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Elasticsearch Compute Resource Autoscaling

This guide will give an overview on how the KubeDB Autoscaler operator autoscales the database compute resources i.e. cpu and memory using elasticsearchautoscaler crd.

Before You Begin

• You should be familiar with the following KubeDB concepts:
  • Elasticsearch
  • ElasticsearchAutoscaler
  • ElasticsearchOpsRequest

How Compute Autoscaling Works

The Auto Scaling process consists of the following steps:

1. At first, a user creates an Elasticsearch Custom Resource Object (CRO).

2. KubeDB Community operator watches the Elasticsearch CRO.

3. When the operator finds an Elasticsearch CRO, it creates required number of StatefulSets and related necessary stuff like secrets, services, etc.

4. Then, in order to set up autoscaling of the various nodes (ie. master, data, ingest, etc.) of the Elasticsearch database the user creates an ElasticsearchAutoscaler CRO with desired configuration.

5. KubeDB Autoscaler operator watches the ElasticsearchAutoscaler CRO.

6. KubeDB Autoscaler operator creates required number of Vertical Pod Autoscaler VPA for different components of the database, as specified in the elasticsearchautoscaler CRO.

7. Then KubeDB Autoscaler operator continuously watches the VPA objects for the recommendation.

8. If the VPA generated recommendation doesn’t match the current resources of the database, then the KubeDB Autoscaler operator creates an ElasticsearchOpsRequest CRO to scale the database to match the recommendation provided by the VPA object.

9. KubeDB Enterprise operator watches the ElasticsearchOpsRequest CRO.

10. Then the KubeDB Enterprise operator will scale the database component vertically as specified on the ElasticsearchOpsRequest CRO.

In the next docs, we are going to show a detailed-guide on Autoscaling of various Elasticsearch database components using ElasticsearchAutoscaler CRD.