Vertical Scaling for Milvus Standalone Clusters with KubeBlocks

This guide demonstrates how to vertically scale a Milvus Cluster managed by KubeBlocks by adjusting compute resources (CPU and memory) while maintaining the same number of replicas.

Vertical scaling modifies compute resources (CPU and memory) for Milvus instances while maintaining replica count. Key characteristics:

• Non-disruptive: When properly configured, maintains availability during scaling
• Granular: Adjust CPU, memory, or both independently
• Reversible: Scale up or down as needed

KubeBlocks ensures minimal impact during scaling operations by following a controlled, role-aware update strategy: Role-Aware Replicas (Primary/Secondary Replicas)

• Secondary replicas update first – Non-leader pods are upgraded to minimize disruption.
• Primary updates last – Only after all secondaries are healthy does the primary pod restart.
• Cluster state progresses from Updating → Running once all replicas are stable.

Role-Unaware Replicas (Ordinal-Based Scaling) If replicas have no defined roles, updates follow Kubernetes pod ordinal order:

• Highest ordinal first (e.g., pod-2 → pod-1 → pod-0) to ensure deterministic rollouts.

Prerequisites

Before proceeding, ensure the following:

• Environment Setup:
  • A Kubernetes cluster is up and running.
  • The kubectl CLI tool is configured to communicate with your cluster.
  • KubeBlocks CLI and KubeBlocks Operator are installed. Follow the installation instructions here.
• Namespace Preparation: To keep resources isolated, create a dedicated namespace for this tutorial:

kubectl create ns demo
namespace/demo created

Deploy a Milvus Cluster

Please refer to Deploying a Milvus Cluster with KubeBlocks to deploy a milvus cluster.

Vertical Scale

Expected Workflow:

1. Pods are updated in pod ordinal order, from highest to lowest, (e.g., pod-2 → pod-1 → pod-0)
2. Cluster status transitions from Updating to Running

Check Components

There are five components in Milvus Cluster. To get the list of components,

kubectl get cluster -n demo milvus-cluster -oyaml | yq '.spec.componentSpecs[].name'

Expected Output:

proxy
mixcoord
datanode
indexnode
querynode

apiVersion: operations.kubeblocks.io/v1alpha1
kind: OpsRequest
metadata:
  name: milvus-cluster-vscale-ops
  namespace: demo
spec:
  clusterName: milvus-cluster
  type: VerticalScaling
  verticalScaling:
  - componentName: querynode
    requests:
      cpu: '1'
      memory: 1Gi
    limits:
      cpu: '1'
      memory: 1Gi

kubectl -n demo get ops milvus-cluster-vscale-ops -w

NAME                        TYPE              CLUSTER          STATUS    PROGRESS   AGE
milvus-cluster-vscale-ops   VerticalScaling   milvus-cluster   Running   0/2        33s
milvus-cluster-vscale-ops   VerticalScaling   milvus-cluster   Running   1/2        55s
milvus-cluster-vscale-ops   VerticalScaling   milvus-cluster   Running   2/2        88s

apiVersion: apps.kubeblocks.io/v1
kind: Cluster
spec:
  componentSpecs:
    - name: querynode
      replicas: 1
      resources:
        requests:
          cpu: "1"       # Update the resources to your need.
          memory: "1Gi"  # Update the resources to your need.
        limits:
          cpu: "1"       # Update the resources to your need.
          memory: "1Gi"  # Update the resources to your need.
  ...

Best Practices & Considerations

Planning:

• Scale during maintenance windows or low-traffic periods
• Verify Kubernetes cluster has sufficient resources
• Check for any ongoing operations before starting

Execution:

• Maintain balanced CPU-to-Memory ratios
• Set identical requests/limits for guaranteed QoS

Post-Scaling:

• Monitor resource utilization and application performance
• Consider adjusting Milvus parameters if needed

Verification

Verify the updated resources by inspecting the cluster configuration or Pod details:

kbcli cluster describe milvus-cluster -n demo

Expected Output:

Resources Allocation:
COMPONENT   INSTANCE-TEMPLATE   CPU(REQUEST/LIMIT)   MEMORY(REQUEST/LIMIT)   STORAGE-SIZE   STORAGE-CLASS
milvus                          1 / 1                1Gi / 1Gi               data:20Gi      <none>

Key Benefits of Vertical Scaling with KubeBlocks

• Seamless Scaling: Pods are recreated in a specific order to ensure minimal disruption.
• Dynamic Resource Adjustments: Easily scale CPU and memory based on workload requirements.
• Flexibility: Choose between OpsRequest for dynamic scaling or direct API updates for precise control.
• Improved Availability: The cluster remains operational during the scaling process, maintaining high availability.

Cleanup

To remove all created resources, delete the Milvus Cluster along with its namespace:

kubectl delete cluster milvus-cluster -n demo
kubectl delete ns demo

Summary

In this guide, you learned how to:

1. Deploy a Milvus Cluster managed by KubeBlocks.
2. Perform vertical scaling by increasing or decreasing resources for the milvus component.
3. Use both OpsRequest and direct Cluster API updates to adjust resource allocations.

Vertical scaling is a powerful tool for optimizing resource utilization and adapting to changing workload demands, ensuring your Milvus Cluster remains performant and resilient.