我们在Kafka实战1-全家桶安装中使用Strimzi在K8S上安装了Kafka全家桶，本节我们将使用Strimzi来实现对Kafka集群的监控。

在Strimzi提供的监控方案主要有Prometheus JMX Exporter和Strimzi Kafka Exporter，使用Prometheus将这些指标数据(metrics)读取，然后通过Grafana将Prometheus作为数据源展示出来作为监控。

Strimizi源码可在此页面选择最新版本下载：https://strimzi.io/downloads/，Strimizi源码本例0.19.0版本下载地址：https://github.com/strimzi/strimzi-kafka-operator/releases/download/0.19.0/strimzi-0.19.0.zip

1.Prometheus JMX Exporter

1.1 更新部署Kafka集群

1.1.1 更新部署Kafka集群metrics配置

• 参考例子strimzi-0.19.0/examples/metrics/kafka-metrics.yaml，为我们前面部署的kafka-persistent.yml添加metrics配置：

apiVersion: kafka.strimzi.io/v1beta1kind: Kafkametadata:  name: my-clusterspec:  kafka:    version: 2.5.0    replicas: 3    listeners:      plain: {}      tls: {}    config:      offsets.topic.replication.factor: 3      transaction.state.log.replication.factor: 3      delete.topic.enable: "true"      transaction.state.log.min.isr: 2      log.message.format.version: "2.5"    storage:      type: jbod      volumes:      - id: 0        type: persistent-claim        size: 100Gi        deleteClaim: false        class: fast    metrics:      # Inspired by config from Kafka 2.0.0 example rules:      # https://github.com/prometheus/jmx_exporter/blob/master/example_configs/kafka-2_0_0.yml      lowercaseOutputName: true      rules:        # Special cases and very specific rules        - pattern : kafka.server<>Value          name: kafka_server_$1_$2          type: GAUGE          labels:            clientId: "$3"            topic: "$4"            partition: "$5"        - pattern : kafka.server<>Value          name: kafka_server_$1_$2          type: GAUGE          labels:            clientId: "$3"            broker: "$4:$5"        # Some percent metrics use MeanRate attribute        # Ex) kafka.server<>MeanRate        - pattern: kafka.(w+)<>MeanRate          name: kafka_$1_$2_$3_percent          type: GAUGE        # Generic gauges for percents        - pattern: kafka.(w+)<>Value          name: kafka_$1_$2_$3_percent          type: GAUGE        - pattern: kafka.(w+)<>Value          name: kafka_$1_$2_$3_percent          type: GAUGE          labels:            "$4": "$5"        # Generic per-second counters with 0-2 key/value pairs        - pattern: kafka.(w+)<>Count          name: kafka_$1_$2_$3_total          type: COUNTER          labels:            "$4": "$5"            "$6": "$7"        - pattern: kafka.(w+)<>Count          name: kafka_$1_$2_$3_total          type: COUNTER          labels:            "$4": "$5"        - pattern: kafka.(w+)<>Count          name: kafka_$1_$2_$3_total          type: COUNTER        # Generic gauges with 0-2 key/value pairs        - pattern: kafka.(w+)<>Value          name: kafka_$1_$2_$3          type: GAUGE          labels:            "$4": "$5"            "$6": "$7"        - pattern: kafka.(w+)<>Value          name: kafka_$1_$2_$3          type: GAUGE          labels:            "$4": "$5"        - pattern: kafka.(w+)<>Value          name: kafka_$1_$2_$3          type: GAUGE        # Emulate Prometheus 'Summary' metrics for the exported 'Histogram's.        # Note that these are missing the '_sum' metric!        - pattern: kafka.(w+)<>Count          name: kafka_$1_$2_$3_count          type: COUNTER          labels:            "$4": "$5"            "$6": "$7"        - pattern: kafka.(w+)<>(d+)thPercentile          name: kafka_$1_$2_$3          type: GAUGE          labels:            "$4": "$5"            "$6": "$7"            quantile: "0.$8"        - pattern: kafka.(w+)<>Count          name: kafka_$1_$2_$3_count          type: COUNTER          labels:            "$4": "$5"        - pattern: kafka.(w+)<>(d+)thPercentile          name: kafka_$1_$2_$3          type: GAUGE          labels:            "$4": "$5"            quantile: "0.$6"        - pattern: kafka.(w+)<>Count          name: kafka_$1_$2_$3_count          type: COUNTER        - pattern: kafka.(w+)<>(d+)thPercentile          name: kafka_$1_$2_$3          type: GAUGE          labels:            quantile: "0.$4"  zookeeper:    replicas: 3    storage:      type: persistent-claim      size: 100Gi      deleteClaim: false      class: fast    metrics:      # Inspired by Zookeeper rules      # https://github.com/prometheus/jmx_exporter/blob/master/example_configs/zookeeper.yaml      lowercaseOutputName: true      rules:        # replicated Zookeeper        - pattern: "org.apache.ZooKeeperService<>(w+)"          name: "zookeeper_$2"          type: GAUGE        - pattern: "org.apache.ZooKeeperService<>(w+)"          name: "zookeeper_$3"          type: GAUGE          labels:            replicaId: "$2"        - pattern: "org.apache.ZooKeeperService<>(Packetsw+)"          name: "zookeeper_$4"          type: COUNTER          labels:            replicaId: "$2"            memberType: "$3"        - pattern: "org.apache.ZooKeeperService<>(w+)"          name: "zookeeper_$4"          type: GAUGE          labels:            replicaId: "$2"            memberType: "$3"        - pattern: "org.apache.ZooKeeperService<>(w+)"          name: "zookeeper_$4_$5"          type: GAUGE          labels:            replicaId: "$2"            memberType: "$3"        # standalone Zookeeper        - pattern: "org.apache.ZooKeeperService<>(w+)"          type: GAUGE          name: "zookeeper_$2"        - pattern: "org.apache.ZooKeeperService<>(w+)"          type: GAUGE          name: "zookeeper_$2"  entityOperator:    topicOperator: {}    userOperator: {}

