1、简介
Kafka和zookeeper是两种典型的有状态的应用集群服务。首先kafka和zookeeper都需要存储盘来保存有状态信息；其次kafka和zookeeper每一个实例都需要有对应的实例Id (Kafka需broker.id, zookeeper需要my.id) 来作为集群内部每个成员的标识，集群内节点之间进行内部通信时需要用到这些标识。
对于这类服务的部署，需要解决两个大的问题：一个是状态保存，另一个是集群管理 (多服务实例管理)。kubernetes中提的StatefulSet方便了有状态集群服务在上的部署和管理。通常来说，通过下面三个手段来实现有状态集群服务的部署：
通过Init Container来做集群的初始化工 作。
通过Headless Service来维持集群成员的稳定关系。
通过Persistent Volume和Persistent Volume Claim提供网络存储来持久化数据。
因此，在K8S集群里面部署类似kafka、zookeeper这种有状态的服务，不能使用Deployment，必须使用StatefulSet来部署，有状态简单来说就是需要持久化数据，比如日志、数据库数据、服务状态等。
2、应用场景
稳定的持久化存储，即Pod重新调度后还是能访问到相同的持久化数据，基于PVC来实现。
稳定的网络标志，即Pod重新调度后其PodName和HostName不变，基于Headless Service（即没有Cluster IP的Service）来实现。
有序部署，有序扩展，即Pod是有顺序的，在部署或者扩展的时候要依据定义的顺序依次依次进行（即从0到N-1，在下一个Pod运行之前所有之前的Pod必须都是Running和Ready状态），基于init containers来实现。
有序收缩，有序删除（即从N-1到0）。
3、格式说明
statefulSetName-{0..N-1}.serviceName.namespace.svc.cluster.local，其中：
statefulSetName为StatefulSet的名字。
0..N-1为Pod所在的序号，从0开始到N-1。
serviceName为Headless Service的名字。
namespace为服务所在的namespace，Headless Servic和StatefulSet必须在相同的namespace。
svc.cluster.local为K8S的Cluster Domain集群根域。
4、创建namespace
root@ldap:/opt/k8s-server/kafka/kafka-test/test# Kubectl create ns boss
5、部署zookeeper集群
创建svc
root@ldap:/opt/k8s-server/kafka/kafka-test/test# cat zk-service.yaml
apiVersion: v1
kind: Service
metadata:
name: zk-hs
namespace: boss
labels:
app: zk
spec:
ports:
– port: 2888
name: server
– port: 3888
name: leader-election
clusterIP: None # 使用 clusterIP 的方式，适用于 headless 服务
selector:
app: zk
apiVersion: v1
kind: Service
metadata:
name: zk-cs
namespace: boss
labels:
app: zk
spec:
ports:
– port: 2181
name: client
selector:
app: zk
允许最多1个不可用
apiVersion: policy/v1
kind: PodDisruptionBudget
metadata:
name: zk-pdb
namespace: zookeeper
spec:
selector:
matchLabels:
app: zk
maxUnavailable: 1
部署zookeeper
root@ldap:/opt/k8s-server/kafka/kafka-test/test# vim zk.yaml
apiVersion: apps/v1
kind: StatefulSet
metadata:
name: zk
namespace: boss
spec:
selector:
matchLabels:
app: zk
serviceName: zk-hs
replicas: 3
updateStrategy:
type: RollingUpdate
podManagementPolicy: OrderedReady
template:
metadata:
labels:
app: zk
spec:
affinity:
podAntiAffinity:
requiredDuringSchedulingIgnoredDuringExecution:
– labelSelector:
matchExpressions:
– key: “app”
operator: In
values:
– zk
topologyKey: “kubernetes.io/hostname”
containers:
– name: kubernetes-zookeeper
imagePullPolicy: IfNotPresent
image: “registry.cn-shanghai.aliyuncs.com/study-03/zookeeper:1.0-3.4.10”
resources:
requests:
memory: “1Gi”
cpu: “0.5”
ports:
– containerPort: 2181
name: client
– containerPort: 2888
name: server
– containerPort: 3888
name: leader-election
command:
– sh
– -c
– “start-zookeeper \
–servers=3 \
–data_dir=/var/lib/zookeeper/data \
–data_log_dir=/var/lib/zookeeper/data/log \
–conf_dir=/opt/zookeeper/conf \
–client_port=2181 \
–election_port=3888 \
–server_port=2888 \
–tick_time=2000 \
–init_limit=10 \
–sync_limit=5 \
–heap=512M \
–max_client_cnxns=60 \
–snap_retain_count=3 \
–purge_interval=12 \
–max_session_timeout=40000 \
–min_session_timeout=4000 \
–log_level=INFO”
readinessProbe:
exec:
command:
– sh
– -c
– “zookeeper-ready 2181”
initialDelaySeconds: 10
timeoutSeconds: 5
livenessProbe:
exec:
command:
– sh
– -c
– “zookeeper-ready 2181”
initialDelaySeconds: 10
timeoutSeconds: 5
volumeMounts:
– name: zookeeper-data
