Scaling subclusters

The operator enables you to scale the number of subclusters and the number of pods per subcluster automatically.

The operator enables you to scale the number of subclusters and the number of pods per subcluster automatically. This utilizes or conserves resources depending on the immediate needs of your workload.

The following sections explain how to scale resources for new workloads. For details about scaling resources for existing workloads, see VerticaAutoscaler custom resource definition.

Prerequisites

Complete Installing the VerticaDB operator.
Install the kubectl command line tool.
Complete VerticaDB custom resource definition.
Confirm that you have the resources to scale.

Note
By default, the custom resource uses the free Community Edition (CE) license. This license allows you to deploy up to three nodes with a maximum of 1TB of data. To add resources beyond these limits, you must add your Vertica license to the custom resource as described in VerticaDB custom resource definition.

Scaling the number of subclusters

Adjust the number of subclusters in your custom resource to fine-tune resources for short-running dashboard queries. For example, increase the number of subclusters to increase throughput. For more information, see Improving query throughput using subclusters.

Use kubectl edit to open your default text editor and update the YAML file for the specified custom resource. The following command opens a custom resource named vdb for editing:
```
$ kubectl edit vdb
```
In the spec section of the custom resource, locate the subclusters subsection. Begin with the type field to define a new subcluster.

The type field indicates the subcluster type. Because there is already a primary subcluster, enter Secondary:
```
spec:
...
  subclusters:
  ...
  - type: secondary
```

Follow the steps in VerticaDB custom resource definition to complete the subcluster definition. The following completed example adds a secondary subcluster for dashboard queries:

spec:
...
  subclusters:
  - type: primary
    name: primary-subcluster
  ...
  - type: secondary
    name: dashboard
    clientNodePort: 32001
    resources:
      limits:
        cpu: 32
        memory: 96Gi
      requests:
        cpu: 32
        memory: 96Gi
    serviceType: NodePort
    size: 3

Save and close the custom resource file. When the update completes, you receive a message similar to the following:
```
verticadb.vertica.com/vertica-db edited
```

Use the kubectl wait command to monitor when the new pods are ready:

$ kubectl wait --for=condition=Ready pod --selector app.kubernetes.io/name=verticadb --timeout 180s
pod/vdb-dashboard-0 condition met
pod/vdb-dashboard-1 condition met
pod/vdb-dashboard-2 condition met

Scaling the pods in a subcluster

For long-running, analytic queries, increase the pod count for a subcluster. See Using elastic crunch scaling to improve query performance.

Use kubectl edit to open your default text editor and update the YAML file for the specified custom resource. The following command opens a custom resource named verticadb for editing:
```
$ kubectl edit verticadb
```

Update the subclusters.size value to 6:

spec:
...
  subclusters:
  ...
  - type: secondary
    ...
    size: 6

Shards are rebalanced automatically.

Save and close the custom resource file. You receive a message similar to the following when you successfully update the file:

verticadb.vertica.com/verticadb edited

Use the kubectl wait command to monitor when the new pods are ready:

$ kubectl wait --for=condition=Ready pod --selector app.kubernetes.io/name=verticadb --timeout 180s
pod/vdb-subcluster1-3 condition met
pod/vdb-subcluster1-4 condition met
pod/vdb-subcluster1-5 condition met

Removing a subcluster

Remove a subcluster when it is no longer needed, or to preserve resources.

Important

Because each custom resource instance requires a primary subcluster, you cannot remove all subclusters.

Use kubectl edit to open your default text editor and update the YAML file for the specified custom resource. The following command opens a custom resource named verticadb for editing:
```
$ kubectl edit verticadb
```
In the subclusters subsection nested under spec, locate the subcluster that you want to delete. Delete the element in the subcluster array represents the subcluster that you want to delete. Each element is identified by a hyphen (-).
After you delete the subcluster and save, you receive a message similar to the following:
```
verticadb.vertica.com/verticadb edited
```