k8s部署custom-metrics服务

custom-metrics部署

   架构分析

        prometheus组件:         负责存储获取到的k8s集群中各种监控数据

        node_exporter组件:        是prometheus安装在每个节点采集数据的agent

        custom-metrics-apiserver组件:   负责接收用户和响应用户发起的rest风格对监控指标操作的请求

        k8s-promethues-adpater组件:     把kube-state-metrics组件返回的数据输出为一个API服务,并集成到k8s的API Server中

        kube-state-metrics组件:        负责完成k8s和prometheus两者之间的数据格式转换.数据转换之后还不能直接通过k8s的API Server获取 还必须经过k8s-promethues-adpater组件的进一步处理

部署步骤

    清单地址:  https://github.com/iKubernetes/k8s-prom

   1.创建名称空间(可选)

---
apiVersion: v1
kind: Namespace
metadata:
  name: prom

View Code

   2.安装node_exporter

   3.安装prometheus

   4.安装kube-state-metrics

   5.安装k8s-promethues-adpater

     参考清单: https://github.com/DirectXMan12/k8s-prometheus-adapter/tree/master/deploy/manifests

apiVersion: v1
kind: ConfigMap
metadata:
  name: adapter-config
  namespace: prom
data:
  config.yaml: |
    rules:
    - seriesQuery: '{__name__=~"^container_.*",container_name!="POD",namespace!="",pod_name!=""}'
      seriesFilters: []
      resources:
        overrides:
          namespace:
            resource: namespace
          pod_name:
            resource: pod
      name:
        matches: ^container_(.*)_seconds_total$
        as: ""
      metricsQuery: sum(rate(<<.Series>>{<<.LabelMatchers>>,container_name!="POD"}[1m])) by (<<.GroupBy>>)
    - seriesQuery: '{__name__=~"^container_.*",container_name!="POD",namespace!="",pod_name!=""}'
      seriesFilters:
      - isNot: ^container_.*_seconds_total$
      resources:
        overrides:
          namespace:
            resource: namespace
          pod_name:
            resource: pod
      name:
        matches: ^container_(.*)_total$
        as: ""
      metricsQuery: sum(rate(<<.Series>>{<<.LabelMatchers>>,container_name!="POD"}[1m])) by (<<.GroupBy>>)
    - seriesQuery: '{__name__=~"^container_.*",container_name!="POD",namespace!="",pod_name!=""}'
      seriesFilters:
      - isNot: ^container_.*_total$
      resources:
        overrides:
          namespace:
            resource: namespace
          pod_name:
            resource: pod
      name:
        matches: ^container_(.*)$
        as: ""
      metricsQuery: sum(<<.Series>>{<<.LabelMatchers>>,container_name!="POD"}) by (<<.GroupBy>>)
    - seriesQuery: '{namespace!="",__name__!~"^container_.*"}'
      seriesFilters:
      - isNot: .*_total$
      resources:
        template: <<.Resource>>
      name:
        matches: ""
        as: ""
      resources:
        template: <<.Resource>>
      name:
        matches: ^(.*)_total$
        as: ""
      metricsQuery: sum(rate(<<.Series>>{<<.LabelMatchers>>}[1m])) by (<<.GroupBy>>)
    - seriesQuery: '{namespace!="",__name__!~"^container_.*"}'
      seriesFilters: []
      resources:
        template: <<.Resource>>
      name:
        matches: ^(.*)_seconds_total$
        as: ""
      metricsQuery: sum(rate(<<.Series>>{<<.LabelMatchers>>}[1m])) by (<<.GroupBy>>)
    resourceRules:
      cpu:
        resources:
          overrides:
            instance:
              resource: node
            namespace:
              resource: namespace
            pod_name:
              resource: pod
        containerLabel: container_name
      memory:
        containerQuery: sum(container_memory_working_set_bytes{<<.LabelMatchers>>}) by (<<.GroupBy>>)
        nodeQuery: sum(container_memory_working_set_bytes{<<.LabelMatchers>>,id='/'}) by (<<.GroupBy>>)
        resources:
          overrides:
            instance:
              resource: node
            namespace:
              resource: namespace
            pod_name:
              resource: pod
        containerLabel: container_name
      window: 1m

