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Visualize Redis Metrics with Grafana Dashboard

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

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/redis/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 Redis 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 Redis with Monitoring Enabled

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

apiVersion: kubedb.com/v1
kind: Redis
metadata:
  name: redis-cluster
  namespace: demo
spec:
  version: 8.2.2
  mode: Cluster
  cluster:
    shards: 3
    replicas: 2
  storageType: Durable
  storage:
    resources:
      requests:
        storage: 1Gi
    storageClassName: local-path
    accessModes:
    - ReadWriteOnce
  deletionPolicy: WipeOut
  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 Redis instance:

$ kubectl create -f https://github.com/kubedb/docs/raw/v2026.6.19/docs/examples/redis/monitoring/redis-cluster.yaml
redis.kubedb.com/redis-cluster created

Wait for it to be Ready:

$ kubectl get redis -n demo redis-cluster
NAME            VERSION   STATUS   AGE
redis-cluster   8.2.2     Ready    5m

KubeDB creates a stats service named {redis-name}-stats for the exporter:

$ kubectl get svc -n demo --selector="app.kubernetes.io/instance=redis-cluster"
NAME                  TYPE        CLUSTER-IP     EXTERNAL-IP   PORT(S)     AGE
redis-cluster         ClusterIP   10.96.10.1     <none>        6379/TCP    5m
redis-cluster-stats   ClusterIP   10.96.10.2     <none>        56790/TCP   5m

KubeDB also creates a ServiceMonitor in the demo namespace:

$ kubectl get servicemonitor -n demo
NAME                  AGE
redis-cluster-stats   5m

Verify it carries the correct label:

$ kubectl get servicemonitor -n demo redis-cluster-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 redis-cluster-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 Redis Dashboard

The KubeDB Redis 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 the JSON files from the opnpulse/dashboards repository (redis/ folder):

The Shard dashboard is relevant for Redis Cluster mode (spec.mode: Cluster); its panels stay empty for a standalone (non-cluster) Redis instance.

Import steps (repeat for each file you need):

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 the files you need, 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 / Redis / Summary — start here for an instance overview:

• General Info — database status, version, max clients, Redis mode, deletion policy, total nodes
• Resource Requests / Limits — configured CPU, memory, and storage requests and limits
• CPU Info / CPU Quota — per-pod CPU usage over time and quota utilization

KubeDB / Redis / Pod — drill into a specific pod:

• General Counters And File Descriptor Stats — status, role (master/slave), my master, my slaves, connected clients, Go routines
• Uptime / Memory Usage / Commands Executed / Hits-Misses — pod uptime, memory usage, command execution rate, cache hit/miss rate
• Network I/O / Command Calls / Connected Clients — network throughput, per-command call breakdown, connected client count over time
• CPU And Memory Usage Stats — total memory usage, average CPU usage, average memory usage

KubeDB / Redis / Shard — cluster shard health for Cluster mode:

• Cluster Shard Slots / Cluster Shard Slots Failed — hash slot coverage and any failed slots
• Cluster Nodes / Cluster Masters — total nodes and master count in the cluster
• Connected Slaves / My Slaves — number of connected slaves and their IP, port, and online status
• Mode — confirms the instance is running in cluster mode

Cleaning up

# Remove the Redis instance
kubectl delete redis -n demo redis-cluster

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