Kafka Quickstart

This guide provides a comprehensive walkabout for deploying and managing Kafka ReplicaSet Clusters using the KubeBlocks Kafka Add-on, covering:

System prerequisites and add-on installation
Cluster creation and configuration
Operational management including start/stop procedures
Connection methods and cluster monitoring

Prerequisites

System Requirements

Before proceeding, verify your environment meets these requirements:

A functional Kubernetes cluster (v1.21+ recommended)
kubectl v1.21+ installed and configured with cluster access
Helm installed (installation guide)
KubeBlocks installed (installation guide)

Verify Kafka Add-on

The Kafka Add-on is included with KubeBlocks by default. Check its status:

helm list -n kb-system | grep kafka

Example Output:

NAME               NAMESPACE   REVISION    UPDATED                     STATUS      CHART
kb-addon-kafka     kb-system   1           2025-05-21                  deployed    kafka-1.0.0

If the add-on isn't enabled, choose an installation method:

# Add Helm repo
helm repo add kubeblocks-addons https://apecloud.github.io/helm-charts
# For users in Mainland China, if GitHub is inaccessible or slow, use this alternative repo:
#helm repo add kubeblocks-addons https://jihulab.com/api/v4/projects/150246/packages/helm/stable

# Update helm repo
helm repo update
# Search available Add-on versions
helm search repo kubeblocks/kafka --versions
# Install your desired version (replace <VERSION> with your chosen version)
helm upgrade -i kb-addon-kafka kubeblocks-addons/kafka --version <VERSION> -n kb-system

# Add an index (kubeblocks is added by default)
kbcli addon index add kubeblocks https://github.com/apecloud/block-index.git
# Update the index
kbcli addon index update kubeblocks
# Update all indexes
kbcli addon index update --all

To search and install an addon:

# Search Add-on
kbcli addon search kafka
# Install Add-on with your desired version (replace <VERSION> with your chosen version)
kbcli addon install kafka --version <VERSION>

Example Output:

ADDON   VERSION         INDEX
kafka   0.9.0           kubeblocks
kafka   0.9.1           kubeblocks
kafka   1.0.0           kubeblocks

To enable or disable an addon:

# Enable Add-on
kbcli addon enable kafka
# Disable Add-on
kbcli addon disable kafka

NOTE

Version Compatibility

Always verify that the Kafka Add-on version matches your KubeBlocks major version to avoid compatibility issues.

Deploy a Kafka Cluster

Deploy a basic Kafka Cluster with default settings:

kubectl apply -f https://raw.githubusercontent.com/apecloud/kubeblocks-addons/refs/heads/main/examples/kafka/cluster-separated.yaml

This creates:

A Kafka Cluster with 3 components, kafka controller with 1 replica, kafka broker with 1 replicas and kafka exporter with 1 replica.
Default resource allocations (0.5 CPU, 0.5Gi memory)
20Gi persistent storage

apiVersion: apps.kubeblocks.io/v1
kind: Cluster
metadata:
  name: kafka-separated-cluster
  namespace: demo
spec:
  # Specifies the behavior when a Cluster is deleted.
  # Valid options are: [DoNotTerminate, Delete, WipeOut] (`Halt` is deprecated since KB 0.9)
  # - `DoNotTerminate`: Prevents deletion of the Cluster. This policy ensures that all resources remain intact.
  # - `Delete`: Extends the `Halt` policy by also removing PVCs, leading to a thorough cleanup while removing all persistent data.
  # - `WipeOut`: An aggressive policy that deletes all Cluster resources, including volume snapshots and backups in external storage. This results in complete data removal and should be used cautiously, primarily in non-production environments to avoid irreversible data loss.
  terminationPolicy: Delete
  # Specifies the name of the ClusterDefinition to use when creating a Cluster.
  # Note: DO NOT UPDATE THIS FIELD
  # The value must be `kafaka` to create a Kafka Cluster
  clusterDef: kafka
  # Specifies the name of the ClusterTopology to be used when creating the
  # Cluster.
  # - combined: combined Kafka controller (KRaft) and broker in one Component
  # - combined_monitor: combined mode with monitor component
  # - separated: separated KRaft and Broker Components.
  # - separated_monitor: separated mode with monitor component
  # Valid options are: [combined,combined_monitor,separated,separated_monitor]
  topology: separated_monitor
  # Specifies a list of ClusterComponentSpec objects used to define the
  # individual Components that make up a Cluster.
  # This field allows for detailed configuration of each Component within the Cluster
  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 # use this ENV to set BROKER HEAP
          value: "-XshowSettings:vm -XX:MaxRAMPercentage=100 -Ddepth=64"
        - name: KB_KAFKA_CONTROLLER_HEAP # use this ENV to set CONTOLLER_HEAP
          value: "-XshowSettings:vm -XX:MaxRAMPercentage=100 -Ddepth=64"
          # Whether to enable direct Pod IP address access mode.
          # - If set to 'true', Kafka clients will connect to Brokers using the Pod IP address directly.
          # - If set to 'false', Kafka clients will connect to Brokers using the Headless Service's FQDN.
        - 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"

