Run Heapster in a Kubernetes cluster with an InfluxDB backend and a Grafana UI
Setup a Kubernetes cluster
Bring up a Kubernetes cluster, if you haven't already.
Ensure that you are able to interact with the cluster via
kubectl (this may be
kubectl.sh if using
the local-up-cluster in the Kubernetes repository).
Start all of the pods and services
In order to deploy Heapster and InfluxDB, you will need to create the Kubernetes resources described by the contents of deploy/kube-config/influxdb.
If you're running a different architecture than amd64, you should correct the image architecture
grafana-deployment.yaml and the
Ensure that you have a valid checkout of Heapster and are in the root directory of the Heapster repository, and then run
$ kubectl create -f deploy/kube-config/influxdb/ $ kubectl create -f deploy/kube-config/rbac/heapster-rbac.yaml
Grafana service by default requests for a LoadBalancer. If that is not available in your cluster, consider changing that to NodePort. Use the external IP assigned to the Grafana service,
to access Grafana.
The default user name and password is 'admin'.
Once you login to Grafana, add a datasource that is InfluxDB. The URL for InfluxDB will be
http://INFLUXDB_HOST:INFLUXDB_PORT. Database name is 'k8s'. Default user name and password is 'root'.
Grafana documentation for InfluxDB here.
Take a look at the storage schema to understand how metrics are stored in InfluxDB.
Grafana is set up to auto-populate nodes and pods using templates.
The Grafana web interface can also be accessed via the api-server proxy. The URL should be visible in
kubectl cluster-info once the above resources are created.
See also the debugging documentation.
If the Grafana service is not accessible, it might not be running. Use
kubectlto verify that the
influxdb & grafanapods are alive.
$ kubectl get pods --namespace=kube-system ... monitoring-grafana-927606581-0tmdx 1/1 Running 0 6d monitoring-influxdb-3276295126-joqo2 1/1 Running 0 15d ... $ kubectl get services --namespace=kube-system monitoring-grafana monitoring-influxdb
If you find InfluxDB to be using up a lot of CPU or memory, consider placing resource restrictions on the
InfluxDB & Grafanapods. You can add
memory: <bytes>in the Controller Specs for InfluxDB and Grafana, and relaunch the controllers by running
kubectl apply -f deploy/kube-config/influxdb/and deleting the old influxdb pods.