Deploy Elasticsearch and Kibana in Azure Kubernetes Service using KubeDB


KubeDB is the Kubernetes Native Database Management Solution which simplifies and automates routine database tasks such as Provisioning, Monitoring, Upgrading, Patching, Scaling, Volume Expansion, Backup, Recovery, Failure detection, and Repair for various popular databases on private and public clouds. The databases that KubeDB supports are Elasticsearch, Kafka, MySQL, MongoDB, MariaDB, Redis, PostgreSQL, ProxySQL, Percona XtraDB, Memcached and PgBouncer. You can find the guides to all the supported databases in KubeDB . KubeDB provides support not only for the official Elasticsearch by Elastic and OpenSearch by AWS, but also other open source distributions like SearchGuard and OpenDistro . KubeDB provides all of these distribution’s support under the Elasticsearch CR of KubeDB. In this tutorial we will Deploy Elasticsearch and Kibana in Azure Kubernetes Service (AKS). We will cover the following steps:

  1. Install KubeDB
  2. Deploy Elasticsearch Topology Cluster
  3. Deploy Kibana
  4. Read/Write Data through Kibana

Get Cluster ID

We need the cluster ID to get the KubeDB License. To get cluster ID, we can run the following command:

$ kubectl get ns kube-system -o jsonpath='{.metadata.uid}'

Get License

Go to Appscode License Server to get the license.txt file. For this tutorial we will use KubeDB Enterprise Edition.

License Server

Install KubeDB

We will use helm to install KubeDB. Please install helm here if it is not already installed. Now, let’s install KubeDB.

$ helm repo add appscode
$ helm repo update

$ helm search repo appscode/kubedb
NAME                              	CHART VERSION	APP VERSION	DESCRIPTION                                       
appscode/kubedb                   	v2023.04.10  	v2023.04.10	KubeDB by AppsCode - Production ready databases...
appscode/kubedb-autoscaler        	v0.18.0      	v0.18.1    	KubeDB Autoscaler by AppsCode - Autoscale KubeD...
appscode/kubedb-catalog           	v2023.04.10  	v2023.04.10	KubeDB Catalog by AppsCode - Catalog for databa...
appscode/kubedb-community         	v0.24.2      	v0.24.2    	KubeDB Community by AppsCode - Community featur...
appscode/kubedb-crds              	v2023.04.10  	v2023.04.10	KubeDB Custom Resource Definitions                
appscode/kubedb-dashboard         	v0.9.0       	v0.9.1     	KubeDB Dashboard by AppsCode                      
appscode/kubedb-enterprise        	v0.11.2      	v0.11.2    	KubeDB Enterprise by AppsCode - Enterprise feat...
appscode/kubedb-grafana-dashboards	v2023.04.10  	v2023.04.10	A Helm chart for kubedb-grafana-dashboards by A...
appscode/kubedb-metrics           	v2023.04.10  	v2023.04.10	KubeDB State Metrics                              
appscode/kubedb-one               	v2023.04.10  	v2023.04.10	KubeDB and Stash by AppsCode - Production ready...
appscode/kubedb-ops-manager       	v0.20.0      	v0.20.1    	KubeDB Ops Manager by AppsCode - Enterprise fea...
appscode/kubedb-opscenter         	v2023.04.10  	v2023.04.10	KubeDB Opscenter by AppsCode                      
appscode/kubedb-provisioner       	v0.33.0      	v0.33.1    	KubeDB Provisioner by AppsCode - Community feat...
appscode/kubedb-schema-manager    	v0.9.0       	v0.9.1     	KubeDB Schema Manager by AppsCode                 
appscode/kubedb-ui                	v2023.03.23  	0.3.28     	A Helm chart for Kubernetes                       
appscode/kubedb-ui-server         	v2021.12.21  	v2021.12.21	A Helm chart for kubedb-ui-server by AppsCode     
appscode/kubedb-webhook-server    	v0.9.0       	v0.9.1     	KubeDB Webhook Server by AppsCode    