For more API fields and descriptions, refer to the API Reference.

Verify Cluster Status

When deploying a Kafka Cluster with 3 replicas:

Confirm successful deployment by checking:

Cluster phase is Running
All pods are operational

Check status using either method:

kubectl get cluster kafka-separated-cluster -n demo -w
NAME                      CLUSTER-DEFINITION   TERMINATION-POLICY   STATUS    AGE
kafka-separated-cluster   kafka                Delete               Running   2m48s

kubectl get pods -l app.kubernetes.io/instance=kafka-separated-cluster -n demo
NAME                                         READY   STATUS    RESTARTS   AGE
kafka-separated-cluster-kafka-broker-0       2/2     Running   0          2m33s
kafka-separated-cluster-kafka-controller-0   2/2     Running   0          2m58s
kafka-separated-cluster-kafka-exporter-0     1/1     Running   0          2m9s

With kbcli installed, you can view comprehensive cluster information:

kbcli cluster describe kafka-separated-cluster -n demo

Name: kafka-separated-cluster  Created Time: May 19,2025 16:56 UTC+0800
NAMESPACE   CLUSTER-DEFINITION   TOPOLOGY            STATUS    TERMINATION-POLICY
demo        kafka                separated_monitor   Running   Delete

Endpoints:
COMPONENT      INTERNAL                                                                                 EXTERNAL
kafka-broker   kafka-separated-cluster-kafka-broker-advertised-listener-0.demo.svc.cluster.local:9092   <none>

Topology:
COMPONENT          SERVICE-VERSION   INSTANCE                                     ROLE     STATUS    AZ       NODE    CREATED-TIME
kafka-broker       3.3.2             kafka-separated-cluster-kafka-broker-0       <none>   Running   zone-x   x.y.z   May 19,2025 16:57 UTC+0800
kafka-controller   3.3.2             kafka-separated-cluster-kafka-controller-0   <none>   Running   zone-x   x.y.z   May 19,2025 16:56 UTC+0800
kafka-exporter     1.6.0             kafka-separated-cluster-kafka-exporter-0     <none>   Running   zone-x   x.y.z   May 19,2025 16:57 UTC+0800

Resources Allocation:
COMPONENT          INSTANCE-TEMPLATE   CPU(REQUEST/LIMIT)   MEMORY(REQUEST/LIMIT)   STORAGE-SIZE   STORAGE-CLASS
kafka-controller                       500m / 500m          512Mi / 512Mi           metadata:1Gi   <none>
kafka-broker                           500m / 500m          512Mi / 512Mi           data:20Gi
                                                                                    metadata:1Gi
kafka-exporter                         100m / 500m          214748364800m / 1Gi     <none>         <none>

Images:
COMPONENT          COMPONENT-DEFINITION             IMAGE
kafka-controller   kafka-controller-1.0.0           docker.io/bitnami/kafka:3.3.2-debian-11-r54
                                                    docker.io/bitnami/jmx-exporter:0.18.0-debian-11-r20
kafka-broker       kafka-broker-1.0.0               docker.io/bitnami/kafka:3.3.2-debian-11-r54
                                                    docker.io/bitnami/jmx-exporter:0.18.0-debian-11-r20
kafka-exporter     kafka-exporter-1.0.0             docker.io/bitnami/kafka-exporter:1.6.0-debian-11-r67

Show cluster events: kbcli cluster list-events -n demo kafka-separated-cluster

Access Kafka Cluster

Step 1. Get the address of the Kafka Services

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

Expected Output:

NAME                                                         TYPE        CLUSTER-IP      EXTERNAL-IP   PORT(S)    AGE
kafka-separated-cluster-kafka-broker-advertised-listener-0   ClusterIP   10.96.131.175   <none>        9092/TCP   5m8s

The service name is kafka-separated-cluster-kafka-broker-advertised-listener-0 in namespace demo.

