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Visualize MSSQLServer Metrics with Grafana Dashboard

KubeDB exposes MSSQLServer 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 MSSQLServer 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.

• MSSQLServer requires TLS to be enabled. You need a cert-manager Issuer in the demo namespace before deploying. If cert-manager is not installed, install it first:

  $ helm repo add jetstack https://charts.jetstack.io
  $ helm repo update
  $ helm upgrade --install cert-manager jetstack/cert-manager \
    --namespace cert-manager --create-namespace \
    --set crds.enabled=true
  

  Then create a self-signed Issuer in the demo namespace:

  apiVersion: cert-manager.io/v1
  kind: Issuer
  metadata:
    name: mssqlserver-ca-issuer
    namespace: demo
  spec:
    selfSigned: {}
  

  $ kubectl apply -f issuer.yaml
  issuer.cert-manager.io/mssqlserver-ca-issuer created
  

• 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/mssqlserver/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 MSSQLServer 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 MSSQLServer with Monitoring Enabled

Below is the MSSQLServer object with TLS and monitoring configured to use Prometheus Operator.

apiVersion: kubedb.com/v1alpha2
kind: MSSQLServer
metadata:
  name: mssql-grafana-demo
  namespace: demo
spec:
  version: "2022-cu12"
  replicas: 1
  tls:
    issuerRef:
      name: mssqlserver-ca-issuer
      kind: Issuer
      apiGroup: "cert-manager.io"
    clientTLS: false
  deletionPolicy: WipeOut
  storage:
    storageClassName: "standard"
    accessModes:
    - ReadWriteOnce
    resources:
      requests:
        storage: 1Gi
  monitor:
    agent: prometheus.io/operator
    prometheus:
      serviceMonitor:
        labels:
          release: prometheus
        interval: 10s

Here,

• tls.issuerRef is required for MSSQLServer; it references the cert-manager Issuer created above.
• 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 MSSQLServer instance:

$ kubectl create -f https://github.com/kubedb/docs/raw/v2026.6.19/docs/examples/mssqlserver/monitoring/mssql-grafana-demo.yaml
mssqlserver.kubedb.com/mssql-grafana-demo created

Wait for it to be Ready:

$ kubectl get mssqlserver -n demo mssql-grafana-demo
NAME                 VERSION    STATUS   AGE
mssql-grafana-demo   2022-cu12  Ready    3m

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

$ kubectl get svc -n demo --selector="app.kubernetes.io/instance=mssql-grafana-demo"
NAME                       TYPE        CLUSTER-IP     EXTERNAL-IP   PORT(S)     AGE
mssql-grafana-demo         ClusterIP   10.96.10.1     <none>        1433/TCP    3m
mssql-grafana-demo-stats   ClusterIP   10.96.10.2     <none>        9399/TCP    3m

KubeDB also creates a ServiceMonitor in the demo namespace:

$ kubectl get servicemonitor -n demo
NAME                       AGE
mssql-grafana-demo-stats   3m

Verify it carries the correct label:

$ kubectl get servicemonitor -n demo mssql-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 mssql-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 MSSQLServer Dashboard

The KubeDB MSSQLServer 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 (mssqlserver/ 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 / MSSQLServer / Summary — start here for an instance overview:

• General Info — database status, version, whether secure transport is required, 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 / MSSQLServer / Pod — drill into a specific pod:

• Pod Name / Status / Role / Uptime — pod identity, running status, Availability Group role (Primary/Secondary), and uptime
• Server Resource Overview — server local time, total and used RAM, pagefile size and usage
• Server Resource Overview (2) — total page faults, batch requests/sec, page life expectancy, deadlocks, user errors/sec, kill connection errors/sec
• Summary — current database connections, log growth since last restart, total I/O stall wait time

KubeDB / MSSQLServer / Database — Availability Group cluster health:

• Service Status / Uptime — per-pod health and how long each pod has been serving
• AG Cluster Active Replica — which pod is acting as the active replica
• Cluster Status — count of Primary vs. Secondary replicas
• SQL Compilations/sec — per-pod query compilation rate
• Batch Requests per Second — per-pod T-SQL batch throughput

Cleaning up

# Remove the MSSQLServer instance
kubectl delete mssqlserver -n demo mssql-grafana-demo

# Remove the TLS Issuer
kubectl delete issuer mssqlserver-ca-issuer -n 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 MSSQLServer instance with KubeDB using Prometheus Operator.
• Want to hack on KubeDB? Check our contribution guidelines.