Prometheus神器之监控K8s集群

Prometheus 简介

Prometheus是SoundCloud开源的一款开源软件。它的实现参考了Google内部的监控实现，与源自Google的Kubernetes结合起来非常合适。另外相比influxdb的方案，性能更加突出，而且还内置了报警功能。它针对大规模的集群环境设计了拉取式的数据采集方式，你只需要在你的应用里面实现一个metrics接口，然后把这个接口告诉Prometheus就可以完成数据采集了。

安装Prometheus

首先我们使用ConfigMap的形式来设置Prometheus的配置文件，如下

代码语言：javascript复制

apiVersion: v1
kind: ConfigMap
metadata:
  name: prometheus-configuration
  labels:
    app.kubernetes.io/name: prometheus
    app.kubernetes.io/part-of: ingress-nginx
    name: prometheus-configuration
  namespace: ingress-nginx
data:
  prometheus.yml: |-
    global:
      scrape_interval: 10s
    scrape_configs:
    - job_name: 'ingress-nginx-endpoints'
      kubernetes_sd_configs:
      - role: pod
        namespaces:
          names:
          - ingress-nginx
      relabel_configs:
      - source_labels: [__meta_kubernetes_pod_annotation_prometheus_io_scrape]
        action: keep
        regex: true
      - source_labels: [__meta_kubernetes_pod_annotation_prometheus_io_scheme]
        action: replace
        target_label: __scheme__
        regex: (https?)
      - source_labels: [__meta_kubernetes_pod_annotation_prometheus_io_path]
        action: replace
        target_label: __metrics_path__
        regex: (. )
      - source_labels: [__address__, __meta_kubernetes_pod_annotation_prometheus_io_port]
        action: replace
        target_label: __address__
        regex: ([^:] )(?::d )?;(d )
        replacement: $1:$2
      - source_labels: [__meta_kubernetes_service_name]
        regex: prometheus-server
        action: drop
---

将以上配置文件保存为configuration.yaml，然后执行命令：

代码语言：javascript复制

$ kubectl apply -f configuration.yaml
namespace "ingress-nginx" created
configmap "prometheus-configuration" created

通过Deployment部署Prometheus,yaml文件如下：

代码语言：javascript复制

---
apiVersion: rbac.authorization.k8s.io/v1beta1
kind: ClusterRole
metadata:
  name: prometheus
rules:
  - apiGroups: [""] # "" indicates the core API group
    resources:
      - nodes
      - nodes/proxy
      - services
      - endpoints
      - pods
    verbs:
      - get
      - watch
      - list
  - apiGroups:
      - extensions
    resources:
      - ingresses
    verbs:
      - get
      - watch
      - list
  - nonResourceURLs: ["/metrics"]
    verbs:
      - get
---
apiVersion: v1
kind: ServiceAccount
metadata:
  name: prometheus
  namespace: ingress-nginx
  labels:
    app: prometheus
---
apiVersion: rbac.authorization.k8s.io/v1beta1
kind: ClusterRoleBinding
metadata:
  name: prometheus
subjects:
  - kind: ServiceAccount
    name: prometheus
    namespace: ingress-nginx
roleRef:
  kind: ClusterRole
  name: prometheus
  apiGroup: rbac.authorization.k8s.io
---
apiVersion: v1
kind: ConfigMap
metadata:
  name: prometheus-conf
  namespace: ingress-nginx
  labels:
    app: prometheus
data:
  prometheus.yml: |-
    # my global config
    global:
      scrape_interval:     15s # Set the scrape interval to every 15 seconds. Default is every 1 minute.
      evaluation_interval: 15s # Evaluate rules every 15 seconds. The default is every 1 minute.
      # scrape_timeout is set to the global default (10s).

    # Alertmanager configuration
    alerting:
      alertmanagers:
      - static_configs:
        - targets:
          # - alertmanager:9093

    # Load rules once and periodically evaluate them according to the global 'evaluation_interval'.
    rule_files:
      # - "first_rules.yml"
      # - "second_rules.yml"

    # A scrape configuration containing exactly one endpoint to scrape:
    # Here it's Prometheus itself.
    scrape_configs:
      # The job name is added as a label `job=<job_name>` to any timeseries scraped from this config.
      - job_name: 'prometheus'

        # metrics_path defaults to '/metrics'
        # scheme defaults to 'http'.

        static_configs:
          - targets: ['localhost:9090']
      - job_name: 'grafana'
        static_configs:
          - targets:
              - 'grafana.ingress-nginx:3000'