Step 2. Connect to the Kafka cluster with the port No.

Start client pod.

kubectl run kafka-producer --restart='Never' --image docker.io/bitnami/kafka:3.3.2-debian-11-r54 --command -- sleep infinity
kubectl run kafka-consumer --restart='Never' --image docker.io/bitnami/kafka:3.3.2-debian-11-r54 --command -- sleep infinity

kubectl exec -ti kafka-producer -- bash

Create topic.

kafka-topics.sh --create --topic quickstart-events --bootstrap-server kafka-separated-cluster-kafka-broker-advertised-listener-0.demo:9092

Create producer.

kafka-console-producer.sh --topic quickstart-events --bootstrap-server kafka-separated-cluster-kafka-broker-advertised-listener-0.demo:9092

Enter："Hello, KubeBlocks" and press Enter.
Start a new terminal session and login to kafka-consumer.

kubectl exec -ti kafka-consumer -- bash

Create consumer and specify consuming topic, and consuming message from the beginning.

kafka-console-consumer.sh --topic quickstart-events --from-beginning --bootstrap-server kafka-separated-cluster-kafka-broker-advertised-listener-0.demo:9092

And you get the output 'Hello, KubeBlocks'.

Stop the Kafka Cluster

Stopping a cluster temporarily suspends operations while preserving all data and configuration:

Key Effects:

Compute resources (Pods) are released
Persistent storage (PVCs) remains intact
Service definitions are maintained
Cluster configuration is preserved
Operational costs are reduced

kubectl apply -f https://raw.githubusercontent.com/apecloud/kubeblocks-addons/refs/heads/main/examples/kafka/stop.yaml

apiVersion: operations.kubeblocks.io/v1alpha1
kind: OpsRequest
metadata:
  name: kafka-stop
  namespace: demo
spec:
  clusterName: kafka-separated-cluster
  type: Stop

Alternatively, stop by setting spec.componentSpecs.stop to true:

kubectl patch cluster kafka-separated-cluster -n demo --type='json' -p='[
{
  "op": "add",
  "path": "/spec/componentSpecs/0/stop",
  "value": true
},
{
  "op": "add",
  "path": "/spec/componentSpecs/1/stop",
  "value": true
},
{
  "op": "add",
  "path": "/spec/componentSpecs/2/stop",
  "value": true
}
]'

Start the Kafka Cluster

Restarting a stopped cluster resumes operations with all data and configuration intact.

Key Effects:

Compute resources (Pods) are recreated
Services become available again
Cluster returns to previous state

apiVersion: operations.kubeblocks.io/v1alpha1
kind: OpsRequest
metadata:
  name: kafka-start
  namespace: demo
spec:
  clusterName: kafka-separated-cluster
  type: Start

Restart by setting spec.componentSpecs.stop to false:

kubectl patch cluster kafka-separated-cluster -n demo --type='json' -p='[
{
  "op": "remove",
  "path": "/spec/componentSpecs/0/stop"
},
{
  "op": "remove",
  "path": "/spec/componentSpecs/1/stop"
},
{
  "op": "remove",
  "path": "/spec/componentSpecs/2/stop"
}
]'

Delete Kafka Cluster

Choose carefully based on your data retention needs:

Policy	Resources Removed	Data Removed	Recommended For
DoNotTerminate	None	None	Critical production clusters
Delete	All resources	PVCs deleted	Non-critical environments
WipeOut	All resources	Everything*	Test environments only

*Includes snapshots and backups in external storage

Pre-Deletion Checklist:

Verify no applications are using the cluster
Ensure required backups exist
Confirm proper terminationPolicy is set
Check for dependent resources

For test environments, use this complete cleanup:

kubectl patch cluster kafka-separated-cluster -p '{"spec":{"terminationPolicy":"WipeOut"}}' --type="merge" -n demo
kubectl delete cluster kafka-separated-cluster -n demo

