OpenSearch

Learn how to customize your OpenSearch cluster configuration

Verrazzano supports two cluster topologies for an OpenSearch 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 OpenSearch cluster configurations provided by Verrazzano.

Configure cluster topology

You can customize the node characteristics of your OpenSearch cluster by using the spec.components.opensearch.nodes field in the Verrazzano custom resource. When installing or upgrading Verrazzano, you can use this field to define an OpenSearch cluster using node groups.

The following example overrides the dev installation profile, OpenSearch configuration (a single-node cluster with 1Gi of memory and ephemeral storage) to use a multi-node cluster (three master nodes, and three combination data/ingest nodes) with persistent storage.

apiVersion: install.verrazzano.io/v1beta1
kind: Verrazzano
metadata:
  name: custom-opensearch-example
spec:
  profile: dev
  components:
    opensearch:
      nodes:
        - name: master
          replicas: 3
          roles:
            - master
          storage:
            size: 50Gi
          resources:
            requests:
              memory: 1.5Gi
        - name: data-ingest
          replicas: 3
          roles:
            - data
            - ingest
          storage:
            size: 100Gi
          resources:
            requests:
              memory: 1Gi
        # Override the default node groups because we are providing our own topology.
        - name: es-master
          replicas: 0
        - name: es-data
          replicas: 0
        - name: es-ingest
          replicas: 0

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 -l verrazzano-component=opensearch -n verrazzano-system

# Sample output
NAME                                                             STATUS   VOLUME                                     CAPACITY   ACCESS MODES   STORAGECLASS   AGE
persistentvolumeclaim/elasticsearch-master-vmi-system-master-0   Bound    pvc-9ace042a-dd68-4975-816d-f2ca0dc4d9d8   50Gi       RWO            standard       5m22s
persistentvolumeclaim/elasticsearch-master-vmi-system-master-1   Bound    pvc-8bf68c2c-235e-4bd5-8741-5a5cd3453934   50Gi       RWO            standard       5m21s
persistentvolumeclaim/elasticsearch-master-vmi-system-master-2   Bound    pvc-da8a48b1-5762-4669-98f0-8479f30043fc   50Gi       RWO            standard       5m21s
persistentvolumeclaim/vmi-system-data-ingest                     Bound    pvc-7ad9f275-632b-4aac-b7bf-c5115215937c   100Gi      RWO            standard       5m23s
persistentvolumeclaim/vmi-system-data-ingest-1                   Bound    pvc-8a293e51-2c20-4cae-916b-1ce46a780403   100Gi      RWO            standard       5m23s
persistentvolumeclaim/vmi-system-data-ingest-2                   Bound    pvc-0025fcef-1d8c-4307-977c-3921545c6730   100Gi      RWO            standard       5m22s

NAME                                                   READY   STATUS     RESTARTS   AGE
pod/coherence-operator-6ffb6bbd4d-bpssc                1/1     Running    1          8m2s
pod/fluentd-ndshl                                      2/2     Running    0          5m51s
pod/oam-kubernetes-runtime-85cfd899d8-z9gv6            1/1     Running    0          8m14s
pod/verrazzano-application-operator-5fbcdf6655-72tw9   1/1     Running    0          7m49s
pod/verrazzano-authproxy-5f9d479455-5bvvt              2/2     Running    0          7m43s
pod/verrazzano-console-5b857d7b47-djbrk                2/2     Running    0          5m51s
pod/verrazzano-monitoring-operator-b4b446567-pgnfw     2/2     Running    0          5m51s
pod/vmi-system-data-ingest-0-5485dcd95d-rkhvk          2/2     Running    0          5m21s
pod/vmi-system-data-ingest-1-8d7db6489-kdhbv           2/2     Running    1          5m21s
pod/vmi-system-data-ingest-2-699d6bdd9c-z7nzx          2/2     Running    0          5m21s
pod/vmi-system-grafana-7947cdd84b-b7mks                2/2     Running    0          5m21s
pod/vmi-system-kiali-6c7bd6658b-d2zq9                  2/2     Running    0          5m37s
pod/vmi-system-kibana-7d47f65dfc-zhjxp                 2/2     Running    0          5m21s
pod/vmi-system-master-0                                2/2     Running    0          5m21s
pod/vmi-system-master-1                                2/2     Running    0          5m21s
pod/vmi-system-master-2                                2/2     Running    0          5m21s
pod/weblogic-operator-666b548749-lj66t                 2/2     Running    0          7m48s

Running the command kubectl describe pod -n verrazzano-system vmi-system-data-ingest-0-5485dcd95d-rkhvk shows the requested amount of memory.

