Raft Kafka on k8s 部署实战操作-六虎

布置 Raft Kafka（Kafka 3.3.1 及以上版别引入的 KRaft 形式）在 Kubernetes (k8s) 上，能够简化 Kafka 集群的管理，由于它不再依赖于 Zookeeper。

关于Raft Kafka 介绍和物理机布置能够参阅我以下文章：

以下是布置 Raft Kafka 集群的基本步骤：

1）预备 Kubernetes 集群

确保你有一个运行中的 Kubernetes 集群，并且已经装备了 kubectl 命令行工具。布置教程如下：

2）装置 helm

下载地址：github.com/helm/helm/r…

# 下载包
wget https://get.helm.sh/helm-v3.9.4-linux-amd64.tar.gz
# 解压压缩包
tar -xf helm-v3.9.4-linux-amd64.tar.gz
# 制作软衔接
ln -s /opt/helm/linux-amd64/helm /usr/local/bin/helm
# 验证
helm version
helm help

3）装备 Helm chart

如果你运用 Bitnami 的 Kafka Helm chart，你需求创立一个 values.yaml 文件来装备 Kafka 集群。在该文件中，你能够启用 KRaft 形式并装备其他设置，如认证、端口等。

# 增加下载源
helm repo add bitnami https://charts.bitnami.com/bitnami
# 下载
helm pull bitnami/kafka --version 26.0.0
# 解压
tar -xf kafka-26.0.0.tgz
# 修正装备
vi kafka/values.yaml

以下是一个 values.yaml 的示例装备：

image:
  registry: registry.cn-hangzhou.aliyuncs.com
  repository: bigdata_cloudnative/kafka
  tag: 3.6.0-debian-11-r0
listeners:
  client:
    containerPort: 9092
    # 默许是带鉴权的，SASL_PLAINTEXT
    protocol: PLAINTEXT
    name: CLIENT
    sslClientAuth: ""
controller:
  replicaCount: 3 # 控制器的数量
  persistence:
  storageClass: "kafka-controller-local-storage"
  size: "10Gi"
  # 目录需求提早在宿主机上创立
  local:
    - name: kafka-controller-0
      host: "local-168-182-110"
      path: "/opt/bigdata/servers/kraft/kafka-controller/data1"
    - name: kafka-controller-1
      host: "local-168-182-111"
      path: "/opt/bigdata/servers/kraft/kafka-controller/data1"
    - name: kafka-controller-2
      host: "local-168-182-112"
      path: "/opt/bigdata/servers/kraft/kafka-controller/data1"
broker:
  replicaCount: 3  # 署理的数量
  persistence:
  storageClass: "kafka-broker-local-storage"
  size: "10Gi"
  # 目录需求提早在宿主机上创立
  local:
    - name: kafka-broker-0
      host: "local-168-182-110"
      path: "/opt/bigdata/servers/kraft/kafka-broker/data1"
    - name: kafka-broker-1
      host: "local-168-182-111"
      path: "/opt/bigdata/servers/kraft/kafka-broker/data1"
    - name: kafka-broker-2
      host: "local-168-182-112"
      path: "/opt/bigdata/servers/kraft/kafka-broker/data1"
service:
  type: NodePort
  nodePorts:
    #NodePort 默许范围是 30000-32767
    client: "32181"
    tls: "32182"
# Enable Prometheus to access ZooKeeper metrics endpoint
metrics:
  enabled: true
kraft:
  enabled: true

增加以下几个文件：

kafka/templates/broker/pv.yaml

{{- range .Values.broker.persistence.local }}
---
apiVersion: v1
kind: PersistentVolume
metadata:
  name: {{ .name }}
  labels:
    name: {{ .name }}
spec:
  storageClassName: {{ $.Values.broker.persistence.storageClass }}
  capacity:
    storage: {{ $.Values.broker.persistence.size }}
  accessModes:
    - ReadWriteOnce
  local:
    path: {{ .path }}
  nodeAffinity:
    required:
      nodeSelectorTerms:
        - matchExpressions:
            - key: kubernetes.io/hostname
              operator: In
              values:
                - {{ .host }}
---
{{- end }}

kafka/templates/broker/storage-class.yaml

kind: StorageClass
apiVersion: storage.k8s.io/v1
metadata:
  name: {{ .Values.broker.persistence.storageClass }}
provisioner: kubernetes.io/no-provisioner

kafka/templates/controller-eligible/pv.yaml

{{- range .Values.controller.persistence.local }}
---
apiVersion: v1
kind: PersistentVolume
metadata:
  name: {{ .name }}
  labels:
    name: {{ .name }}
spec:
  storageClassName: {{ $.Values.controller.persistence.storageClass }}
  capacity:
    storage: {{ $.Values.controller.persistence.size }}
  accessModes:
    - ReadWriteOnce
  local:
    path: {{ .path }}
  nodeAffinity:
    required:
      nodeSelectorTerms:
        - matchExpressions:
            - key: kubernetes.io/hostname
              operator: In
              values:
                - {{ .host }}
---
{{- end }}

kafka/templates/controller-eligible/storage-class.yaml

kind: StorageClass
apiVersion: storage.k8s.io/v1
metadata:
  name: {{ .Values.controller.persistence.storageClass }}
provisioner: kubernetes.io/no-provisioner

