Customize Elasticsearch

Learn how to customize your Elasticsearch cluster configuration

Verrazzano supports two cluster topologies for an Elasticsearch cluster:

  • A single-node cluster (master, ingest, and data roles performed by a single node).
  • A multi-node cluster configuration with separate master, data, and ingest nodes.

Installation Profiles describes the default Elasticsearch cluster configurations provided by Verrazzano.

You can customize the node characteristics of your Elasticsearch cluster by using the spec.components.elasticsearch.installArgs field in the Verrazzano custom resource. When installing Verrazzano, you can use this field to specify a list of Helm value overrides for the Elasticsearch configuration.

These Helm overrides let you to customize the following node characteristics:

  • Number of node replicas.
  • Memory request size per node.
  • Storage request size (data nodes only).

The following table lists the Helm values in the Verrazzano system chart related to Elasticsearch nodes.

Name Description
nodes.master.replicas Number of master node replicas.
nodes.master.requests.memory Memory request amount expressed as a Quantity.
nodes.ingest.replicas Number of ingest node replicas.
nodes.ingest.requests.memory Memory request amount expressed as a Quantity. Number of data node replicas. Memory request amount expressed as a Quantity. Storage request amount expressed as a Quantity.

The following example overrides the dev installation profile, Elasticsearch configuration (a single-node cluster with 1Gi of memory and ephemeral storage) to use a multi-node cluster with persistent storage:

kind: Verrazzano
  name: custom-es-example
  profile: dev
      - name: nodes.master.replicas
        value: "1"
      - name: nodes.master.requests.memory
        value: "1G"
      - name: nodes.ingest.replicas
        value: "1"
      - name: nodes.ingest.requests.memory
        value: "1G"
      - name:
        value: "3"
      - name:
        value: "1.5G"
      - name:
        value: "10Gi"

Listing the pods and persistent volumes in the verrazzano-system namespace for the previous configuration shows the expected nodes are running with the appropriate data volumes:

$ kubectl  get pvc,pod -n verrazzano-system

# Sample output
NAME                                                                STATUS   VOLUME                                     CAPACITY   ACCESS MODES   STORAGECLASS   AGE
persistentvolumeclaim/elasticsearch-master-vmi-system-es-master-0   Bound    pvc-8ffff457-4d72-4a72-89ba-2cdcb8eade38   10Gi       RWO            standard       6m51s
persistentvolumeclaim/vmi-system-es-data                            Bound    pvc-e32c2182-46ba-4789-b577-195874b3dd69   10Gi       RWO            standard       6m53s
persistentvolumeclaim/vmi-system-es-data-1                          Bound    pvc-67789196-d688-4d06-b074-77655a913552   10Gi       RWO            standard       6m53s
persistentvolumeclaim/vmi-system-es-data-2                          Bound    pvc-43e07e3e-0713-4ab1-ac3f-812069c35cbb   10Gi       RWO            standard       6m53s

NAME                                                   READY   STATUS    RESTARTS   AGE
pod/coherence-operator-6986d6cf95-6b58p                1/1     Running   2          7m3s
pod/fluentd-fn28c                                      2/2     Running   2          7m12s
pod/oam-kubernetes-runtime-679c6f6775-79tvm            1/1     Running   0          5m11s
pod/verrazzano-api-58c5f65c8-6zbpc                     2/2     Running   0          7m12s
pod/verrazzano-application-operator-5766b899fd-9fjhb   1/1     Running   0          4m55s
pod/verrazzano-console-6599854544-pw56c                2/2     Running   0          7m12s
pod/verrazzano-monitoring-operator-55877766d4-9ktvh    1/1     Running   0          7m12s
pod/verrazzano-operator-75b5cd49fc-68cm4               1/1     Running   0          7m12s
pod/vmi-system-es-data-0-5884cfb84d-hn8xg              2/2     Running   0          6m52s
pod/vmi-system-es-data-1-679775494f-pdwzf              2/2     Running   0          6m52s
pod/vmi-system-es-data-2-5886d745c5-6pscm              2/2     Running   0          6m52s
pod/vmi-system-es-ingest-795749ddd8-cs4pc              3/3     Running   0          6m52s
pod/vmi-system-es-master-0                             2/2     Running   0          6m51s
pod/vmi-system-grafana-b94fcbb67-ktwf8                 3/3     Running   0          6m52s
pod/vmi-system-kibana-6594cfccc-j8gp5                  3/3     Running   0          6m51s
pod/vmi-system-prometheus-0-75864fc668-s5xv8           4/4     Running   0          44s
pod/weblogic-operator-5bd7bb6fb5-wz5cr                 2/2     Running   0          6m30s

Note that the master node uses the same amount of persistent storage as is configured for the data nodes.

Running the command kubectl describe pod -n verrazzano-system vmi-system-es-data-0-5884cfb84d-hn8xg shows the requested amount of memory:

    Container ID:  containerd://cc01f24b107da0e1e90a05a49c7fd969761f59a81316fa01f7cc56a166684628
    Image ID:
    Ports:         9200/TCP, 9300/TCP
    Host Ports:    0/TCP, 0/TCP
    State:          Running
      Started:      Thu, 29 Jul 2021 06:04:17 +0000
    Ready:          True
    Restart Count:  0
      memory:   1500M