Templates for a DU workload deployed with kube-burner
Pod | Number of Pods | Specs | Stress |
---|---|---|---|
Guaranteed | 1 pod, 2 containers | - 32 CPU, 1 GiB Memory, 16 GiB HP - 2 configmaps and 4 secrets 1 svc |
32 threads of 100% CPU stress, 512M virtual memory stress |
BestEffort - web_server | 4 pods, 2 containers each | - 100 mc CPU, 128 Mib Memory - 2 configmaps and 4 secrets |
Exposes 8080 port for probes |
BestEffort - curl_app | 4 pods, 2 containers each | - 100 mc CPU, 128 Mib Memory - 2 configmaps and 4 secrets - Liveness Probes (every 10 secs) |
Kubelet stress with probes, ~250 KB per sec n/w traffic on Primary CNI |
BestEffort - kubectl_pods | 6 pods, 2 containers each | - 100 mc CPU , 128 Mib Memory - 2 configmaps and 4 secrets - 2 kubectl gets (every 5 sec) |
Kube-api-server stress with kubectl get, ~10% increase due to workload |
- Total pods - 15 pods / 30 containers
- 2 config maps and 4 secrets in each pod
- Exec Probes less than 10 in total and frequency >10 secs
- No Exec probes on Gu pod
- Traffic on primary CNI due to workload expected around 350 KB per sec
- kube api-server incremental load due to workload expected to increase by 5-8%
Intended for use in internal system testing pipelines but the templates can be run on any cluster with kube-burner
- Run the MIRROR_SPOKE_OPERATOR_IMAGES stage in ocp-far-edge-vran-deployment pipeline to mirror necessary test images
- Run the cpu_util test using ocp-far-edge-vran-tests pipeline
- export REGISTRY=quay.io/rh_ee_apalanis
- clone and deploy DU workload with
kube-burner init --config du-intensive.yaml