• 更新部署

kubectl apply -f kafka-persistent.yml -n kafka

1.1.2 更新部署Kafka Connect集群metrics配置

• 根据strimzi-0.19.0/examples/metrics/kafka-connect-metrics.yaml修改kafka-connect.yaml，增加metrics配置：

apiVersion: kafka.strimzi.io/v1beta1kind: KafkaConnectmetadata:  name: my-connect-cluster#  annotations:#  # use-connector-resources configures this KafkaConnect#  # to use KafkaConnector resources to avoid#  # needing to call the Connect REST API directly#    strimzi.io/use-connector-resources: "true"spec:  version: 2.5.0  replicas: 1  bootstrapServers: my-cluster-kafka-bootstrap:9093  image: registry.cn-shanghai.aliyuncs.com/wiselyman/kafka-connect-mysql-es:4  tls:    trustedCertificates:      - secretName: my-cluster-cluster-ca-cert        certificate: ca.crt  config:    group.id: connect-cluster    offset.storage.topic: connect-cluster-offsets    config.storage.topic: connect-cluster-configs    status.storage.topic: connect-cluster-status    schema.registry.url: http://my-cluster-kafka-schema-registry-cp-schema-registry:8081    key.converter: org.apache.kafka.connect.storage.StringConverter    value.converter: io.confluent.connect.avro.AvroConverter    value.converter.schema.registry.url: http://my-cluster-kafka-schema-registry-cp-schema-registry:8081  metrics:    # Inspired by kafka-connect rules    # https://github.com/prometheus/jmx_exporter/blob/master/example_configs/kafka-connect.yml    lowercaseOutputName: true    lowercaseOutputLabelNames: true    rules:      #kafka.connect:type=app-info,client-id="{clientid}"      #kafka.consumer:type=app-info,client-id="{clientid}"      #kafka.producer:type=app-info,client-id="{clientid}"      - pattern: 'kafka.(.+)<>start-time-ms'        name: kafka_$1_start_time_seconds        labels:          clientId: "$2"        help: "Kafka $1 JMX metric start time seconds"        type: GAUGE        valueFactor: 0.001      - pattern: 'kafka.(.+)<>(commit-id|version): (.+)'        name: kafka_$1_$3_info        value: 1        labels:          clientId: "$2"          $3: "$4"        help: "Kafka $1 JMX metric info version and commit-id"        type: GAUGE      #kafka.producer:type=producer-topic-metrics,client-id="{clientid}",topic="{topic}"", partition="{partition}"      #kafka.consumer:type=consumer-fetch-manager-metrics,client-id="{clientid}",topic="{topic}"", partition="{partition}"      - pattern: kafka.(.+)<>(.+-total|compression-rate|.+-avg|.+-replica|.+-lag|.+-lead)        name: kafka_$2_$6        labels:          clientId: "$3"          topic: "$4"          partition: "$5"        help: "Kafka $1 JMX metric type $2"        type: GAUGE      #kafka.producer:type=producer-topic-metrics,client-id="{clientid}",topic="{topic}"      #kafka.consumer:type=consumer-fetch-manager-metrics,client-id="{clientid}",topic="{topic}"", partition="{partition}"      - pattern: kafka.(.+)<>(.+-total|compression-rate|.+-avg)        name: kafka_$2_$5        labels:          clientId: "$3"          topic: "$4"        help: "Kafka $1 JMX metric type $2"        type: GAUGE      #kafka.connect:type=connect-node-metrics,client-id="{clientid}",node-id="{nodeid}"      #kafka.consumer:type=consumer-node-metrics,client-id=consumer-1,node-id="{nodeid}"      - pattern: kafka.(.+)<>(.+-total|.+-avg)        name: kafka_$2_$5        labels:          clientId: "$3"          nodeId: "$4"        help: "Kafka $1 JMX metric type $2"        type: UNTYPED      #kafka.connect:type=kafka-metrics-count,client-id="{clientid}"      #kafka.consumer:type=consumer-fetch-manager-metrics,client-id="{clientid}"      #kafka.consumer:type=consumer-coordinator-metrics,client-id="{clientid}"      #kafka.consumer:type=consumer-metrics,client-id="{clientid}"      - pattern: kafka.(.+)<>(.+-total|.+-avg|.+-bytes|.+-count|.+-ratio|.+-age|.