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Visualize RabbitMQ Metrics with Grafana Dashboard

KubeDB exposes RabbitMQ metrics through a built-in Prometheus plugin. Once Prometheus scrapes those metrics, you can visualize them in Grafana using a pre-built KubeDB dashboard. This tutorial walks through the full setup: deploying the monitoring stack, enabling monitoring on a RabbitMQ instance, and importing the Grafana dashboard.

Before You Begin

• You need a Kubernetes cluster with kubectl configured. If you do not already have a cluster, you can create one by using kind.

• KubeDB must be installed in your cluster with kubedb-metrics enabled. Follow the setup guide here and make sure to include the flag below during installation:

  --set kubedb-metrics.enabled=true
  

  kubedb-metrics creates MetricsConfiguration objects for each database type, which Panopticon (Step 2) uses to expose metrics to Prometheus.

• To keep monitoring resources isolated, we use a separate monitoring namespace and deploy the database in the demo namespace.

  $ kubectl create ns monitoring
  namespace/monitoring created
  
  $ kubectl create ns demo
  namespace/demo created
  

Note: YAML files used in this tutorial are stored in docs/examples/rabbitmq/monitoring folder in GitHub repository kubedb/docs.

Configuration

These two steps — deploying kube-prometheus-stack and installing Panopticon — are shared prerequisites for all KubeDB database monitoring guides. If you have already completed them in another guide, skip to Step 1.

Step 1: Deploy kube-prometheus-stack

kube-prometheus-stack installs Prometheus, Prometheus Operator, Alertmanager, and Grafana together. This is the recommended way to get the full monitoring stack on Kubernetes.

Add the prometheus-community Helm repo and install:

$ helm repo add prometheus-community https://prometheus-community.github.io/helm-charts
$ helm repo update

$ helm upgrade --install prometheus prometheus-community/kube-prometheus-stack \
  --namespace monitoring \
  --set grafana.image.tag=7.5.5

Wait for all pods to be ready:

$ kubectl get pods -n monitoring
NAME                                                   READY   STATUS    RESTARTS   AGE
alertmanager-prometheus-kube-prometheus-alertmanager-0 2/2     Running   0          2m
prometheus-grafana-xxxx                                3/3     Running   0          2m
prometheus-kube-prometheus-operator-xxxx               1/1     Running   0          2m
prometheus-kube-prometheus-prometheus-0                2/2     Running   0          2m
prometheus-kube-state-metrics-xxxx                     1/1     Running   0          2m

Find the serviceMonitorSelector label that Prometheus uses to pick up ServiceMonitor objects. You will need this label when enabling monitoring on the RabbitMQ instance.

$ kubectl get prometheus -n monitoring -o jsonpath='{.items[0].spec.serviceMonitorSelector}'
{"matchLabels":{"release":"prometheus"}}

The label is release: prometheus.

Step 2: Install Panopticon

Panopticon is the Appscode operator that reads MetricsConfiguration objects created by kubedb-metrics and exposes them to Prometheus. It must be installed before enabling kubedb-metrics.

$ helm repo add appscode https://charts.appscode.com/stable/
$ helm repo update

$ helm upgrade --install panopticon appscode/panopticon \
  --version v2026.4.30 \
  --namespace kubeops --create-namespace \
  --set monitoring.enabled=true \
  --set monitoring.agent=prometheus.io/operator \
  --set monitoring.serviceMonitor.labels.release=prometheus \
  --set-file license=/path/to/kubedb-license.txt \
  --wait --timeout 5m0s

Verify panopticon is running:

$ kubectl get pods -n kubeops
NAME                          READY   STATUS    RESTARTS   AGE
panopticon-xxxx               1/1     Running   0          1m

Setup

Step 1: Deploy RabbitMQ with Monitoring Enabled

Below is the RabbitMQ object with monitoring configured to use Prometheus Operator.

apiVersion: kubedb.com/v1alpha2
kind: RabbitMQ
metadata:
  name: rmq-grafana-demo
  namespace: demo
spec:
  version: "4.0.4"
  replicas: 1
  deletionPolicy: WipeOut
  storage:
    storageClassName: "standard"
    accessModes:
    - ReadWriteOnce
    resources:
      requests:
        storage: 1Gi
  monitor:
    agent: prometheus.io/operator
    prometheus:
      serviceMonitor:
        labels:
          release: prometheus
        interval: 10s

Here,

• monitor.agent: prometheus.io/operator tells KubeDB to create a ServiceMonitor for this instance.
• monitor.prometheus.serviceMonitor.labels must match the serviceMonitorSelector label of your Prometheus (release: prometheus).
• monitor.prometheus.serviceMonitor.interval sets the scrape interval to 10 seconds.

