KubeBlocks
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Overview
Quickstart

Operations

Lifecycle Management
Vertical Scaling
Horizontal Scaling
Volume Expansion
Manage Kafka Services
Decommission Kafka Replica

Monitoring

Observability for Kafka Clusters

tpl

  1. Why Decommission Pods with KubeBlocks?
  2. Prerequisites
  3. Deploy a Kafka Cluster
  4. Verifying the Deployment
  5. Decommission a Pod
    1. Monitor the Decommissioning Process
    2. Verify the Decommissioning
  6. Summary

Decommission a Specific Pod in KubeBlocks-Managed Kafka Clusters

This guide explains how to decommission (take offline) specific Pods in Kafka clusters managed by KubeBlocks. Decommissioning provides precise control over cluster resources while maintaining availability. Use this for workload rebalancing, node maintenance, or addressing failures.

Why Decommission Pods with KubeBlocks?

In traditional StatefulSet-based deployments, Kubernetes lacks the ability to decommission specific Pods. StatefulSets ensure the order and identity of Pods, and scaling down always removes the Pod with the highest ordinal number (e.g., scaling down from 3 replicas removes Pod-2 first). This limitation prevents precise control over which Pod to take offline, which can complicate maintenance, workload distribution, or failure handling.

KubeBlocks overcomes this limitation by enabling administrators to decommission specific Pods directly. This fine-grained control ensures high availability and allows better resource management without disrupting the entire cluster.

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 Kafka Cluster

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

      Apply the following YAML configuration to deploy the cluster:

      apiVersion: apps.kubeblocks.io/v1
      kind: Cluster
      metadata:
        name: kafka-separated-cluster
        namespace: demo
      spec:
        terminationPolicy: Delete
        clusterDef: kafka
        topology: separated_monitor
        componentSpecs:
          - name: kafka-broker
            replicas: 1
            resources:
              limits:
                cpu: "0.5"
                memory: "0.5Gi"
              requests:
                cpu: "0.5"
                memory: "0.5Gi"
            env:
              - name: KB_KAFKA_BROKER_HEAP
                value: "-XshowSettings:vm -XX:MaxRAMPercentage=100 -Ddepth=64"
              - name: KB_KAFKA_CONTROLLER_HEAP
                value: "-XshowSettings:vm -XX:MaxRAMPercentage=100 -Ddepth=64"
              - name: KB_BROKER_DIRECT_POD_ACCESS
                value: "true"
            volumeClaimTemplates:
              - name: data
                spec:
                  storageClassName: ""
                  accessModes:
                    - ReadWriteOnce
                  resources:
                    requests:
                      storage: 20Gi
              - name: metadata
                spec:
                  storageClassName: ""
                  accessModes:
                    - ReadWriteOnce
                  resources:
                    requests:
                      storage: 1Gi
          - name: kafka-controller
            replicas: 1
            resources:
              limits:
                cpu: "0.5"
                memory: "0.5Gi"
              requests:
                cpu: "0.5"
                memory: "0.5Gi"
            volumeClaimTemplates:
              - name: metadata
                spec:
                  storageClassName: ""
                  accessModes:
                    - ReadWriteOnce
                  resources:
                    requests:
                      storage: 1Gi
          - name: kafka-exporter
            replicas: 1
            resources:
              limits:
                cpu: "0.5"
                memory: "1Gi"
              requests:
                cpu: "0.1"
                memory: "0.2Gi"
      
      NOTE

      These three components will be created strictly in controller->broker->exporter order as defined in ClusterDefinition.

      Verifying the Deployment

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

        kubectl get cluster kafka-separated-cluster -n demo -w
        

        Expected Output:

        kubectl get cluster kafka-separated-cluster -n demo
        NAME                      CLUSTER-DEFINITION   TERMINATION-POLICY   STATUS     AGE
        kafka-separated-cluster   kafka                Delete               Creating   13s
        kafka-separated-cluster   kafka                Delete               Running    63s
        

        Check the pod status and roles:

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

        Expected Output:

        NAME                                         READY   STATUS    RESTARTS   AGE
        kafka-separated-cluster-kafka-broker-0       2/2     Running   0          13m
        kafka-separated-cluster-kafka-controller-0   2/2     Running   0          13m
        kafka-separated-cluster-kafka-exporter-0     1/1     Running   0          12m
        

        Once the cluster status becomes Running, your Kafka 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.