Containers:
  es-data:
    ...
    Requests:
      memory:   1Gi

Configure Index State Management policies

Index State Management policies configure OpenSearch to manage the data in your indices. Policies can be used to automatically rollover and prune old data, preventing your OpenSearch cluster from running out of disk space.

The following policy example configures OpenSearch to manage indices matching the pattern my-app-*. The data in these indices will be automatically pruned every 14 days, and will be rolled over if an index meets at least one of the following criteria:

Is three or more days old
Contains 1,000 documents or more
Is 10 GB in size or larger

apiVersion: install.verrazzano.io/v1beta1
kind: Verrazzano
metadata:
  name: custom-opensearch-example
spec:
  profile: dev
  components:
    opensearch:
      policies:
        - policyName: my-app
          indexPattern: my-app-*
          minIndexAge: 14d
          rollover:
            minIndexAge: 3d
            minDocCount: 1000
            minSize: 10Gb

Install OpenSearch and OpenSearch Dashboards plug-ins

Verrazzano supports OpenSearch and OpenSearch Dashboard plug-in installation by providing plug-ins in the Verrazzano custom resource. To install plug-ins for OpenSearch, you define the field spec.components.opensearch.plugins in the Verrazzano custom resource.

The following Verrazzano custom resource example installs the analysis-stempel and opensearch-anomaly-detection plug-ins for OpenSearch:

apiVersion: install.verrazzano.io/v1beta1
kind: Verrazzano
metadata:
  name: custom-opensearch-example
spec:
  profile: dev
  components:
    opensearch:
      plugins:
        enabled: true
        installList:
          - analysis-stempel
          - https://repo1.maven.org/maven2/org/opensearch/plugin/opensearch-anomaly-detection/2.2.0.0/opensearch-anomaly-detection-2.2.0.0.zip

There are three ways to define a plug-in in the plugins.installList:

Define a plug-in by name:

There are some pre-built additional plug-ins that you can install by name.
```
installList:
        - analysis-icu
```

Define a plug-in from a remote ZIP file:

Provide the URL to a remote ZIP file that contains the required plug-in.

installList:
        - https://repo1.maven.org/maven2/org/opensearch/plugin/opensearch-anomaly-detection/2.2.0.0/opensearch-anomaly-detection-2.2.0.0.zip

Define a plug-in using Maven coordinates:

Provide the Maven coordinates for the available artifacts and versions hosted on Maven Central.
```
installList:
        - org.opensearch.plugin:opensearch-anomaly-detection:2.2.0.0
```

NOTE

Your environment must be able to connect to the Internet to access the provided plug-in URL or Maven Central to install the plug-in. If there is any error during plug-in installation, then the OS pods (one per deployment) will go into the CrashLoopBackOff state. Check the logs for the exact reason of the failure. In the case of an Internet issue, you might see SocketException or UnknownHostException exceptions in the logs. To resolve this issue, make sure that the pods are connected to the Internet.
Adding a new plug-in in the plugins.installList or removing a plug-in from the plugins.installList will result in restarting the OpenSearch related pods.
To be compatible, major, minor, and patch plug-in versions must match OpenSearch major, minor, and patch versions. For example, plug-ins versions 2.3.0.x are compatible only with OpenSearch version 2.3.0.

For OpenSearch Dashboard, you can provide the plug-ins by defining the field spec.components.opensearch-dashboards.plugins in the Verrazzano custom resource.

Here is a Verrazzano custom resource example to install plug-ins for the OpenSearch Dashboards:

apiVersion: install.verrazzano.io/v1beta1
kind: Verrazzano
metadata:
  name: custom-opensearch-example
spec:
  profile: dev
  components:
    opensearchDashboards:
      plugins:
        enabled: true
        installList:
          - <URL to OpenSearch Dashboard plugin ZIP file>

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