# Install KubeDB Enterprise operator chart
$ helm install kubedb appscode/kubedb \
  --version v2023.04.10 \
  --namespace kubedb --create-namespace \
  --set kubedb-provisioner.enabled=true \
  --set kubedb-ops-manager.enabled=true \
  --set kubedb-autoscaler.enabled=true \
  --set kubedb-dashboard.enabled=true \
  --set kubedb-schema-manager.enabled=true \
  --set-file global.license=/path/to/the/license.txt

Let’s verify the installation:

$ kubectl get pods --all-namespaces -l ""
NAMESPACE   NAME                                            READY   STATUS    RESTARTS   AGE
kubedb      kubedb-kubedb-autoscaler-56d655557f-g6gmt       1/1     Running   0          2m7s
kubedb      kubedb-kubedb-dashboard-7c867ffd67-s5rhn        1/1     Running   0          2m7s
kubedb      kubedb-kubedb-ops-manager-5cd864fdc8-lq6ft      1/1     Running   0          2m7s
kubedb      kubedb-kubedb-provisioner-86f7b7b7cf-flh86      1/1     Running   0          2m7s
kubedb      kubedb-kubedb-schema-manager-6c67df98db-4q9qx   1/1     Running   0          2m7s
kubedb      kubedb-kubedb-webhook-server-6dc774cd9f-pwrcv   1/1     Running   0          2m7s

We can list the CRD Groups that have been registered by the operator by running the following command:

$ kubectl get crd -l
NAME                                              CREATED AT   2023-05-19T08:56:17Z      2023-05-19T08:56:17Z                        2023-05-19T08:56:17Z           2023-05-19T08:56:21Z          2023-05-19T08:53:33Z                                  2023-05-19T08:56:19Z                   2023-05-19T08:53:34Z                                 2023-05-19T08:56:21Z                  2023-05-19T08:53:34Z         2023-05-19T08:56:17Z                2023-05-19T08:56:23Z                 2023-05-19T08:56:36Z                               2023-05-19T08:56:19Z                2023-05-19T08:53:34Z                             2023-05-19T08:56:19Z              2023-05-19T08:53:34Z         2023-05-19T08:56:17Z                2023-05-19T08:56:21Z                 2023-05-19T08:56:25Z                               2023-05-19T08:56:19Z                2023-05-19T08:53:35Z           2023-05-19T08:56:17Z                  2023-05-19T08:56:20Z                   2023-05-19T08:56:33Z                                 2023-05-19T08:56:20Z                  2023-05-19T08:53:35Z   2023-05-19T08:56:17Z           2023-05-19T08:56:50Z                         2023-05-19T08:56:20Z          2023-05-19T08:53:35Z                             2023-05-19T08:56:20Z              2023-05-19T08:53:36Z        2023-05-19T08:56:18Z               2023-05-19T08:56:23Z                             2023-05-19T08:56:20Z                2023-05-19T08:56:43Z               2023-05-19T08:53:36Z        2023-05-19T08:56:18Z                2023-05-19T08:56:46Z                              2023-05-19T08:56:21Z               2023-05-19T08:53:36Z                    2023-05-19T08:56:59Z           2023-05-19T08:56:18Z                                2023-05-19T08:56:21Z                   2023-05-19T08:56:39Z   2023-05-19T08:56:18Z           2023-05-19T08:56:53Z                         2023-05-19T08:56:21Z                  2023-05-19T08:53:37Z                   2023-05-19T08:57:03Z

Deploy Elasticsearch Topology Cluster

We are going to use the KubeDB-provided Custom Resource object Elasticsearch for deployment. The object will be deployed in demo namespace. So, let’s create the namespace first.

