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Qdrant Compute Resource Autoscaling

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

Before You Begin

• You should be familiar with the following KubeDB concepts:
  • Qdrant
  • QdrantOpsRequest
  • QdrantAutoscaler

How Compute Autoscaling Works

The following diagram shows how KubeDB Autoscaler operator autoscales the resources of Qdrant database components. Open the image in a new tab to see the enlarged version.

  

The Auto Scaling process consists of the following steps:

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

2. KubeDB Provisioner operator watches the Qdrant CRO.

3. When the operator finds a Qdrant CRO, it creates PetSet and related necessary stuff like secrets, services, etc.

4. Then, in order to set up autoscaling of the Qdrant database the user creates a QdrantAutoscaler CRO with desired configuration.

5. KubeDB Autoscaler operator watches the QdrantAutoscaler 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 QdrantAutoscaler CRO.

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

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

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

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