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1. Edit the values.yaml file of the HiveMQ operator and enable the deployment of the HiveMQ Prometheus Monitoring Extension along with the deployment of the HiveMQ operator.
   When the monitoring.enabled key in the values.yaml then each HiveMQ pod will have the HiveMQ Monitoring Extension installed and enabled. The operator will also create a hivemq-...-metrics service and expose its endpoint by default on port 9399. This makes HiveMQ broker metrics ready for scraping by the Prometheus application.

   Code Block
   language yaml
   monitoring: # Deploy ServiceMonitor for Prometheus Operator and enable Prometheus enabled: true # Deploy a dedicated instance of the prometheus operator, including grafana, as sub-chart dedicated: false

2. Install HiveMQ with the release name "hivemq" from the Helm chart hivemq-operator to the namespace hivemq and use parameter values from the file values.yaml

   Code Block
   language bash
   helm upgrade "hivemq" \ --install hivemq/hivemq-operator \ --namespace hivemq \ --values values.yaml

3. This should create, Make sure that alongside the HiveMQ cluster, a the Kubernetes Service hivemq-metrics was created:

   Code Block
   language bash
   kubectl get services | head -n 1 && kubectl get services--namespace 'hivemq' | grep 'metrics'

   Code Block
   language text
   NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE hivemq-hivemq-metrics ClusterIP 10.96.207.165 <none> 9399/TCP 2m31s

4. Install Prometheus on your own and configure it to scrape from the hivemq:9399/metrics.

5. Install Grafana on your own and configure it to use the Prometheus Datasource and the HiveMQ Cluster Dashboard.

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