Create the RabbitMQ instance:

$ kubectl create -f https://github.com/kubedb/docs/raw/v2026.6.19/docs/examples/rabbitmq/monitoring/coreos-prom-rabbitmq.yaml
rabbitmq.kubedb.com/rmq-grafana-demo created

Wait for it to be Ready:

$ kubectl get rabbitmq -n demo rmq-grafana-demo
NAME               VERSION   STATUS   AGE
rmq-grafana-demo   4.0.4     Ready    2m

KubeDB creates a stats service named {rabbitmq-name}-stats for monitoring:

$ kubectl get svc -n demo --selector="app.kubernetes.io/instance=rmq-grafana-demo"
NAME                     TYPE        CLUSTER-IP     EXTERNAL-IP   PORT(S)      AGE
rmq-grafana-demo         ClusterIP   10.96.10.1     <none>        5672/TCP     2m
rmq-grafana-demo-stats   ClusterIP   10.96.10.2     <none>        15692/TCP    2m

KubeDB also creates a ServiceMonitor in the demo namespace:

$ kubectl get servicemonitor -n demo
NAME                     AGE
rmq-grafana-demo-stats   2m

Verify it carries the correct label:

$ kubectl get servicemonitor -n demo rmq-grafana-demo-stats -o jsonpath='{.metadata.labels}'
{"release":"prometheus", ...}

Step 2: Verify Prometheus is Scraping

Port-forward the Prometheus pod:

$ kubectl port-forward -n monitoring \
  prometheus-prometheus-kube-prometheus-prometheus-0 9090
Forwarding from 127.0.0.1:9090 -> 9090
Forwarding from [::1]:9090 -> 9090

Open http://localhost:9090/targets in your browser. Look for an entry whose service label matches rmq-grafana-demo-stats. Its state should be UP.

If the target is missing, check that the ServiceMonitor label (release: prometheus) matches the Prometheus serviceMonitorSelector.

Step 3: Access Grafana

Port-forward the Grafana service:

$ kubectl port-forward -n monitoring svc/prometheus-grafana 3000:80
Forwarding from 127.0.0.1:3000 -> 80

Open http://localhost:3000. The username is admin. Retrieve the auto-generated password from the secret:

$ kubectl get secret -n monitoring prometheus-grafana \
  -o jsonpath='{.data.admin-password}' | base64 -d

After a successful login you will see the Grafana home page:

Step 4: Configure Prometheus as a Data Source

If you installed Grafana via kube-prometheus-stack, Prometheus is already configured as the default data source — skip to Step 5.

For a standalone Grafana installation:

1. Go to Connections → Data sources → Add new data source.

2. Select Prometheus.

3. Set the URL to your Prometheus service:

   http://prometheus-operated.monitoring.svc:9090
   

4. Click Save & test. You should see Data source is working.

Step 5: Import KubeDB RabbitMQ Dashboard

The KubeDB RabbitMQ dashboards are distributed as JSON files. Each JSON file is a complete dashboard definition — panels, queries, variables, and layout — that Grafana loads in one shot. Without importing, you would have to build every panel and write every PromQL query by hand. Importing lets you skip that entirely.

Three dashboards are available. Download all three JSON files from the appscode/grafana-dashboards repository (rabbitmq/ folder):

Import steps (repeat for each of the three files):

1. In Grafana, click the + icon in the left sidebar.
2. Select Import from the menu.
3. Click Upload JSON file and select one of the downloaded .json files.
4. In the Prometheus dropdown that appears, select your Prometheus data source.
5. Click Import.

The import page looks like this — click Upload dashboard JSON file to select the file:

After importing all three files, they will appear under Dashboards in the left sidebar.

Step 6: Explore the Dashboard

After opening a dashboard, use the dropdown filters at the top to focus on a specific instance.

KubeDB / RabbitMQ / Summary — start here for a node and cluster overview:

• Node Health — running/stopped/disk alarm/memory alarm status per node
• Queue Count — total queues in the cluster
• Message Rates — publish rate, deliver rate, acknowledge rate
• Messages Ready / Unacknowledged — total backlog depth
• Connection / Channel Count — active connections and open channels
• CPU / Memory / Disk Free — resource consumption per node

KubeDB / RabbitMQ / Pod — drill into a specific node:

• Erlang Process Count — number of Erlang processes (high counts indicate load)
• Memory Breakdown — code, heap, binaries, ETS table memory
• Socket Descriptors — used vs. available file descriptors for connections
• GC — garbage collection runs and bytes reclaimed per second
• CPU / Memory — per-pod resource usage over time

KubeDB / RabbitMQ / Database — per-queue and per-vhost metrics:

• Queue Depth — messages ready + unacknowledged per queue
• Publish / Deliver Rate — throughput per queue
• Consumer Count — active consumers per queue
• Oldest Unacknowledged Message — age of the oldest pending message (latency indicator)

Cleaning up

# Remove the RabbitMQ instance
kubectl delete rabbitmq -n demo rmq-grafana-demo

# Remove namespaces
kubectl delete ns demo

# Uninstall monitoring stack (optional)
helm uninstall prometheus -n monitoring
helm uninstall panopticon -n kubeops
kubectl delete ns monitoring kubeops

Next Steps

• Monitor your RabbitMQ instance with KubeDB using built-in Prometheus.
• Monitor your RabbitMQ instance with KubeDB using Prometheus Operator.
• Want to hack on KubeDB? Check our contribution guidelines.