      - job_name: 'kubernetes-apiservers'

        kubernetes_sd_configs:
        - role: endpoints

        # Default to scraping over https. If required, just disable this or change to
        # `http`.
        scheme: https

        # This TLS & bearer token file config is used to connect to the actual scrape
        # endpoints for cluster components. This is separate to discovery auth
        # configuration because discovery & scraping are two separate concerns in
        # Prometheus. The discovery auth config is automatic if Prometheus runs inside
        # the cluster. Otherwise, more config options have to be provided within the
        # <kubernetes_sd_config>.
        tls_config:
          ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crt
          # If your node certificates are self-signed or use a different CA to the
          # master CA, then disable certificate verification below. Note that
          # certificate verification is an integral part of a secure infrastructure
          # so this should only be disabled in a controlled environment. You can
          # disable certificate verification by uncommenting the line below.
          #
          # insecure_skip_verify: true
        bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token

        # Keep only the default/kubernetes service endpoints for the https port. This
        # will add targets for each API server which Kubernetes adds an endpoint to
        # the default/kubernetes service.
        relabel_configs:
        - source_labels: [__meta_kubernetes_namespace, __meta_kubernetes_service_name, __meta_kubernetes_endpoint_port_name]
          action: keep
          regex: default;kubernetes;https

      # Scrape config for nodes (kubelet).
      #
      # Rather than connecting directly to the node, the scrape is proxied though the
      # Kubernetes apiserver.  This means it will work if Prometheus is running out of
      # cluster, or can't connect to nodes for some other reason (e.g. because of
      # firewalling).
      - job_name: 'kubernetes-nodes'

        # Default to scraping over https. If required, just disable this or change to
        # `http`.
        scheme: https

        # This TLS & bearer token file config is used to connect to the actual scrape
        # endpoints for cluster components. This is separate to discovery auth
        # configuration because discovery & scraping are two separate concerns in
        # Prometheus. The discovery auth config is automatic if Prometheus runs inside
        # the cluster. Otherwise, more config options have to be provided within the
        # <kubernetes_sd_config>.
        tls_config:
          ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crt
        bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token

        kubernetes_sd_configs:
        - role: node

        relabel_configs:
        - action: labelmap
          regex: __meta_kubernetes_node_label_(. )
        - target_label: __address__
          replacement: kubernetes.default.svc:443
        - source_labels: [__meta_kubernetes_node_name]
          regex: (. )
          target_label: __metrics_path__
          replacement: /api/v1/nodes/${1}/proxy/metrics

      # Scrape config for Kubelet cAdvisor.
      #
      # This is required for Kubernetes 1.7.3 and later, where cAdvisor metrics
      # (those whose names begin with 'container_') have been removed from the
      # Kubelet metrics endpoint.  This job scrapes the cAdvisor endpoint to
      # retrieve those metrics.
      #
      # In Kubernetes 1.7.0-1.7.2, these metrics are only exposed on the cAdvisor
      # HTTP endpoint; use "replacement: /api/v1/nodes/${1}:4194/proxy/metrics"
      # in that case (and ensure cAdvisor's HTTP server hasn't been disabled with
      # the --cadvisor-port=0 Kubelet flag).
      #
      # This job is not necessary and should be removed in Kubernetes 1.6 and
      # earlier versions, or it will cause the metrics to be scraped twice.
      - job_name: 'kubernetes-cadvisor'

        # Default to scraping over https. If required, just disable this or change to
        # `http`.
        scheme: https

        # This TLS & bearer token file config is used to connect to the actual scrape
        # endpoints for cluster components. This is separate to discovery auth
        # configuration because discovery & scraping are two separate concerns in
        # Prometheus. The discovery auth config is automatic if Prometheus runs inside
        # the cluster. Otherwise, more config options have to be provided within the
        # <kubernetes_sd_config>.
        tls_config:
          ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crt
        bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token

        kubernetes_sd_configs:
        - role: node

        relabel_configs:
        - action: labelmap
          regex: __meta_kubernetes_node_label_(. )
        - target_label: __address__
          replacement: kubernetes.default.svc:443
        - source_labels: [__meta_kubernetes_node_name]
          regex: (. )
          target_label: __metrics_path__
          replacement: /api/v1/nodes/${1}/proxy/metrics/cadvisor