$ kubectl create namespace demo
namespace/demo created

Here is the yaml of Elasticsearch we are going to use:

kind: Elasticsearch
  name: es-cluster
  namespace: demo
  enableSSL: true 
  version: xpack-8.5.2 
  storageType: Durable
      replicas: 2
        storageClassName: "default"
        - ReadWriteOnce
            storage: 1Gi
      replicas: 2
        storageClassName: "default"
        - ReadWriteOnce
            storage: 1Gi
      replicas: 2
        storageClassName: "default"
        - ReadWriteOnce
            storage: 1Gi
  terminationPolicy: WipeOut


  • spec.version - is the name of the ElasticsearchVersion CR. Here, we are using Elasticsearch version xpack-8.5.2 of Elasticsearch distribution.
  • spec.enableSSL - specifies whether the HTTP layer is secured with certificates or not.
  • spec.storageType - specifies the type of storage that will be used for Elasticsearch database. It can be Durable or Ephemeral. The default value of this field is Durable. If Ephemeral is used then KubeDB will create the Elasticsearch database using EmptyDir volume. In this case, you don’t have to specify field. This is useful for testing purposes.
  • spec.topology - specifies the node-specific properties for the Elasticsearch cluster.
  • spec.terminationPolicy field is Wipeout means that the database will be deleted without restrictions. It can also be “Halt”, “Delete” and “DoNotTerminate”. Learn More about these checkout Termination Policy .

Let’s deploy the above yaml by the following command:

$ kubectl apply -f es-cluster.yaml created

However, KubeDB also provides dedicated node support for other node roles like data_hot, data_warm, data_cold, data_frozen, transform, coordinating, data_content and ml for Topology clustering .

Once these are handled correctly and the Elasticsearch object is deployed, you will see that the following resources are created:

$ kubectl get all -n demo
NAME                      READY   STATUS    RESTARTS   AGE
pod/es-cluster-data-0     1/1     Running   0          2m45s
pod/es-cluster-data-1     1/1     Running   0          2m2s
pod/es-cluster-ingest-0   1/1     Running   0          2m46s
pod/es-cluster-ingest-1   1/1     Running   0          85s
pod/es-cluster-master-0   1/1     Running   0          2m45s
pod/es-cluster-master-1   1/1     Running   0          2m3s

NAME                        TYPE        CLUSTER-IP    EXTERNAL-IP   PORT(S)    AGE
service/es-cluster          ClusterIP   <none>        9200/TCP   2m47s
service/es-cluster-master   ClusterIP   None          <none>        9300/TCP   2m47s
service/es-cluster-pods     ClusterIP   None          <none>        9200/TCP   2m47s

NAME                                 READY   AGE
statefulset.apps/es-cluster-data     2/2     2m48s
statefulset.apps/es-cluster-ingest   2/2     2m49s
statefulset.apps/es-cluster-master   2/2     2m48s

NAME                                            TYPE                       VERSION   AGE   8.5.2     2m50s

NAME                                  VERSION       STATUS   AGE   xpack-8.5.2   Ready    2m58s

We have successfully deployed Elasticsearch cluster in Azure.

Deploy Kibana

kind: ElasticsearchDashboard
  name: es-cluster-dashboard
  namespace: demo
  enableSSL: true
    name: es-cluster
  terminationPolicy: WipeOut

Note: Elasticsearch Database and Elasticsearch dashboard should have to be deployed in the same namespace. In this tutorial, we use demo namespace for both cases.

  • spec.enableSSL specifies whether the HTTP layer is secured with certificates or not.
  • refers to the Elasticsearch database name.
  • spec.terminationPolicy refers to the strategy to follow during dashboard deletion. Wipeout means that the database will be deleted without restrictions. It can also be DoNotTerminate which will cause a restriction to delete the dashboard. Learn More about these Termination Policy .

Let’s deploy the above yaml by the following command:

$ kubectl apply -f es-cluster-dashboard.yaml created

KubeDB will create the necessary resources to deploy the Elasticsearch dashboard according to the above specification. Let’s wait until the dashboard to be ready to use,

$ watch kubectl get elasticsearchdashboard -n demo
NAME                   TYPE                            DATABASE     STATUS   AGE
es-cluster-dashboard   es-cluster   Ready    61s

Here, Elasticsearch Dashboard is in Ready state.

