Elasticsearch Monitoring with Prometheus Operator

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

1. Prometheus Operator for metrics collection
2. Built-in Elasticsearch 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 Elasticsearch Cluster

KubeBlocks uses a declarative approach for managing Elasticsearch Clusters. Below is an example configuration for deploying a Elasticsearch Cluster with create a cluster with replicas for different roles.

Apply the following YAML configuration to deploy the cluster:

apiVersion: apps.kubeblocks.io/v1
kind: Cluster
metadata:
  name: es-multinode
  namespace: demo
spec:
  terminationPolicy: Delete
  componentSpecs:
    - name: dit
      componentDef: elasticsearch-8
      serviceVersion: 8.8.2
      configs:
        - name: es-cm
          variables:
            # use key `roles` to specify roles this component assume
            roles: data,ingest,transform
      replicas: 3
      disableExporter: false
      resources:
        limits:
          cpu: "1"
          memory: "2Gi"
        requests:
          cpu: "1"
          memory: "2Gi"
      volumeClaimTemplates:
        - name: data
          spec:
            accessModes:
              - ReadWriteOnce
            resources:
              requests:
                storage: 20Gi
    - name: master
      componentDef: elasticsearch-8
      serviceVersion: 8.8.2
      configs:
        - name: es-cm
          variables:
            # use key `roles` to specify roles this component assume
            roles: master
      replicas: 3
      disableExporter: false
      resources:
        limits:
          cpu: "1"
          memory: "2Gi"
        requests:
          cpu: "1"
          memory: "2Gi"
      volumeClaimTemplates:
        - name: data
          spec:
            accessModes:
              - ReadWriteOnce
            resources:
              requests:
                storage: 20Gi

Verifying the Deployment

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

kubectl get cluster es-multinode -n demo -w

Expected Output:

NAME           CLUSTER-DEFINITION   TERMINATION-POLICY   STATUS     AGE
es-multinode                        Delete               Creating   10s
es-multinode                        Delete               Updating   41s
es-multinode                        Delete               Running    42s

Check the pod status and roles:

kubectl get pods -l app.kubernetes.io/instance=es-multinode -n demo

Expected Output:

NAME                    READY   STATUS    RESTARTS   AGE
es-multinode-dit-0      3/3     Running   0          6m21s
es-multinode-dit-1      3/3     Running   0          6m21s
es-multinode-dit-2      3/3     Running   0          6m21s
es-multinode-master-0   3/3     Running   0          6m21s
es-multinode-master-1   3/3     Running   0          6m21s
es-multinode-master-2   3/3     Running   0          6m21s

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

Configure Metrics Collection

1. Verify Exporter Endpoint

kubectl -n demo exec -it pods/es-multinode-dit-0 -- \
  curl -s http://127.0.0.1:9114/metrics | head -n 50

kubectl -n demo exec -it pods/es-multinode-master-0 -- \
  curl -s http://127.0.0.1:9114/metrics | head -n 50

2. Create PodMonitor

apiVersion: monitoring.coreos.com/v1
kind: PodMonitor
metadata:
  name: elasticsearch-jmx-pod-monitor
  namespace: demo
  labels:               # match labels in `prometheus.spec.podMonitorSelector`
    release: prometheus
spec:
  jobLabel: app.kubernetes.io/managed-by
  podMetricsEndpoints:
    - path: /metrics
      port: metrics
      scheme: http
  namespaceSelector:
    matchNames:
      - demo
  selector:
    matchLabels:
      app.kubernetes.io/instance: es-multinode

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/es-multinode-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=elasticsearch_clusterinfo_up{job="kubeblocks"}' | jq

Example Output:

{
  "status": "success",
  "data": {
    "resultType": "vector",
    "result": [
      {
        "metric": {
          "__name__": "elasticsearch_clusterinfo_up",
          "container": "exporter",
          "endpoint": "metrics",
          "instance": "10.244.0.49:9114",
          "job": "kubeblocks",
          "namespace": "demo",
          "pod": "es-multinode-master-2",
          "url": "http://localhost:9200"
        },
        "value": [
          1747666760.443,
          "1"
        ]
      },
... // more lines ommited

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 Elasticsearch dashboard:

1. In Grafana, navigate to "+" → "Import"
2. Import dashboard from Elasticsearch Dashboard

Figure 1. Elasticsearch dashboard

Delete

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

kubectl delete cluster es-multinode -n demo
kubectl delete ns demo
kubectl delete podmonitor es-multinode-pod-monitor -n demo

Summary

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