        Decommission a Pod

        Expected Workflow:

        1. Replica specified in onlineInstancesToOffline is removed
        2. Pod terminates gracefully
        3. Cluster transitions from Updating to Running

        Before decommissioning a specific pod from a component, make sure this component has more than one replicas. If not, please scale out the component ahead.

        E.g. you can patch the cluster CR with command, to declare there are 3 replicas in component querynode.

        kubectl patch cluster kafka-separated-cluster -n demo --type='json' -p='[
          {
            "op": "replace",
            "path": "/spec/componentSpecs/1/replicas",
            "value": 3
          }
        ]'
        

        Wait till all pods are running

        kubectl get pods -n demo -l app.kubernetes.io/instance=kafka-separated-cluster,apps.kubeblocks.io/component-name=kafka-broker
        

        Expected Output:

        NAME                                     READY   STATUS    RESTARTS   AGE
        kafka-separated-cluster-kafka-broker-0   2/2     Running   0          18m
        kafka-separated-cluster-kafka-broker-1   2/2     Running   0          3m33m
        kafka-separated-cluster-kafka-broker-2   2/2     Running   0          2m1s
        

        To decommission a specific Pod (e.g., 'kafka-separated-cluster-kafka-broker-1'), you can use one of the following methods:

        Option 1: Using OpsRequest

        Create an OpsRequest to mark the Pod as offline:

        apiVersion: operations.kubeblocks.io/v1alpha1
        kind: OpsRequest
        metadata:
          name: kafka-separated-cluster-decommission-ops
          namespace: demo
        spec:
          clusterName: kafka-separated-cluster
          type: HorizontalScaling
          horizontalScaling:
          - componentName: kafka-broker
            scaleIn:
              onlineInstancesToOffline:
                - 'kafka-separated-cluster-kafka-broker-1'  # Specifies the instance names that need to be taken offline
        

        Monitor the Decommissioning Process

        Check the progress of the decommissioning operation:

        kubectl get ops kafka-separated-cluster-decommission-ops -n demo -w
        

        Example Output:

        NAME                                       TYPE                CLUSTER                   STATUS    PROGRESS   AGE
        kafka-separated-cluster-decommission-ops   HorizontalScaling   kafka-separated-cluster   Running   0/1        8s
        kafka-separated-cluster-decommission-ops   HorizontalScaling   kafka-separated-cluster   Running   1/1        31s
        kafka-separated-cluster-decommission-ops   HorizontalScaling   kafka-separated-cluster   Succeed   1/1        31s
        

        Option 2: Using Cluster API

        Alternatively, update the Cluster resource directly to decommission the Pod:

        apiVersion: apps.kubeblocks.io/v1
        kind: Cluster
        spec:
          componentSpecs:
            - name: kafka-broker
              replicas: 2       # explected replicas after decommission
              offlineInstances:
                - kafka-separated-cluster-kafka-broker-1   # <----- Specify Pod to be decommissioned
         ...
        

        Verify the Decommissioning

        After applying the updated configuration, verify the remaining Pods in the cluster:

        kubectl get pods -n demo -l app.kubernetes.io/instance=kafka-separated-cluster,apps.kubeblocks.io/component-name=kafka-broker
        

        Example Output:

        NAME                                     READY   STATUS    RESTARTS   AGE
        kafka-separated-cluster-kafka-broker-0   2/2     Running   0          24m
        kafka-separated-cluster-kafka-broker-2   2/2     Running   0          2m1s
        

        Summary

        Key takeaways:

        • Traditional StatefulSets lack precise Pod removal control
        • KubeBlocks enables targeted Pod decommissioning
        • Two implementation methods: OpsRequest or Cluster API

        This provides granular cluster management while maintaining availability.

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