KubeBlocks
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Overview
Quickstart

Operations

Lifecycle Management
Vertical Scaling
Horizontal Scaling
Volume Expansion
Manage Qdrant Services
Minor Version Upgrade
Decommission Qdrant Replica

Backup And Restores

Create BackupRepo
Create Full Backup
Scheduled Backups
Restore Qdrant Cluster

Monitoring

Observability for Qdrant Clusters

tpl

  1. Prerequisites
  2. Deploy a Qdrant Cluster
  3. Verifying the Deployment
  4. Vertical Scale
  5. Best Practices & Considerations
  6. Verification
  7. Key Benefits of Vertical Scaling with KubeBlocks
  8. Cleanup
  9. Summary

Vertical Scaling for Qdrant Clusters with KubeBlocks

This guide demonstrates how to vertically scale a Qdrant 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 Qdrant 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 Qdrant Cluster

      KubeBlocks uses a declarative approach for managing Qdrant Clusters. Below is an example configuration for deploying a Qdrant Cluster with 3 replicas.

      Apply the following YAML configuration to deploy the cluster:

      apiVersion: apps.kubeblocks.io/v1 kind: Cluster metadata: name: qdrant-cluster namespace: demo spec: terminationPolicy: Delete clusterDef: qdrant topology: cluster componentSpecs: - name: qdrant serviceVersion: 1.10.0 replicas: 3 resources: limits: cpu: "0.5" memory: "0.5Gi" requests: cpu: "0.5" memory: "0.5Gi" volumeClaimTemplates: - name: data spec: storageClassName: "" accessModes: - ReadWriteOnce resources: requests: storage: 20Gi

      Verifying the Deployment

        Monitor the cluster status until it transitions to the Running state:

        kubectl get cluster qdrant-cluster -n demo -w

        Expected Output:

        kubectl get cluster qdrant-cluster -n demo NAME CLUSTER-DEFINITION TERMINATION-POLICY STATUS AGE qdrant-cluster qdrant Delete Creating 49s qdrant-cluster qdrant Delete Running 62s

        Check the pod status and roles:

        kubectl get pods -l app.kubernetes.io/instance=qdrant-cluster -n demo

        Expected Output:

        NAME READY STATUS RESTARTS AGE qdrant-cluster-qdrant-0 2/2 Running 0 1m43s qdrant-cluster-qdrant-1 2/2 Running 0 1m28s qdrant-cluster-qdrant-2 2/2 Running 0 1m14s

        Once the cluster status becomes Running, your Qdrant cluster is ready for use.

        TIP

        If you are creating the cluster for the very first time, it may take some time to pull images before running.

        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

        Option 1: Using VerticalScaling OpsRequest

        Apply the following YAML to scale up the resources for the qdrant component:

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

        You can check the progress of the scaling operation with the following command:

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

        Expected Result:

        NAME TYPE CLUSTER STATUS PROGRESS AGE qdrant-cluster-vscale-ops VerticalScaling qdrant-cluster Running 0/3 32s qdrant-cluster-vscale-ops VerticalScaling qdrant-cluster Running 1/3 55s qdrant-cluster-vscale-ops VerticalScaling qdrant-cluster Running 2/3 82s qdrant-cluster-vscale-ops VerticalScaling qdrant-cluster Running 3/3 2m13s

        Option 2: Direct Cluster API Update

        Alternatively, you may update spec.componentSpecs.resources field to the desired resources for vertical scale.

        apiVersion: apps.kubeblocks.io/v1 kind: Cluster spec: componentSpecs: - name: qdrant replicas: 3 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 Qdrant parameters if needed

        Verification

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

        kbcli cluster describe qdrant-cluster -n demo

        Expected Output:

        Resources Allocation: COMPONENT INSTANCE-TEMPLATE CPU(REQUEST/LIMIT) MEMORY(REQUEST/LIMIT) STORAGE-SIZE STORAGE-CLASS qdrant 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 Qdrant Cluster along with its namespace:

        kubectl delete cluster qdrant-cluster -n demo kubectl delete ns demo

        Summary

        In this guide, you learned how to:

        1. Deploy a Qdrant Cluster managed by KubeBlocks.
        2. Perform vertical scaling by increasing or decreasing resources for the qdrant 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 Qdrant Cluster remains performant and resilient.

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