Installing Strimzi

In this post, you'll learn how to install Strimzi on a K3s cluster.

By Anatoly Zelenin

Install k3s

curl -sfL https://get.k3s.io | K3S_KUBECONFIG_MODE="644" sh -

Install Strimzi CRDs + operator

Let’s continue in a new directory and also create a separate namespace for the Strimzi operator:

mkdir ~/strimzi
cd ~/strimzi
kubectl create namespace strimzi-operator
kubectl create namespace kafka

Now we download the Strimzi CRDs and the operator and adjust the namespace configuration so that the operator runs in the namespace strimzi-operator:

wget https://github.com/strimzi/strimzi-kafka-operator/releases/download/0.40.0/strimzi-crds-0.40.0.yaml -O strimzi-crds.yaml
wget https://github.com/strimzi/strimzi-kafka-operator/releases/download/0.40.0/strimzi-cluster-operator-0.40.0.yaml -O strimzi-cluster-operator.yaml
sed -i 's/namespace: .*/namespace: strimzi-operator/' strimzi-cluster-operator.yaml

We want Strimzi Operator to monitor all namespaces so that we can also start several Kafka clusters per Kubernetes.

However, we need to customise the Strimzi deployment for this. To do this, replace the following lines in the strimzi-cluster-operator.yaml file:

strimzi-cluster-operator.yaml
# Old (for me line 7452
          env:
            - name: STRIMZI_NAMESPACE
              valueFrom:
                fieldRef:
                  fieldPath: metadata.namespace
# New
          env:
            - name: STRIMZI_NAMESPACE
              value: "*"

The operator requires some additional rights that are not available in the deployment:

kubectl create clusterrolebinding strimzi-cluster-operator-namespaced --clusterrole=strimzi-cluster-operator-namespaced --serviceaccount strimzi-operator:strimzi-cluster-operator
kubectl create clusterrolebinding strimzi-cluster-operator-watched --clusterrole=strimzi-cluster-operator-watched --serviceaccount strimzi-operator:strimzi-cluster-operator
kubectl create clusterrolebinding strimzi-cluster-operator-entity-operator-delegation --clusterrole=strimzi-entity-operator --serviceaccount strimzi-operator:strimzi-cluster-operator

Now we can install the CRDs and the operator:

kubectl apply -f strimzi-crds.yaml
kubectl apply -f strimzi-cluster-operator.yaml -n strimzi-operator

Wait a moment until the operator is ready:

kubectl get pods -n strimzi-operator -w

Configure Kafka Cluster

We would now like to set up the Kafka cluster "correctly" with KRaft:

  • 3 KRaft Controllers with 5GB memory each

  • 3 Kafka Brokers with 50GB memory each

To do this, we create a node pool for both the controllers and the brokers:

kafka-controller-pool.yaml
apiVersion: kafka.strimzi.io/v1beta2
kind: KafkaNodePool
metadata:
  name: controller
  namespace: kafka
  labels:
    strimzi.io/cluster: kafka
spec:
  replicas: 3
  roles:
    - controller
  storage:
    type: jbod
    volumes:
      - id: 0
        type: persistent-claim
        size: 5Gi
        deleteClaim: false
kafka-broker-pool.yaml
apiVersion: kafka.strimzi.io/v1beta2
kind: KafkaNodePool
metadata:
  name: broker
  namespace: kafka
  labels:
    strimzi.io/cluster: kafka
spec:
  replicas: 3
  roles:
    - broker
  storage:
    type: jbod
    volumes:
      - id: 0
        type: persistent-claim
        size: 50Gi
        deleteClaim: false

Finally, the resources for the Kafka Cluster itself:

kafka-cluster.yaml
apiVersion: kafka.strimzi.io/v1beta2
kind: Kafka
metadata:
  name: kafka
  namespace: kafka
  annotations:
    strimzi.io/node-pools: enabled
    strimzi.io/kraft: enabled
spec:
  kafka:
    version: 3.7.0
    listeners:
      - name: plain
        port: 9092
        type: internal
        tls: false
    config:
      offsets.topic.replication.factor: 3
      transaction.state.log.replication.factor: 3
      transaction.state.log.min.isr: 2
      default.replication.factor: 3
      min.insync.replicas: 2
  entityOperator:
    topicOperator: {}
    userOperator: {}

Now we can create the resources:

# We are still in the namespace kafka
kubectl apply -f kafka-controller-pool.yaml
kubectl apply -f kafka-broker-pool.yaml
kubectl apply -f kafka-cluster.yaml

Take a closer look at the Kafka resource and then wait until the pods have started:

kubectl config set-context --current --namespace=kafka
kubectl describe kafka kafka
kubectl get pods -w

Anatoly Zelenin teaches Apache Kafka to hundreds of participants in interactive training sessions. His clients from the DAX environment and German mid-sized companies have valued his expertise and inspiring approach for over a decade. In addition to being an IT consultant and trainer, he also explores our planet as an adventurer.

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