Kafka Quickstart

This guide provides a comprehensive walkabout for deploying and managing Kafka ReplicaSet Clusters using the KubeBlocks Kafka Add-on, covering:

System prerequisites and add-on installation
Cluster creation and configuration
Operational management including start/stop procedures
Connection methods and cluster monitoring

Prerequisites

System Requirements

Before proceeding, verify your environment meets these requirements:

A functional Kubernetes cluster (v1.21+ recommended)
kubectl v1.21+ installed and configured with cluster access
Helm installed (installation guide)
KubeBlocks installed (installation guide)

Verify Kafka Add-on

The Kafka Add-on is included with KubeBlocks by default. Check its status:

helm list -n kb-system | grep kafka

Example Output:

NAME               NAMESPACE   REVISION    UPDATED                     STATUS      CHART
kb-addon-kafka     kb-system   1           2025-05-21                  deployed    kafka-1.0.0

If the add-on isn't enabled, choose an installation method:

# Add Helm repo
helm repo add kubeblocks-addons https://apecloud.github.io/helm-charts
# For users in Mainland China, if GitHub is inaccessible or slow, use this alternative repo:
#helm repo add kubeblocks-addons https://jihulab.com/api/v4/projects/150246/packages/helm/stable

# Update helm repo
helm repo update
# Search available Add-on versions
helm search repo kubeblocks/kafka --versions
# Install your desired version (replace <VERSION> with your chosen version)
helm upgrade -i kb-addon-kafka kubeblocks-addons/kafka --version <VERSION> -n kb-system

# Add an index (kubeblocks is added by default)
kbcli addon index add kubeblocks https://github.com/apecloud/block-index.git
# Update the index
kbcli addon index update kubeblocks
# Update all indexes
kbcli addon index update --all

To search and install an addon:

# Search Add-on
kbcli addon search kafka
# Install Add-on with your desired version (replace <VERSION> with your chosen version)
kbcli addon install kafka --version <VERSION>

Example Output:

ADDON   VERSION         INDEX
kafka   0.9.0           kubeblocks
kafka   0.9.1           kubeblocks
kafka   1.0.0           kubeblocks

To enable or disable an addon:

# Enable Add-on
kbcli addon enable kafka
# Disable Add-on
kbcli addon disable kafka

NOTE

Version Compatibility

Always verify that the Kafka Add-on version matches your KubeBlocks major version to avoid compatibility issues.

Deploy a Kafka Cluster

Deploy a basic Kafka Cluster with default settings:

kubectl apply -f https://raw.githubusercontent.com/apecloud/kubeblocks-addons/refs/heads/main/examples/kafka/cluster-separated.yaml

This creates:

A Kafka Cluster with 3 components, kafka controller with 1 replica, kafka broker with 1 replicas and kafka exporter with 1 replica.
Default resource allocations (0.5 CPU, 0.5Gi memory)
20Gi persistent storage

apiVersion: apps.kubeblocks.io/v1
kind: Cluster
metadata:
  name: kafka-separated-cluster
  namespace: demo
spec:
  # Specifies the behavior when a Cluster is deleted.
  # Valid options are: [DoNotTerminate, Delete, WipeOut] (`Halt` is deprecated since KB 0.9)
  # - `DoNotTerminate`: Prevents deletion of the Cluster. This policy ensures that all resources remain intact.
  # - `Delete`: Extends the `Halt` policy by also removing PVCs, leading to a thorough cleanup while removing all persistent data.
  # - `WipeOut`: An aggressive policy that deletes all Cluster resources, including volume snapshots and backups in external storage. This results in complete data removal and should be used cautiously, primarily in non-production environments to avoid irreversible data loss.
  terminationPolicy: Delete
  # Specifies the name of the ClusterDefinition to use when creating a Cluster.
  # Note: DO NOT UPDATE THIS FIELD
  # The value must be `kafaka` to create a Kafka Cluster
  clusterDef: kafka
  # Specifies the name of the ClusterTopology to be used when creating the
  # Cluster.
  # - combined: combined Kafka controller (KRaft) and broker in one Component
  # - combined_monitor: combined mode with monitor component
  # - separated: separated KRaft and Broker Components.
  # - separated_monitor: separated mode with monitor component
  # Valid options are: [combined,combined_monitor,separated,separated_monitor]
  topology: separated_monitor
  # Specifies a list of ClusterComponentSpec objects used to define the
  # individual Components that make up a Cluster.
  # This field allows for detailed configuration of each Component within the Cluster
  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 # use this ENV to set BROKER HEAP
          value: "-XshowSettings:vm -XX:MaxRAMPercentage=100 -Ddepth=64"
        - name: KB_KAFKA_CONTROLLER_HEAP # use this ENV to set CONTOLLER_HEAP
          value: "-XshowSettings:vm -XX:MaxRAMPercentage=100 -Ddepth=64"
          # Whether to enable direct Pod IP address access mode.
          # - If set to 'true', Kafka clients will connect to Brokers using the Pod IP address directly.
          # - If set to 'false', Kafka clients will connect to Brokers using the Headless Service's FQDN.
        - 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"