      # Scrape config for service endpoints.
      #
      # The relabeling allows the actual service scrape endpoint to be configured
      # via the following annotations:
      #
      # * `prometheus.io/scrape`: Only scrape services that have a value of `true`
      # * `prometheus.io/scheme`: If the metrics endpoint is secured then you will need
      # to set this to `https` & most likely set the `tls_config` of the scrape config.
      # * `prometheus.io/path`: If the metrics path is not `/metrics` override this.
      # * `prometheus.io/port`: If the metrics are exposed on a different port to the
      # service then set this appropriately.
      - job_name: 'kubernetes-service-endpoints'

        kubernetes_sd_configs:
        - role: endpoints

        relabel_configs:
        - source_labels: [__meta_kubernetes_service_annotation_prometheus_io_scrape]
          action: keep
          regex: true
        - source_labels: [__meta_kubernetes_service_annotation_prometheus_io_scheme]
          action: replace
          target_label: __scheme__
          regex: (https?)
        - source_labels: [__meta_kubernetes_service_annotation_prometheus_io_path]
          action: replace
          target_label: __metrics_path__
          regex: (. )
        - source_labels: [__address__, __meta_kubernetes_service_annotation_prometheus_io_port]
          action: replace
          target_label: __address__
          regex: ([^:] )(?::d )?;(d )
          replacement: $1:$2
        - action: labelmap
          regex: __meta_kubernetes_service_label_(. )
        - source_labels: [__meta_kubernetes_namespace]
          action: replace
          target_label: kubernetes_namespace
        - source_labels: [__meta_kubernetes_service_name]
          action: replace
          target_label: kubernetes_name

      # Example scrape config for probing services via the Blackbox Exporter.
      #
      # The relabeling allows the actual service scrape endpoint to be configured
      # via the following annotations:
      #
      # * `prometheus.io/probe`: Only probe services that have a value of `true`
      - job_name: 'kubernetes-services'

        metrics_path: /probe
        params:
          module: [http_2xx]

        kubernetes_sd_configs:
        - role: service

        relabel_configs:
        - source_labels: [__meta_kubernetes_service_annotation_prometheus_io_probe]
          action: keep
          regex: true
        - source_labels: [__address__]
          target_label: __param_target
        - target_label: __address__
          replacement: blackbox-exporter.example.com:9115
        - source_labels: [__param_target]
          target_label: instance
        - action: labelmap
          regex: __meta_kubernetes_service_label_(. )
        - source_labels: [__meta_kubernetes_namespace]
          target_label: kubernetes_namespace
        - source_labels: [__meta_kubernetes_service_name]
          target_label: kubernetes_name

      # Example scrape config for probing ingresses via the Blackbox Exporter.
      #
      # The relabeling allows the actual ingress scrape endpoint to be configured
      # via the following annotations:
      #
      # * `prometheus.io/probe`: Only probe services that have a value of `true`
      - job_name: 'kubernetes-ingresses'

        metrics_path: /probe
        params:
          module: [http_2xx]

        kubernetes_sd_configs:
          - role: ingress

        relabel_configs:
          - source_labels: [__meta_kubernetes_ingress_annotation_prometheus_io_probe]
            action: keep
            regex: true
          - source_labels: [__meta_kubernetes_ingress_scheme,__address__,__meta_kubernetes_ingress_path]
            regex: (. );(. );(. )
            replacement: ${1}://${2}${3}
            target_label: __param_target
          - target_label: __address__
            replacement: blackbox-exporter.example.com:9115
          - source_labels: [__param_target]
            target_label: instance
          - action: labelmap
            regex: __meta_kubernetes_ingress_label_(. )
          - source_labels: [__meta_kubernetes_namespace]
            target_label: kubernetes_namespace
          - source_labels: [__meta_kubernetes_ingress_name]
            target_label: kubernetes_name

      # Example scrape config for pods
      #
      # The relabeling allows the actual pod scrape endpoint to be configured via the
      # following annotations:
      #
      # * `prometheus.io/scrape`: Only scrape pods that have a value of `true`
      # * `prometheus.io/path`: If the metrics path is not `/metrics` override this.
      # * `prometheus.io/port`: Scrape the pod on the indicated port instead of the
      # pod's declared ports (default is a port-free target if none are declared).
      - job_name: 'kubernetes-pods'

