
abstracting a google cloud storage bucket. However, I couldn't find anywhere including the google documentation a way to do this. I am baffled because I would expect this to be a very common use case. Anyone knows how I can do that? I was expecting to find something along the lines of
apiVersion: v1
kind: PersistentVolume
metadata:
name: test-volume
spec:
storageBucketPersistentDisk:
pdName: gs://my-gs-bucket
To mount cloud storage bucket you need to install Google Cloud Storage driver ( NOT the persistent disk nor file store) on your cluster, create the StorageClass and then provision the bucket backed storage either dynamically or static; just as you would like using persistent disk or file store csi driver. Checkout the link for detailed steps.
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