mountPath: /bitnami/zookeeper
readinessProbe:
tcpSocket:
port: 2181
initialDelaySeconds: 20
periodSeconds: 10
volumeClaimTemplates:
– metadata:
name: zookeeper-data
spec:
accessModes: [ “ReadWriteOnce” ]
storageClassName: “juicefs-sc” # 根据集群调整
resources:
requests:
storage: 8Gi
6、部署kafka集群
创建svc
root@ldap:/opt/k8s-server/kafka/kafka-test/test# cat kafka-service.yaml
apiVersion: v1
kind: Service
metadata:
name: kafka-svc
namespace: boss
labels:
app: kafka
spec:
type: NodePort # 将服务类型设置为 NodePort
ports:
- port: 9092
name: server
targetPort: 9092 # 映射到 Pod 内部的端口
nodePort: 30092 # 设置一个指定的端口，或者让 Kubernetes 自动分配
selector:
app: kafka
部署kafka
root@ldap:/opt/k8s-server/kafka/kafka-test/test# vim kf.yaml
apiVersion: v1
kind: Service
metadata:
name: kafka-svc
namespace: boss
labels:
app: kafka
spec:
type: NodePort # 将服务类型设置为 NodePort
ports:
- port: 9092
name: server
targetPort: 9092 # 映射到 Pod 内部的端口
nodePort: 30092 # 设置一个指定的端口，或者让 Kubernetes 自动分配
selector:
app: kafka
apiVersion: apps/v1
kind: StatefulSet
metadata:
name: kafka
namespace: boss
spec:
selector:
matchLabels:
app: kafka
serviceName: kafka-svc
replicas: 3
template:
metadata:
labels:
app: kafka
spec:
containers:
– name: k8s-kafka
imagePullPolicy: Always
image: registry.cn-hangzhou.aliyuncs.com/aliyun_0612/kafka:3.7.1
resources:
requests:
memory: “600Mi”
cpu: 500m
ports:
– containerPort: 9092
name: server
command:
– sh
– -c
– “exec /opt/kafka/bin/kafka-server-start.sh /opt/kafka/config/server.properties –override broker.id=${HOSTNAME##*-} \
–override listeners=PLAINTEXT://:9092 \
–override zookeeper.connect=zk-cs.boss.svc.cluster.local:2181 \
–override log.dir=/var/lib/kafka \
–override auto.create.topics.enable=true \
–override auto.leader.rebalance.enable=true \
–override background.threads=10 \
–override compression.type=producer \
–override delete.topic.enable=false \
–override leader.imbalance.check.interval.seconds=300 \
–override leader.imbalance.per.broker.percentage=10 \
–override log.flush.interval.messages=9223372036854775807 \
–override log.flush.offset.checkpoint.interval.ms=60000 \
–override log.flush.scheduler.interval.ms=9223372036854775807 \
–override log.retention.bytes=-1 \
–override log.retention.hours=168 \
–override log.roll.hours=168 \
–override log.roll.jitter.hours=0 \
–override log.segment.bytes=1073741824 \
–override log.segment.delete.delay.ms=60000 \
–override message.max.bytes=1000012 \
–override min.insync.replicas=1 \
–override num.io.threads=8 \
–override num.network.threads=3 \
–override num.recovery.threads.per.data.dir=1 \
–override num.replica.fetchers=1 \
–override offset.metadata.max.bytes=4096 \
–override offsets.commit.required.acks=-1 \
–override offsets.commit.timeout.ms=5000 \
–override offsets.load.buffer.size=5242880 \
–override offsets.retention.check.interval.ms=600000 \
–override offsets.retention.minutes=1440 \
–override offsets.topic.compression.codec=0 \
–override offsets.topic.num.partitions=50 \
–override offsets.topic.replication.factor=3 \
–override offsets.topic.segment.bytes=104857600 \
–override queued.max.requests=500 \
–override quota.consumer.default=9223372036854775807 \
–override quota.producer.default=9223372036854775807 \
–override replica.fetch.min.bytes=1 \
–override replica.fetch.wait.max.ms=500 \
