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This guide will give an overview on how the KubeDB Autoscaler operator autoscales the database compute resources i.e.
The Auto Scaling process consists of the following steps:
At first, a user creates an
Elasticsearch Custom Resource Object (CRO).
KubeDB Community operator watches the
When the operator finds an
Elasticsearch CRO, it creates required number of
StatefulSets and related necessary stuff like secrets, services, etc.
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.
KubeDB Autoscaler operator watches the
KubeDB Autoscaler operator creates required number of Vertical Pod Autoscaler VPA for different components of the database, as specified in the
KubeDB Autoscaler operator continuously watches the VPA objects for the recommendation.
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.
KubeDB Enterprise operator watches the
KubeDB Enterprise operator will scale the database component vertically as specified on the
In the next docs, we are going to show a detailed-guide on Autoscaling of various Elasticsearch database components using