For more API fields and descriptions, refer to the API Reference.

Verify Cluster Status

When deploying a Kafka Cluster with 3 replicas:

Confirm successful deployment by checking:

Cluster phase is Running
All pods are operational

Check status using either method:

kubectl get cluster kafka-separated-cluster -n demo -w
NAME                      CLUSTER-DEFINITION   TERMINATION-POLICY   STATUS    AGE
kafka-separated-cluster   kafka                Delete               Running   2m48s

kubectl get pods -l app.kubernetes.io/instance=kafka-separated-cluster -n demo
NAME                                         READY   STATUS    RESTARTS   AGE
kafka-separated-cluster-kafka-broker-0       2/2     Running   0          2m33s
kafka-separated-cluster-kafka-controller-0   2/2     Running   0          2m58s
kafka-separated-cluster-kafka-exporter-0     1/1     Running   0          2m9s

With kbcli installed, you can view comprehensive cluster information:

kbcli cluster describe kafka-separated-cluster -n demo

Name: kafka-separated-cluster  Created Time: May 19,2025 16:56 UTC+0800
NAMESPACE   CLUSTER-DEFINITION   TOPOLOGY            STATUS    TERMINATION-POLICY
demo        kafka                separated_monitor   Running   Delete

Endpoints:
COMPONENT      INTERNAL                                                                                 EXTERNAL
kafka-broker   kafka-separated-cluster-kafka-broker-advertised-listener-0.demo.svc.cluster.local:9092   <none>

Topology:
COMPONENT          SERVICE-VERSION   INSTANCE                                     ROLE     STATUS    AZ       NODE    CREATED-TIME
kafka-broker       3.3.2             kafka-separated-cluster-kafka-broker-0       <none>   Running   zone-x   x.y.z   May 19,2025 16:57 UTC+0800
kafka-controller   3.3.2             kafka-separated-cluster-kafka-controller-0   <none>   Running   zone-x   x.y.z   May 19,2025 16:56 UTC+0800
kafka-exporter     1.6.0             kafka-separated-cluster-kafka-exporter-0     <none>   Running   zone-x   x.y.z   May 19,2025 16:57 UTC+0800

Resources Allocation:
COMPONENT          INSTANCE-TEMPLATE   CPU(REQUEST/LIMIT)   MEMORY(REQUEST/LIMIT)   STORAGE-SIZE   STORAGE-CLASS
kafka-controller                       500m / 500m          512Mi / 512Mi           metadata:1Gi   <none>
kafka-broker                           500m / 500m          512Mi / 512Mi           data:20Gi
                                                                                    metadata:1Gi
kafka-exporter                         100m / 500m          214748364800m / 1Gi     <none>         <none>

Images:
COMPONENT          COMPONENT-DEFINITION             IMAGE
kafka-controller   kafka-controller-1.0.0           docker.io/bitnami/kafka:3.3.2-debian-11-r54
                                                    docker.io/bitnami/jmx-exporter:0.18.0-debian-11-r20
kafka-broker       kafka-broker-1.0.0               docker.io/bitnami/kafka:3.3.2-debian-11-r54
                                                    docker.io/bitnami/jmx-exporter:0.18.0-debian-11-r20
kafka-exporter     kafka-exporter-1.0.0             docker.io/bitnami/kafka-exporter:1.6.0-debian-11-r67

Show cluster events: kbcli cluster list-events -n demo kafka-separated-cluster

Access Kafka Cluster

Step 1. Get the address of the Kafka Services

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

Expected Output:

NAME                                                         TYPE        CLUSTER-IP      EXTERNAL-IP   PORT(S)    AGE
kafka-separated-cluster-kafka-broker-advertised-listener-0   ClusterIP   10.96.131.175   <none>        9092/TCP   5m8s

The service name is kafka-separated-cluster-kafka-broker-advertised-listener-0 in namespace demo.