        kubernetes_sd_configs:
        - role: pod

        relabel_configs:
        - source_labels: [__meta_kubernetes_pod_annotation_prometheus_io_scrape]
          action: keep
          regex: true
        - source_labels: [__meta_kubernetes_pod_annotation_prometheus_io_path]
          action: replace
          target_label: __metrics_path__
          regex: (. )
        - source_labels: [__address__, __meta_kubernetes_pod_annotation_prometheus_io_port]
          action: replace
          regex: ([^:] )(?::d )?;(d )
          replacement: $1:$2
          target_label: __address__
        - action: labelmap
          regex: __meta_kubernetes_pod_label_(. )
        - source_labels: [__meta_kubernetes_namespace]
          action: replace
          target_label: kubernetes_namespace
        - source_labels: [__meta_kubernetes_pod_name]
          action: replace
          target_label: kubernetes_pod_name
---
apiVersion: v1
kind: ConfigMap
metadata:
  name: prometheus-rules
  namespace: ingress-nginx
  labels:
    app: prometheus
data:
  cpu-usage.rule: |
    groups:
      - name: NodeCPUUsage
        rules:
          - alert: NodeCPUUsage
            expr: (100 - (avg by (instance) (irate(node_cpu{name="node-exporter",mode="idle"}[5m])) * 100)) > 75
            for: 2m
            labels:
              severity: "page"
            annotations:
              summary: "{{$labels.instance}}: High CPU usage detected"
              description: "{{$labels.instance}}: CPU usage is above 75% (current value is: {{ $value }})"

---
kind: Deployment
apiVersion: apps/v1beta2
metadata:
  labels:
    app: prometheus
  name: prometheus
  namespace: ingress-nginx
spec:
  replicas: 1
  revisionHistoryLimit: 10
  selector:
    matchLabels:
      app: prometheus
  template:
    metadata:
      labels:
        app: prometheus
    spec:
      serviceAccountName: prometheus
      securityContext:
        runAsUser: 65534
        fsGroup: 65534
      containers:
        - name: prometheus
          image: prom/prometheus:latest
          volumeMounts:
            - mountPath: /etc/prometheus/prometheus.yml
              name: prometheus-conf-volume
              subPath: prometheus.yml
            - mountPath: /etc/prometheus/rules
              name: prometheus-rules-volume
          ports:
            - containerPort: 9090
              protocol: TCP
      volumes:
        - name: prometheus-conf-volume
          configMap:
            name: prometheus-conf
        - name: prometheus-rules-volume
          configMap:
            name: prometheus-rules
      tolerations:
        - key: node-role.kubernetes.io/master
          effect: NoSchedule

---
kind: Service
apiVersion: v1
metadata:
  annotations:
    prometheus.io/scrape: 'true'
  labels:
    app: prometheus
  name: prometheus-service
  namespace: ingress-nginx
spec:
  ports:
    - port: 9090
      targetPort: 9090
  selector:
    app: prometheus
  type: NodePort

将以上文件保存为prometheus.yaml，然后执行命令：

代码语言：javascript复制

$ kubectl apply -f prometheus.yaml
clusterrole "prometheus" created
serviceaccount "prometheus" created
clusterrolebinding "prometheus" created
configmap "prometheus-conf" created
configmap "prometheus-rules" created
deployment "prometheus" created
service "prometheus-service" created

部署node-exporter，为了能够收集每个节点的信息，所以我们这里使用DaemonSet的形式部署：

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kind: DaemonSet
apiVersion: apps/v1beta2
metadata: 
  labels:
    app: node-exporter
  name: node-exporter
  namespace: ingress-nginx
spec:
  revisionHistoryLimit: 10
  selector:
    matchLabels:
      app: node-exporter
  template:
    metadata:
      labels:
        app: node-exporter
    spec:
      containers:
        - name: node-exporter
          image: prom/node-exporter:v0.16.0
          ports:
            - containerPort: 9100
              protocol: TCP
              name: http
      hostNetwork: true
      hostPID: true
      tolerations:
        - effect: NoSchedule
          operator: Exists

---
kind: Service
apiVersion: v1
metadata:
  labels:
    app: node-exporter
  name: node-exporter-service
  namespace: ingress-nginx
spec:
  ports:
    - name: http
      port: 9100
      nodePort: 31672
      protocol: TCP
  type: NodePort
  selector:
    app: node-exporter

将以上文件保存为node-exporter.yaml，然后执行命令：

代码语言：javascript复制

$ kubectl apply -f node-exporter.yaml
daemonset "node-exporter" created
service "node-exporter-service" created

