Operations
Backup And Restores
Monitoring
tpl
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:
KubeBlocks ensures minimal impact during scaling operations by following a controlled, role-aware update strategy: Role-Aware Replicas (Primary/Secondary Replicas)
Role-Unaware Replicas (Ordinal-Based Scaling) If replicas have no defined roles, updates follow Kubernetes pod ordinal order:
Before proceeding, ensure the following:
kubectl create ns demo
namespace/demo created
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
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.
If you are creating the cluster for the very first time, it may take some time to pull images before running.
Expected Workflow:
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.
...
Planning:
Execution:
Post-Scaling:
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>
To remove all created resources, delete the Qdrant Cluster along with its namespace:
kubectl delete cluster qdrant-cluster -n demo
kubectl delete ns demo
In this guide, you learned how to:
Vertical scaling is a powerful tool for optimizing resource utilization and adapting to changing workload demands, ensuring your Qdrant Cluster remains performant and resilient.