Benchmark Kubernetes persistent disk volumes with fio: Read/write IOPS, bandwidth MB/s and latency.
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List down all Kubernetes storageClassName using command kubectl get storageclasses
Note down the storage class that you want to bench mark and use as storageClassName in below yaml file
Create a PVC claim and Job using below yaml
kind: PersistentVolumeClaim
apiVersion: v1
metadata:
name: dbench-pv-claim
spec:
storageClassName: ssd
accessModes:
- ReadWriteOnce
resources:
requests:
storage: 100Gi
---
apiVersion: batch/v1
kind: Job
metadata:
name: dbench
spec:
template:
spec:
containers:
- name: dbench
image: logdna/dbench:latest
imagePullPolicy: Always
env:
- name: DBENCH_MOUNTPOINT
value: /data
# - name: DBENCH_QUICK
# value: "yes"
# - name: FIO_SIZE
# value: 1G
# - name: FIO_OFFSET_INCREMENT
# value: 256M
# - name: FIO_DIRECT
# value: "0"
volumeMounts:
- name: dbench-pv
mountPath: /data
restartPolicy: Never
volumes:
- name: dbench-pv
persistentVolumeClaim:
claimName: dbench-pv-claim
backoffLimit: 4
Deploy Dbench using: kubectl apply -f dbench.yaml. Once deployed, the Dbench Job will:
Follow benchmarking progress using: kubectl logs -f job/dbench (empty output means the Job not yet created, or storageClassName is invalid, see Troubleshooting below)
At the end of all tests, you'll see a summary that looks similar to this:
==================
= Dbench Summary =
==================
Random Read/Write IOPS: 75.7k/59.7k. BW: 523MiB/s / 500MiB/s
Average Latency (usec) Read/Write: 183.07/76.91
Sequential Read/Write: 536MiB/s / 512MiB/s
Mixed Random Read/Write IOPS: 43.1k/14.4k
Once the tests are finished, clean up using: kubectl delete -f dbench.yaml and that should deprovision the persistent disk and delete it to minimize storage billing.
docker pull adnan80/dbench