4）运用 Helm 布置 Kafka 集群

# 先预备好镜像
docker pull docker.io/bitnami/kafka:3.6.0-debian-11-r0
docker tag docker.io/bitnami/kafka:3.6.0-debian-11-r0 registry.cn-hangzhou.aliyuncs.com/bigdata_cloudnative/kafka:3.6.0-debian-11-r0
docker push registry.cn-hangzhou.aliyuncs.com/bigdata_cloudnative/kafka:3.6.0-debian-11-r0
# 开始装置
helm install kraft ./kafka -n kraft --create-namespace

NOTES

[root@local-168-182-110 KRaft-on-k8s]# helm upgrade kraft 
Release "kraft" has been upgraded. Happy Helming!
NAME: kraft
LAST DEPLOYED: Sun Mar 24 20:05:04 2024
NAMESPACE: kraft
STATUS: deployed
REVISION: 3
TEST SUITE: None
NOTES:
CHART NAME: kafka
CHART VERSION: 26.0.0
APP VERSION: 3.6.0
** Please be patient while the chart is being deployed **
Kafka can be accessed by consumers via port 9092 on the following DNS name from within your cluster:
    kraft-kafka.kraft.svc.cluster.local
Each Kafka broker can be accessed by producers via port 9092 on the following DNS name(s) from within your cluster:
    kraft-kafka-controller-0.kraft-kafka-controller-headless.kraft.svc.cluster.local:9092
    kraft-kafka-controller-1.kraft-kafka-controller-headless.kraft.svc.cluster.local:9092
    kraft-kafka-controller-2.kraft-kafka-controller-headless.kraft.svc.cluster.local:9092
    kraft-kafka-broker-0.kraft-kafka-broker-headless.kraft.svc.cluster.local:9092
    kraft-kafka-broker-1.kraft-kafka-broker-headless.kraft.svc.cluster.local:9092
    kraft-kafka-broker-2.kraft-kafka-broker-headless.kraft.svc.cluster.local:9092
To create a pod that you can use as a Kafka client run the following commands:
    kubectl run kraft-kafka-client --restart='Never' --image registry.cn-hangzhou.aliyuncs.com/bigdata_cloudnative/kafka:3.6.0-debian-11-r0 --namespace kraft --command -- sleep infinity
    kubectl exec --tty -i kraft-kafka-client --namespace kraft -- bash
    PRODUCER:
        kafka-console-producer.sh 
            --broker-list kraft-kafka-controller-0.kraft-kafka-controller-headless.kraft.svc.cluster.local:9092,kraft-kafka-controller-1.kraft-kafka-controller-headless.kraft.svc.cluster.local:9092,kraft-kafka-controller-2.kraft-kafka-controller-headless.kraft.svc.cluster.local:9092,kraft-kafka-broker-0.kraft-kafka-broker-headless.kraft.svc.cluster.local:9092,kraft-kafka-broker-1.kraft-kafka-broker-headless.kraft.svc.cluster.local:9092,kraft-kafka-broker-2.kraft-kafka-broker-headless.kraft.svc.cluster.local:9092 
            --topic test
    CONSUMER:
        kafka-console-consumer.sh 
            --bootstrap-server kraft-kafka.kraft.svc.cluster.local:9092 
            --topic test 
            --from-beginning

5）测验验证

# 创立客户端
kubectl run kraft-kafka-client --restart='Never' --image registry.cn-hangzhou.aliyuncs.com/bigdata_cloudnative/kafka:3.6.0-debian-11-r0 --namespace kraft --command -- sleep infinity

创立客户端

kafka-topics.sh --create --topic test --bootstrap-server kraft-kafka-controller-0.kraft-kafka-controller-headless.kraft.svc.cluster.local:9092  --partitions 3 --replication-factor 2
# 查看概况
kafka-topics.sh --describe --bootstrap-server kraft-kafka-controller-0.kraft-kafka-controller-headless.kraft.svc.cluster.local:9092  --topic test
# 删去topic
kafka-topics.sh --delete --topic test --bootstrap-server kraft-kafka-controller-0.kraft-kafka-controller-headless.kraft.svc.cluster.local:9092

生产者和消费者

# 生产者
kafka-console-producer.sh 
    --broker-list kraft-kafka-controller-0.kraft-kafka-controller-headless.kraft.svc.cluster.local:9092,kraft-kafka-controller-1.kraft-kafka-controller-headless.kraft.svc.cluster.local:9092,kraft-kafka-controller-2.kraft-kafka-controller-headless.kraft.svc.cluster.local:9092,kraft-kafka-broker-0.kraft-kafka-broker-headless.kraft.svc.cluster.local:9092,kraft-kafka-broker-1.kraft-kafka-broker-headless.kraft.svc.cluster.local:9092,kraft-kafka-broker-2.kraft-kafka-broker-headless.kraft.svc.cluster.local:9092 
    --topic test
# 消费者
kafka-console-consumer.sh 
    --bootstrap-server kraft-kafka.kraft.svc.cluster.local:9092 
    --topic test 
    --from-beginning

6）更新集群

helm upgrade kraft ./kafka -n kraft

7）删去集群

helm uninstall kraft -n kraft

Raft Kafka on k8s 布置实战操作就先到这儿了，有任何疑问也可关注我公众号：大数据与云原生技能分享，进行技能交流，如本篇文章对您有所协助，费事帮忙一键三连（点赞、转发、保藏）~

Raft Kafka on k8s 部署实战操作

1）预备 Kubernetes 集群

2）装置 helm

3）装备 Helm chart

4）运用 Helm 布置 Kafka 集群

5）测验验证

6）更新集群

7）删去集群

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