1. Jindo Directly Accelerating OSS Set the environment variables 1 2 3 4 5 6 7 export ENDPOINT=oss-cn-beijing-internal.aliyuncs.com export BUCKET= export AK= export SK= export NAMESPACE=default export PVC=myoss-jindo export URI=datacenter Create the credentials 1 2 3 4 5 6 7 8 9 10 11 kubectl apply -f - <<EOF apiVersion:

1. About JuiceFS Caching On a host, warmed cache is placed directly on the host. In a cluster, there are two levels of cache: Worker, which provides cache shared at the cluster level Fuse, which provides cache at the current node level only 2. Warming Data with the JuiceFS Client Note that warming at the Fuse layer is only effective for the current node; if you need to warm the whole cluster, you must warm at the Worker layer.

1. Create the Dataset 1 2 3 4 5 6 7 8 9 10 kubectl apply -f - <<EOF apiVersion: v1 kind: Secret metadata: name: my-s3 type: Opaque stringData: aws.accessKeyId: xxx aws.secretKey: xxx EOF 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 kubectl apply -f - <<EOF apiVersion: data.

1. Packaging the Fluid Runtime Image Create the fluid_config_init.py script 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 #!/usr/bin/env python import json rawStr = "" with open("/etc/fluid/config.json", "r") as f: rawStr = f.

1. Analyzing How Fluid Mounts NFS Storage Inspect the Fuse Pod 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 kubectl get pod nfs-demo-fuse-f9wg8 -oyaml apiVersion: v1 kind: Pod metadata: generateName: nfs-demo-fuse- spec: containers: - command: - /usr/local/bin/entrypoint.