custom-metrics-config-map.yaml

apiVersion: apps/v1
kind: Deployment
metadata:
  labels:
    app: custom-metrics-apiserver
  name: custom-metrics-apiserver
  namespace: prom
spec:
  replicas: 1
  selector:
    matchLabels:
      app: custom-metrics-apiserver
  template:
    metadata:
      labels:
        app: custom-metrics-apiserver
      name: custom-metrics-apiserver
    spec:
      serviceAccountName: custom-metrics-apiserver
      containers:
      - name: custom-metrics-apiserver
        image: directxman12/k8s-prometheus-adapter-amd64
        args:
        - --secure-port=6443
        - --tls-cert-file=/var/run/serving-cert/serving.crt
        - --tls-private-key-file=/var/run/serving-cert/serving.key
        - --logtostderr=true
        - --prometheus-url=http://prometheus.prom.svc:9090/
        - --metrics-relist-interval=1m
        - --v=10
        - --config=/etc/adapter/config.yaml
        ports:
        - containerPort: 6443
        volumeMounts:
        - mountPath: /var/run/serving-cert
          name: volume-serving-cert
          readOnly: true
        - mountPath: /etc/adapter/
          name: config
          readOnly: true
        - mountPath: /tmp
          name: tmp-vol
      volumes:
      - name: volume-serving-cert
        secret:
          secretName: cm-adapter-serving-certs
      - name: config
        configMap:
          name: adapter-config
      - name: tmp-vol
        emptyDir: {}

custom-metrics-apiserver-deployment.yaml

  k8s-promethues-adpater默认使用的是http协议 k8s默认采取的是https协议 必须手动把 k8s-promethues-adpater的协议升级为https

用k8s自带的CA创建证书用来和apiserver进行通信
  1. cd /etc/kubernetes/pki
  2. (umask 077;openssl genrsa -out serving.key 2048)
  3.openssl req -new -key serving.key -out serving.csr -subj "/CN=serving"
  4.openssl x509 -req -in serving.csr -CA ./ca.crt -CAkey ./ca.key -CAcreateserial -out serving.crt -days 3650
  5.kubectl create secret generic cm-adapter-serving-certs --from-file=serving.crt=./serving.crt --from-file=serving.key=./serving.key -n prom

 cm-adapter-serving-certs是pod中指定需要加载的secret名称 
  这两个地方的名称必须是一致的

创建k8s信任的证书

 检查部署结果如下:

 6.prometheus集成Grafana

apiVersion: apps/v1beta1
kind: Deployment
metadata:
  name: monitoring-grafana
  namespace: prom
spec:
  replicas: 1
  template:
    metadata:
      labels:
        task: monitoring
        k8s-app: grafana
    spec:
      containers:
      - name: grafana
        image: k8s.gcr.io/heapster-grafana-amd64:v5.0.4
        ports:
        - containerPort: 3000
          protocol: TCP
        volumeMounts:
        - mountPath: /etc/ssl/certs
          name: ca-certificates
          readOnly: true
        - mountPath: /var
          name: grafana-storage
        env:
        - name: GF_SERVER_HTTP_PORT
          value: "3000"
          # The following env variables are required to make Grafana accessible via
          # the kubernetes api-server proxy. On production clusters, we recommend
          # removing these env variables, setup auth for grafana, and expose the grafana
          # service using a LoadBalancer or a public IP.
        - name: GF_AUTH_BASIC_ENABLED
          value: "false"
        - name: GF_AUTH_ANONYMOUS_ENABLED
          value: "true"
        - name: GF_AUTH_ANONYMOUS_ORG_ROLE
          value: Admin
        - name: GF_SERVER_ROOT_URL
          # If you're only using the API Server proxy, set this value instead:
          # value: /api/v1/namespaces/kube-system/services/monitoring-grafana/proxy
          value: /
      volumes:
      - name: ca-certificates
        hostPath:
          path: /etc/ssl/certs
      - name: grafana-storage
        emptyDir: {}
---
apiVersion: v1
kind: Service
metadata:
  labels:
    # For use as a Cluster add-on (https://github.com/kubernetes/kubernetes/tree/master/cluster/addons)
    # If you are NOT using this as an addon, you should comment out this line.
    kubernetes.io/cluster-service: 'true'
    kubernetes.io/name: monitoring-grafana
  name: monitoring-grafana
  namespace: prom
spec:
  # In a production setup, we recommend accessing Grafana through an external Loadbalancer
  # or through a public IP.
  # type: LoadBalancer
  # You could also use NodePort to expose the service at a randomly-generated port
  type: NodePort
  ports:
  - port: 80
    targetPort: 3000
  selector:
    k8s-app: grafana

grafana.yaml

   

 monitoring-grafana这个pod通过prometheus这个svc来访问prometheus提供的服务 所以在grafana在配置数据源的时候可以如下格式

  

 选择一个合适的kubernetes的展示模板    https://grafana.com/grafana/dashboards/

 

 grafana最终展示监控大屏效果