RabbitMQ Monitoring with Prometheus Operator

This guide demonstrates how to configure comprehensive monitoring for RabbitMQ clusters in KubeBlocks using:

1. Prometheus Operator for metrics collection
2. Built-in RabbitMQ exporter for metrics exposure
3. Grafana for visualization

Prerequisites

Before proceeding, ensure the following:

• Environment Setup:
  • A Kubernetes cluster is up and running.
  • The kubectl CLI tool is configured to communicate with your cluster.
  • KubeBlocks CLI and KubeBlocks Operator are installed. Follow the installation instructions here.
• Namespace Preparation: To keep resources isolated, create a dedicated namespace for this tutorial:

kubectl create ns demo
namespace/demo created

Install Monitoring Stack

1. Install Prometheus Operator

Deploy the kube-prometheus-stack using Helm:

helm repo add prometheus-community https://prometheus-community.github.io/helm-charts
helm install prometheus prometheus-community/kube-prometheus-stack \
  -n monitoring \
  --create-namespace

2. Verify Installation

Check all components are running:

kubectl get pods -n monitoring

Expected Output:

NAME                                                     READY   STATUS    RESTARTS   AGE
alertmanager-prometheus-kube-prometheus-alertmanager-0   2/2     Running   0          114s
prometheus-grafana-75bb7d6986-9zfkx                      3/3     Running   0          2m
prometheus-kube-prometheus-operator-7986c9475-wkvlk      1/1     Running   0          2m
prometheus-kube-state-metrics-645c667b6-2s4qx            1/1     Running   0          2m
prometheus-prometheus-kube-prometheus-prometheus-0       2/2     Running   0          114s
prometheus-prometheus-node-exporter-47kf6                1/1     Running   0          2m1s
prometheus-prometheus-node-exporter-6ntsl                1/1     Running   0          2m1s
prometheus-prometheus-node-exporter-gvtxs                1/1     Running   0          2m1s
prometheus-prometheus-node-exporter-jmxg8                1/1     Running   0          2m1s

Deploy a RabbitMQ Cluster

KubeBlocks uses a declarative approach for managing RabbitMQ Clusters. Below is an example configuration for deploying a RabbitMQ Cluster with 3 replicas.

Apply the following YAML configuration to deploy the cluster:

apiVersion: apps.kubeblocks.io/v1
kind: Cluster
metadata:
  name: rabbitmq-cluster
  namespace: demo
spec:
  terminationPolicy: Delete
  clusterDef: rabbitmq
  topology: clustermode
  componentSpecs:
    - name: rabbitmq
      serviceVersion: 3.13.7
      replicas: 3
      resources:
        limits:
          cpu: "0.5"
          memory: "0.5Gi"
        requests:
          cpu: "0.5"
          memory: "0.5Gi"
      volumeClaimTemplates:
        - name: data
          spec:
            storageClassName: ""
            accessModes:
              - ReadWriteOnce
            resources:
              requests:
                storage: 20Gi

Verifying the Deployment

Monitor the cluster status until it transitions to the Running state:

kubectl get cluster rabbitmq-cluster -n demo -w

Expected Output:

kubectl get cluster rabbitmq-cluster -n demo
NAME               CLUSTER-DEFINITION   TERMINATION-POLICY   STATUS     AGE
rabbitmq-cluster   rabbitmq             Delete               Creating   15s
rabbitmq-cluster   rabbitmq             Delete               Running    83s

Check the pod status and roles:

kubectl get pods -l app.kubernetes.io/instance=rabbitmq-cluster -n demo

Expected Output:

NAME                          READY   STATUS    RESTARTS   AGE
rabbitmq-cluster-rabbitmq-0   2/2     Running   0          106s
rabbitmq-cluster-rabbitmq-1   2/2     Running   0          82s
rabbitmq-cluster-rabbitmq-2   2/2     Running   0          47s

Once the cluster status becomes Running, your RabbitMQ cluster is ready for use.