+-flight|.+-threads|.+-connectors|.+-tasks|.+-ago)        name: kafka_$2_$4        labels:          clientId: "$3"        help: "Kafka $1 JMX metric type $2"        type: GAUGE      #kafka.connect:type=connector-task-metrics,connector="{connector}",task="{task}<> status"      - pattern: 'kafka.connect<>status: ([a-z-]+)'        name: kafka_connect_connector_status        value: 1        labels:          connector: "$1"          task: "$2"          status: "$3"        help: "Kafka Connect JMX Connector status"        type: GAUGE      #kafka.connect:type=task-error-metrics,connector="{connector}",task="{task}"      #kafka.connect:type=source-task-metrics,connector="{connector}",task="{task}"      #kafka.connect:type=sink-task-metrics,connector="{connector}",task="{task}"      #kafka.connect:type=connector-task-metrics,connector="{connector}",task="{task}"      - pattern: kafka.connect<>(.+-total|.+-count|.+-ms|.+-ratio|.+-avg|.+-failures|.+-requests|.+-timestamp|.+-logged|.+-errors|.+-retries|.+-skipped)        name: kafka_connect_$1_$4        labels:          connector: "$2"          task: "$3"        help: "Kafka Connect JMX metric type $1"        type: GAUGE      #kafka.connect:type=connector-metrics,connector="{connector}"      #kafka.connect:type=connect-worker-metrics,connector="{connector}"      - pattern: kafka.connect<>([a-z-]+)        name: kafka_connect_worker_$2        labels:          connector: "$1"        help: "Kafka Connect JMX metric $1"        type: GAUGE      #kafka.connect:type=connect-worker-metrics      - pattern: kafka.connect<>([a-z-]+)        name: kafka_connect_worker_$1        help: "Kafka Connect JMX metric worker"        type: GAUGE      #kafka.connect:type=connect-worker-rebalance-metrics      - pattern: kafka.connect<>([a-z-]+)        name: kafka_connect_worker_rebalance_$1        help: "Kafka Connect JMX metric rebalance information"        type: GAUGE

• 更新部署

kubectl apply -f kafka-connect.yml -n kafka

1.2 配置安装Promethueus

1.2.1 安装Promethueus Operator

• 安装Promethueus Operator，地址：https://operatorhub.io/operator/prometheus

kubectl create -f https://operatorhub.io/install/prometheus.yamlkubectl get csv -n operators

1.2.2 配置安装Promethueus Server

• 对于目录strimzi-0.19.0/examples/metrics/prometheus-install的文件。
• prometheus.yaml：namespace修改为default，Promethueus将安装到default命名空间

apiVersion: rbac.authorization.k8s.io/v1kind: ClusterRolemetadata:  name: prometheus-server  labels:    app: strimzirules:  - apiGroups: [""]    resources:      - nodes      - nodes/proxy      - services      - endpoints      - pods    verbs: ["get", "list", "watch"]  - apiGroups:      - extensions    resources:      - ingresses    verbs: ["get", "list", "watch"]  - nonResourceURLs: ["/metrics"]    verbs: ["get"]---apiVersion: v1kind: ServiceAccountmetadata:  name: prometheus-server  labels:    app: strimzi---apiVersion: rbac.authorization.k8s.io/v1kind: ClusterRoleBindingmetadata:  name: prometheus-server  labels:    app: strimziroleRef:  apiGroup: rbac.authorization.k8s.io  kind: ClusterRole  name: prometheus-serversubjects:  - kind: ServiceAccount    name: prometheus-server    namespace: default---apiVersion: monitoring.coreos.com/v1kind: Prometheusmetadata:  name: prometheus  labels:    app: strimzispec:  replicas: 1  serviceAccountName: prometheus-server  serviceMonitorSelector:    matchLabels:      app: strimzi  podMonitorSelector:    matchLabels:      app: strimzi  resources:    requests:      memory: 400Mi  enableAdminAPI: false  ruleSelector:    matchLabels:      role: alert-rules      app: strimzi  alerting:    alertmanagers:    - namespace: default      name: alertmanager      port: alertmanager  additionalScrapeConfigs:    name: additional-scrape-configs    key: prometheus-additional.yaml

