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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 a Elasticsearch Custom Resource Object (CRO).

2. KubeDB Provisioner operator watches the Elasticsearch CRO.

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

4. Then, in order to set up autoscaling of the various components of the Elasticsearch database the user creates a ElasticsearchAutoscaler CRO with desired configuration.

5. KubeDB Autoscaler operator watches the ElasticsearchAutoscaler CRO.

6. KubeDB Autoscaler operator generates recommendation using the modified version of kubernetes official recommender for different components of the database, as specified in the ElasticsearchAutoscaler CRO.

7. If the generated recommendation doesn’t match the current resources of the database, then KubeDB Autoscaler operator creates a ElasticsearchOpsRequest CRO to scale the database to match the recommendation generated.

8. KubeDB Ops-manager operator watches the ElasticsearchOpsRequest CRO.

9. Then the KubeDB Ops-manager operator will scale the database component vertically as specified on the ElasticsearchOpsRequest CRO.

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