Configure Metrics Collection

1. Verify Exporter Endpoint

# prot-forward
kubectl -n demo port-forward pods/rabbitmq-cluster-rabbitmq-0  15692:15692
# check metrics
curl -s http://127.0.0.1:15692/metrics | head -n 50

2. Create PodMonitor

apiVersion: monitoring.coreos.com/v1
kind: PodMonitor
metadata:
  name: rabbitmq-cluster-pod-monitor
  namespace: demo
  labels:               # Must match the setting in 'prometheus.spec.podMonitorSelector'
    release: prometheus
spec:
  jobLabel: app.kubernetes.io/managed-by
  # defines the labels which are transferred from the
  # associated Kubernetes 'Pod' object onto the ingested metrics
  # set the lables w.r.t you own needs
  podTargetLabels:
  - app.kubernetes.io/instance
  - app.kubernetes.io/managed-by
  - apps.kubeblocks.io/component-name
  - apps.kubeblocks.io/pod-name
  podMetricsEndpoints:
    - path: /metrics
      port: prometheus   # Must match exporter port name
      scheme: http
  namespaceSelector:
    matchNames:
      - demo               # Target namespace
  selector:
    matchLabels:
      app.kubernetes.io/instance: rabbitmq-cluster

PodMonitor Configuration Guide

Verify Monitoring Setup

1. Check Prometheus Targets

Forward and access Prometheus UI:

kubectl port-forward svc/prometheus-kube-prometheus-prometheus -n monitoring 9090:9090

Open your browser and navigate to: http://localhost:9090/targets

Check if there is a scrape job corresponding to the PodMonitor (the job name is 'demo/rabbitmq-cluster-pod-monitor').

Expected State:

• The State of the target should be UP.
• The target's labels should include the ones defined in podTargetLabels (e.g., 'app_kubernetes_io_instance').

2. Test Metrics Collection

Verify metrics are being scraped:

curl -sG "http://localhost:9090/api/v1/query" --data-urlencode 'query=up{app_kubernetes_io_instance="rabbitmq-cluster"}' | jq

Example Output:

{
  "status": "success",
  "data": {
    "resultType": "vector",
    "result": [
      {
        "metric": {
          "__name__": "up",
          "app_kubernetes_io_instance": "rabbitmq-cluster",
          "app_kubernetes_io_managed_by": "kubeblocks",
          "apps_kubeblocks_io_component_name": "rabbitmq",
          "apps_kubeblocks_io_pod_name": "rabbitmq-cluster-rabbitmq-0",
          "container": "rabbitmq",
          "endpoint": "prometheus",
          "instance": "10.244.0.78:15692",
          "job": "kubeblocks",
          "namespace": "demo",
          "pod": "rabbitmq-cluster-rabbitmq-0"
        },
        "value": [
          1747622160.396,
          "1"
        ]
      },
      {
        "metric": {
          "__name__": "up",
          "app_kubernetes_io_instance": "rabbitmq-cluster",
          "app_kubernetes_io_managed_by": "kubeblocks",
          "apps_kubeblocks_io_component_name": "rabbitmq",
          "apps_kubeblocks_io_pod_name": "rabbitmq-cluster-rabbitmq-1",
          "container": "rabbitmq",
          "endpoint": "prometheus",
          "instance": "10.244.0.80:15692",
          "job": "kubeblocks",
          "namespace": "demo",
          "pod": "rabbitmq-cluster-rabbitmq-1"
        },
        "value": [
          1747622160.396,
          "1"
        ]
      }
    ]
  }
}

Visualize in Grafana

1. Access Grafana

Port-forward and login:

kubectl port-forward svc/prometheus-grafana -n monitoring 3000:80

Open your browser and navigate to http://localhost:3000. Use the default credentials to log in:

• Username: 'admin'
• Password: 'prom-operator' (default)

2. Import Dashboard

Import the KubeBlocks RabbitMQ dashboard:

1. In Grafana, navigate to "+" → "Import"
2. Import dashboard from Grafana RabbitMQ-Overview.

Delete

To delete all the created resources, run the following commands:

kubectl delete cluster rabbitmq-cluster -n demo
kubectl delete ns demo
kubectl delete podmonitor rabbitmq-cluster-pod-monitor -n demo

Summary

In this tutorial, we set up observability for a RabbitMQ cluster in KubeBlocks using the Prometheus Operator. By configuring a PodMonitor, we enabled Prometheus to scrape metrics from the RabbitMQ exporter. Finally, we visualized these metrics in Grafana. This setup provides valuable insights for monitoring the health and performance of your RabbitMQ databases.