Connect with Elasticsearch Dashboard

We will use port forwarding to connect with our Elasticsearch database. Then we will use curl to send HTTP requests to check cluster health to verify that our Elasticsearch database is working well.

Port-forward the Service

KubeDB will create few Services to connect with the database. Let’s check the Services by following command,

$ kubectl get service -n demo
NAME                   TYPE        CLUSTER-IP    EXTERNAL-IP   PORT(S)    AGE
es-cluster             ClusterIP   <none>        9200/TCP   8m32s
es-cluster-dashboard   ClusterIP   <none>        5601/TCP   79s
es-cluster-master      ClusterIP   None          <none>        9300/TCP   8m32s
es-cluster-pods        ClusterIP   None          <none>        9200/TCP   8m32s

Here, we are going to use es-cluster-dashboard Service to connect with the database. Now, let’s port-forward the es-cluster-dashboard Service to the port 5601 to local machine:

$ kubectl port-forward -n demo service/es-cluster-dashboard 5601
Forwarding from -> 5601
Forwarding from [::1]:5601 -> 5601

Now, our Elasticsearch cluster dashboard is accessible at https://localhost:5601.

Export the Credentials

KubeDB also create some Secrets for the database. Let’s check which Secrets have been created by KubeDB for our es-cluster.

$ kubectl get secret -n demo | grep es-cluster
es-cluster-apm-system-cred        2      11m
es-cluster-beats-system-cred      2      11m
es-cluster-ca-cert                       2      12m
es-cluster-client-cert                   3      11m
es-cluster-config                        Opaque                     1      11m
es-cluster-dashboard-ca-cert             2      4m47s
es-cluster-dashboard-config              Opaque                     2      4m47s
es-cluster-dashboard-server-cert          3      4m47s
es-cluster-elastic-cred           2      11m
es-cluster-http-cert                     3      11m
es-cluster-kibana-system-cred     2      11m
es-cluster-logstash-system-cred   2      11m
es-cluster-remote-monitoring-user-cred   2      11m
es-cluster-transport-cert                3      11m

Now, we can connect to the database with es-cluster-elastic-cred which contains the admin credentials to connect with the database.

Accessing Database Through Dashboard

To access the database through Dashboard, we have to get the credentials. We can do that by following command,

$ kubectl get secret -n demo es-cluster-elastic-cred -o jsonpath='{.data.username}' | base64 -d
$ kubectl get secret -n demo es-cluster-elastic-cred -o jsonpath='{.data.password}' | base64 -d

Now, let’s go to https://localhost:5601 from our browser and login by using those credentials.

Login Page

After login successfully, we will see Elasticsearch Dashboard UI. Now, We are going to Dev tools for running some queries into our Elasticsearch database.

Dashboard UI

Here, in Dev tools we will use Console section for running some queries. Let’s run GET / query to check node informations.


Get Query

Now, we are going to insert some sample data to our Elasticsearch cluster index music/_doc/1 by using PUT query.

PUT music/_doc/1
    "Playlist": {
      "Song": "Take Me Home Country Roads",
      "Artist": "John Denver",
      "Album": "Poems, Prayers & Promises"

Sample Data

Let’s check that sample data in the index music/_doc/1 by using GET query.

GET music/_doc/1

Get Data

Now, we are going to update sample data in the index music/_doc/1 by using POST query.

POST music/_doc/1
    "Playlist": {
      "Song": "Take Me Home Country Roads",
      "Artist": "John Denver",
      "Album": "Poems, Prayers & Promises",
      "Released": "April 6, 1971"

Post Data

Let’s verify the index music/_doc/1 again to see whether the data is updated or not.

GET music/_doc/1

Get Updated Data

We have made an in depth tutorial on Elasticsearch Hot Warm Cold Architecture Management with Kibana in Kubernetes Using KubeDB. You can have a look into the video below:


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More about Elasticsearch in Kubernetes

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