1.9 KiB
Quick start
This example show case how one can use a metricsTrait to add prometheus monitoring capability to any workload that emits metrics data.
Install Vela core
make docker-build
kubectl create ns vela-system
helm install kube --namespace vela-system charts/vela-core/
OAM will automatically install a prometheus stack in the monitoring namespace if it does not detect a prometheus CRDs in the cluster
Run ApplicationConfiguration
kubectl apply -f e2e/raw-objects/samples/metrics-demo/
workloaddefinition.core.oam.dev/deployments.apps created
traitdefinition.core.oam.dev/services created
traitdefinition.core.oam.dev/metricstraits.standard.oam.dev created
component.core.oam.dev/sample-application created
applicationconfiguration.core.oam.dev/sample-application-with-metrics created
Verify that the metrics are collected on prometheus
kubectl --namespace monitoring port-forward svc/prometheus-oam 4848
Then access the prometheus dashboard via http://localhost:4848
Verify that the metrics showing up on grafana
kubectl --namespace monitoring port-forward service/kube-prometheus-stack-grafana 3000:80
Then access the grafana dashboard via http://localhost:3000. You shall set the data source URL as http://prometheus-oam:4848
Setup Grafana Panel and Alert
kubectl apply -f config/samples/application/dashboard/OAM-Workload-Dashboard.yaml
How to set up a Grafana dashboard https://grafana.com/docs/grafana/latest/features/dashboard/dashboards/
Import the dashboard stored in config/samples/application
How to set up a Grafana alert https://grafana.com/docs/grafana/latest/alerting/alerts-overview/. One caveat is that only one alert is supported for each panel.
How to set up a DingDing robot as the Grafana notification channel https://ding-doc.dingtalk.com/doc#/serverapi2/qf2nxq