接下来暴露服务以便可以访问Prometheus的UI界面，查看NodePort：

代码语言：javascript复制

[root@dtdream-dtwarebase-prod-k8s-01 monitoring]# kubectl  -s10.90.2.100:8080 -ningress-nginx get svc,po -owide
NAME                        TYPE       CLUSTER-IP       EXTERNAL-IP   PORT(S)          AGE       SELECTOR
svc/node-exporter-service   NodePort   10.254.208.254   <none>        9100:31672/TCP   55s       app=node-exporter
svc/prometheus-service      NodePort   10.254.187.175   <none>        9090:25759/TCP   3m        app=prometheus

NAME                             READY     STATUS             RESTARTS   AGE       IP             NODE
po/node-exporter-b47ch           1/1       Running            0          54s       10.90.2.102    10.90.2.102
po/node-exporter-q88pp           1/1       Running            0          54s       10.90.2.100    10.90.2.100
po/prometheus-7b7fd77c44-7cf6z   1/1       Running            0          3m        172.17.21.28   10.90.2.101

然后用浏览器访问http://10.90.2.101:9090就可以访问到Prometheus的界面了。

可以切换到Status下面的targets查看我们采集的数据是否正常：

可以根据targets下面的提示信息对采集失败的数据进行修正。

查询监控数据

Prometheus提供了API的方式进行数据查询，同样可以使用query语言进行复杂的查询任务，在上面的WEB界面上提供了基本的查询和图形化的展示功能。

比如查询每个POD的CPU使用情况，查询条件如下：

代码语言：javascript复制

sum by (pod_name)( rate(container_cpu_usage_seconds_total{image!="", pod_name!=""}[1m] ) )

注意其中的pod_name和image要根据自己采集的数据进行区分。

安装Grafana

Prometheus以及获取到了我们采集的数据，现在我们需要一个更加强大的图标展示工具，毫无疑问选择grafana，同样的，在Kubernetes环境下面进行安装，yaml文件如下:

代码语言：javascript复制

apiVersion: extensions/v1beta1
kind: Deployment
metadata:
  labels:
    app.kubernetes.io/name: grafana
    app.kubernetes.io/part-of: ingress-nginx

  name: grafana
  namespace: ingress-nginx
spec:
  selector:
    matchLabels:
      app.kubernetes.io/name: grafana
      app.kubernetes.io/part-of: ingress-nginx
  strategy:
    rollingUpdate:
      maxSurge: 1
      maxUnavailable: 1
    type: RollingUpdate
  template:
    metadata:
      labels:
        app.kubernetes.io/name: grafana
        app.kubernetes.io/part-of: ingress-nginx
    spec:
      containers:
        - image: grafana/grafana
          name: grafana
          ports:
            - containerPort: 3000
              protocol: TCP
          resources:
            limits:
              cpu: 500m
              memory: 2500Mi
            requests:
              cpu: 100m
              memory: 100Mi
          volumeMounts:
            - mountPath: /var/lib/grafana
              name: data
      restartPolicy: Always
      volumes:
        - emptyDir: {}
          name: data

---
apiVersion: v1
kind: Service
metadata:
  name: grafana
  namespace: ingress-nginx
  labels:
    app.kubernetes.io/name: grafana
    app.kubernetes.io/part-of: ingress-nginx

spec:
  ports:
    - port: 3000
      protocol: TCP
      targetPort: 3000
  selector:
    app.kubernetes.io/name: grafana
    app.kubernetes.io/part-of: ingress-nginx
  type: NodePort

---

将以上文件保存为grafana.yaml，然后执行命令：

代码语言：javascript复制

$ kubectl apply -f grafana.yaml
deployment "grafana" created
service "grafana" created

可以选择使用ingress将服务暴露在外网进行访问。 访问grafanaWEB界面，我这里就直接使用的Nodeport。

查看grafana访问端口

代码语言：javascript复制

$ kubectl  -ningress-nginx get svc,po|grep grafana
svc/grafana                 NodePort   10.254.86.182    <none>        3000:7006/TCP    2m
po/grafana-85fbffb76f-x6hqw      1/1       Running            0          2m

访问http://10.90.2.101:7006

将我们上面的Prometheus添加到grafana数据源中去。

然后添加我们的Dashboard，可以使用https://grafana.com/dashboards/162，可以下载该页面的dashboard的json文件，然后直接导入到grafana中去，但是需要注意其中的一些参数，需要根据prometheus中采集到实际数据进行填写，比如我们这里采集到容器名是name，而不是io_kubernetes_container_name,最终展示界面如下：

上面用的yaml文件可以到github上查看https://github.com/jcops/k8s-yaml/tree/master/monitoring

大数据可视交互系统

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