• strimzi-pod-monitor.yaml：

将namespaceSelector.matchNames修改为kafka，我们需要监控的命名空间为kafka

apiVersion: monitoring.coreos.com/v1kind: PodMonitormetadata:  name: cluster-operator-metrics  labels:    app: strimzispec:  selector:    matchLabels:      strimzi.io/kind: cluster-operator  namespaceSelector:    matchNames:      - kafka  podMetricsEndpoints:  - path: /metrics    port: http---apiVersion: monitoring.coreos.com/v1kind: PodMonitormetadata:  name: entity-operator-metrics  labels:    app: strimzispec:  selector:    matchLabels:      app.kubernetes.io/name: entity-operator  namespaceSelector:    matchNames:      - kafka  podMetricsEndpoints:  - path: /metrics    port: healthcheck---apiVersion: monitoring.coreos.com/v1kind: PodMonitormetadata:  name: bridge-metrics  labels:    app: strimzispec:  selector:    matchLabels:      strimzi.io/kind: KafkaBridge  namespaceSelector:    matchNames:      - kafka  podMetricsEndpoints:  - path: /metrics    port: rest-api---apiVersion: monitoring.coreos.com/v1kind: PodMonitormetadata:  name: kafka-metrics  labels:    app: strimzispec:  selector:    matchExpressions:      - key: "strimzi.io/kind"        operator: In        values: ["Kafka", "KafkaConnect"]  namespaceSelector:    matchNames:      - kafka  podMetricsEndpoints:  - path: /metrics    port: tcp-prometheus    relabelings:    - separator: ;      regex: __meta_kubernetes_pod_label_(.+)      replacement: $1      action: labelmap    - sourceLabels: [__meta_kubernetes_namespace]      separator: ;      regex: (.*)      targetLabel: namespace      replacement: $1      action: replace    - sourceLabels: [__meta_kubernetes_pod_name]      separator: ;      regex: (.*)      targetLabel: kubernetes_pod_name      replacement: $1      action: replace    - sourceLabels: [__meta_kubernetes_pod_node_name]      separator: ;      regex: (.*)      targetLabel: node_name      replacement: $1      action: replace    - sourceLabels: [__meta_kubernetes_pod_host_ip]      separator: ;      regex: (.*)      targetLabel: node_ip      replacement: $1      action: replace    

• 通过prometheus-additional.yaml创建Secret

kubectl create secret generic additional-scrape-configs --from-file=prometheus-additional.yaml

此时prometheus.yaml的additionalScrapeConfigs属性使用这个Secret的名称additional-scrape-configs

• 部署

kubectl apply -f strimzi-pod-monitor.yamlkubectl apply -f prometheus-rules.yamlkubectl apply -f prometheus.yaml

1.3 安装配置Grafana

1.3.1 安装访问Grafana

• 安装Grafana：strimzi-0.19.0/examples/metrics/grafana-install/grafana.yaml

kubectl apply -f grafana.yaml

• 代理访问grafana

kubectl port-forward svc/grafana 3000:3000

http://localhost:3000，默认账号密码:admin/admin

1.3.2 添加Prometheus数据源

• Add data source -> Prometheus->http://prometheus-operated:9090->Save & Test

1.3.3 导入监控的dashboards

• 健康的dashboard配置都在strimzi-0.19.0/examples/metrics/grafana-dashboards下，可以通过grafana导入。
• 点击左侧➕->Import，可从文件夹导入Dashboardstrimzi-0.19.0/examples/metrics/grafana-dashboards的json文件，或者直接粘贴：

2.Strimzi Kafka Exporter

2.1 更新部署Kafka集群配置

• Kafka Exporter监控，在我们的kafka-persistent.yml尾部添加

  kafkaExporter:    topicRegex: ".*"    groupRegex: ".*"

• 更新部署Kafka

kubectl apply -f kafka-persistent.yml -n kafka

2.2 配置监控dashboard

• grafana导入strimzi-0.19.0/examples/metrics/grafana-dashboards/strimzi-kafka-exporter.json