New to KubeDB? Please start here.

Hazelcast 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 hazelcastautoscaler crd.

Before You Begin

• You should be familiar with the following KubeDB concepts:
  • Hazelcast
  • HazelcastAutoscaler
  • HazelcastOpsRequest

How Compute Autoscaling Works

The following diagram shows how KubeDB Autoscaler operator autoscales the resources of Hazelcast 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 Hazelcast Custom Resource Object (CRO).

2. KubeDB Provisioner operator watches the Hazelcast CRO.

3. When the operator finds a Hazelcast 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 components (ie. ) of the Hazelcast cluster the user creates a HazelcastAutoscaler CRO with desired configuration.

5. KubeDB Autoscaler operator watches the HazelcastAutoscaler 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 HazelcastAutoscaler CRO.

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

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

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

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