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Milvus Compute Resource Autoscaling

This guide will give an overview on how the KubeDB Autoscaler operator autoscales the compute resources (CPU/memory) of a Milvus database.

Before You Begin

• You should be familiar with the following KubeDB concepts:
  • Milvus
  • MilvusAutoscaler
  • MilvusOpsRequest

How Compute Autoscaling Works

A MilvusAutoscaler of type compute watches the resource usage of the Milvus pods (via the metrics server / VPA recommender) and, when usage drifts far enough from the requested resources, it creates a VerticalScaling MilvusOpsRequest to right-size the pods.

spec.compute is keyed by component:

• Standalone: node.
• Distributed: proxy, mixcoord, datanode, querynode, streamingnode.

Each block supports:

spec:
  compute:
    node:                          # or proxy/mixcoord/datanode/querynode/streamingnode
      trigger: "On"
      podLifeTimeThreshold: 1m
      resourceDiffPercentage: 10
      minAllowed:
        cpu: 100m
        memory: 256Mi
      maxAllowed:
        cpu: 1000m
        memory: 2Gi
      controlledResources: ["cpu", "memory"]

• trigger — On/Off; enables autoscaling for the component.
• minAllowed/maxAllowed — the bounds the autoscaler stays within.
• resourceDiffPercentage — how far current resources must drift from the recommendation before an ops request is created.
• podLifeTimeThreshold — minimum pod age before it is considered for scaling.
• controlledResources — which resources are managed.

The flow is:

1. A user creates a MilvusAutoscaler with spec.compute.
2. The autoscaler creates a VerticalPodAutoscaler (VPA) object which produces resource recommendations.
3. When the recommendation differs from the current resources by more than resourceDiffPercentage, the autoscaler creates a VerticalScaling MilvusOpsRequest (subject to spec.opsRequestOptions).
4. The Ops-manager operator applies the vertical scaling as usual.

Prerequisite: a metrics server must be installed in the cluster for the VPA recommender to produce recommendations.

In the next doc, we will see a step-by-step guide on compute autoscaling of a Milvus database.