–override replica.high.watermark.checkpoint.interval.ms=5000 \
–override replica.lag.time.max.ms=10000 \
–override replica.socket.receive.buffer.bytes=65536 \
–override replica.socket.timeout.ms=30000 \
–override request.timeout.ms=30000 \
–override socket.receive.buffer.bytes=102400 \
–override socket.request.max.bytes=104857600 \
–override socket.send.buffer.bytes=102400 \
–override unclean.leader.election.enable=true \
–override zookeeper.session.timeout.ms=6000 \
–override zookeeper.set.acl=false \
–override broker.id.generation.enable=true \
–override connections.max.idle.ms=600000 \
–override controlled.shutdown.enable=true \
–override controlled.shutdown.max.retries=3 \
–override controlled.shutdown.retry.backoff.ms=5000 \
–override controller.socket.timeout.ms=30000 \
–override default.replication.factor=1 \
–override fetch.purgatory.purge.interval.requests=1000 \
–override group.max.session.timeout.ms=300000 \
–override group.min.session.timeout.ms=6000 \
–override inter.broker.protocol.version=2.2.0 \
–override log.cleaner.backoff.ms=15000 \
–override log.cleaner.dedupe.buffer.size=134217728 \
–override log.cleaner.delete.retention.ms=86400000 \
–override log.cleaner.enable=true \
–override log.cleaner.io.buffer.load.factor=0.9 \
–override log.cleaner.io.buffer.size=524288 \
–override log.cleaner.io.max.bytes.per.second=1.7976931348623157E308 \
–override log.cleaner.min.cleanable.ratio=0.5 \
–override log.cleaner.min.compaction.lag.ms=0 \
–override log.cleaner.threads=1 \
–override log.cleanup.policy=delete \
–override log.index.interval.bytes=4096 \
–override log.index.size.max.bytes=10485760 \
–override log.message.timestamp.difference.max.ms=9223372036854775807 \
–override log.message.timestamp.type=CreateTime \
–override log.preallocate=false \
–override log.retention.check.interval.ms=300000 \
–override max.connections.per.ip=2147483647 \
–override num.partitions=3 \
–override producer.purgatory.purge.interval.requests=1000 \
–override replica.fetch.backoff.ms=1000 \
–override replica.fetch.max.bytes=1048576 \
–override replica.fetch.response.max.bytes=10485760 \
–override reserved.broker.max.id=1000 “
env:
– name: KAFKA_HEAP_OPTS
value : “-Xmx512M -Xms512M”
– name: KAFKA_OPTS
value: “-Dlogging.level=INFO”
– name: KAFKA_ZOOKEEPER_SESSION_TIMEOUT_MS
value: “6000”
– name: KAFKA_ZOOKEEPER_CONNECTION_TIMEOUT_MS
value: “10000”
volumeMounts:
– name: kafka-data
mountPath: /bitnami/kafka
readinessProbe:
tcpSocket:
port: 9092
initialDelaySeconds: 30
periodSeconds: 10
volumeClaimTemplates:
- metadata:
name: kafka-data
spec:
accessModes: [ “ReadWriteOnce” ]
storageClassName: “juicefs-sc” # 根据集群调整
resources:
requests:
storage: 8Gi
7、查看服务
root@ldap:/opt/k8s-server/kafka/kafka-test/test# kubectl get pod,svc -n boss
NAME READY STATUS RESTARTS AGE
pod/kafka-0 1/1 Running 0 3h19m
pod/kafka-1 1/1 Running 0 3h18m
pod/kafka-2 1/1 Running 0 3h17m
pod/zk-0 1/1 Running 0 3h23m
pod/zk-1 1/1 Running 0 3h22m
pod/zk-2 1/1 Running 0 3h21m
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
service/kafka-svc NodePort 10.96.3.240 9092:30092/TCP 3h19m
service/zk-cs ClusterIP 10.96.0.129 2181/TCP 3h24m
service/zk-hs ClusterIP None 2888/TCP,3888/TCP 3h24m
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