Step 2. Connect to the Kafka cluster with the port No.

Start client pod.

kubectl run kafka-producer --restart='Never' --image docker.io/bitnami/kafka:3.3.2-debian-11-r54 --command -- sleep infinity
kubectl run kafka-consumer --restart='Never' --image docker.io/bitnami/kafka:3.3.2-debian-11-r54 --command -- sleep infinity

kubectl exec -ti kafka-producer -- bash

Create topic.

kafka-topics.sh --create --topic quickstart-events --bootstrap-server kafka-separated-cluster-kafka-broker-advertised-listener-0.demo:9092

Create producer.

kafka-console-producer.sh --topic quickstart-events --bootstrap-server kafka-separated-cluster-kafka-broker-advertised-listener-0.demo:9092

Enter："Hello, KubeBlocks" and press Enter.
Start a new terminal session and login to kafka-consumer.

kubectl exec -ti kafka-consumer -- bash

Create consumer and specify consuming topic, and consuming message from the beginning.

kafka-console-consumer.sh --topic quickstart-events --from-beginning --bootstrap-server kafka-separated-cluster-kafka-broker-advertised-listener-0.demo:9092

And you get the output 'Hello, KubeBlocks'.

Stop the Kafka Cluster

Stopping a cluster temporarily suspends operations while preserving all data and configuration:

Key Effects:

Compute resources (Pods) are released
Persistent storage (PVCs) remains intact
Service definitions are maintained
Cluster configuration is preserved
Operational costs are reduced

kubectl apply -f https://raw.githubusercontent.com/apecloud/kubeblocks-addons/refs/heads/main/examples/kafka/stop.yaml

apiVersion: operations.kubeblocks.io/v1alpha1
kind: OpsRequest
metadata:
  name: kafka-stop
  namespace: demo
spec:
  clusterName: kafka-separated-cluster
  type: Stop

Alternatively, stop by setting spec.componentSpecs.stop to true:

kubectl patch cluster kafka-separated-cluster -n demo --type='json' -p='[
{
  "op": "add",
  "path": "/spec/componentSpecs/0/stop",
  "value": true
},
{
  "op": "add",
  "path": "/spec/componentSpecs/1/stop",
  "value": true
},
{
  "op": "add",
  "path": "/spec/componentSpecs/2/stop",
  "value": true
}
]'

Start the Kafka Cluster

Restarting a stopped cluster resumes operations with all data and configuration intact.

Key Effects:

Compute resources (Pods) are recreated
Services become available again
Cluster returns to previous state

apiVersion: operations.kubeblocks.io/v1alpha1
kind: OpsRequest
metadata:
  name: kafka-start
  namespace: demo
spec:
  clusterName: kafka-separated-cluster
  type: Start

Restart by setting spec.componentSpecs.stop to false:

kubectl patch cluster kafka-separated-cluster -n demo --type='json' -p='[
{
  "op": "remove",
  "path": "/spec/componentSpecs/0/stop"
},
{
  "op": "remove",
  "path": "/spec/componentSpecs/1/stop"
},
{
  "op": "remove",
  "path": "/spec/componentSpecs/2/stop"
}
]'

Delete Kafka Cluster

Choose carefully based on your data retention needs:

Policy	Resources Removed	Data Removed	Recommended For
DoNotTerminate	None	None	Critical production clusters
Delete	All resources	PVCs deleted	Non-critical environments
WipeOut	All resources	Everything*	Test environments only

*Includes snapshots and backups in external storage

Pre-Deletion Checklist:

Verify no applications are using the cluster
Ensure required backups exist
Confirm proper terminationPolicy is set
Check for dependent resources

For test environments, use this complete cleanup:

kubectl patch cluster kafka-separated-cluster -p '{"spec":{"terminationPolicy":"WipeOut"}}' --type="merge" -n demo
kubectl delete cluster kafka-separated-cluster -n demo