Prometheus神器之监控K8s集群

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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

apiVersion: v1kind: ConfigMapmetadata:  name: prometheus-configuration  labels:    app.kubernetes.io/name: prometheus    app.kubernetes.io/part-of: ingress-nginx    name: prometheus-configuration  namespace: ingress-nginxdata:  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:

$ kubectl apply -f configuration.yamlnamespace "ingress-nginx" createdconfigmap "prometheus-configuration" created

通过Deployment部署Prometheus,yaml文件如下:

---apiVersion: rbac.authorization.k8s.io/v1beta1kind: ClusterRolemetadata:  name: prometheusrules:  - 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: v1kind: ServiceAccountmetadata:  name: prometheus  namespace: ingress-nginx  labels:    app: prometheus---apiVersion: rbac.authorization.k8s.io/v1beta1kind: ClusterRoleBindingmetadata:  name: prometheussubjects:  - kind: ServiceAccount    name: prometheus    namespace: ingress-nginxroleRef:  kind: ClusterRole  name: prometheus  apiGroup: rbac.authorization.k8s.io---apiVersion: v1kind: ConfigMapmetadata:  name: prometheus-conf  namespace: ingress-nginx  labels:    app: prometheusdata:  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:$2          target_label: __address__        - action: labelmap          regex: __meta_kubernetes_pod_label_(.+)        - source_labels: [__meta_kubernetes_namespace]          action: replace          target_label: kubernetes_namespace        - source_labels: [__meta_kubernetes_pod_name]          action: replace          target_label: kubernetes_pod_name---apiVersion: v1kind: ConfigMapmetadata:  name: prometheus-rules  namespace: ingress-nginx  labels:    app: prometheusdata:  cpu-usage.rule: |    groups:      - name: NodeCPUUsage        rules:          - alert: NodeCPUUsage            expr: (100 - (avg by (instance) (irate(node_cpu{name="node-exporter",mode="idle"}[5m])) * 100)) > 75            for: 2m            labels:              severity: "page"            annotations:              summary: "{{$labels.instance}}: High CPU usage detected"              description: "{{$labels.instance}}: CPU usage is above 75% (current value is: {{ $value }})"---kind: DeploymentapiVersion: apps/v1beta2metadata:  labels:    app: prometheus  name: prometheus  namespace: ingress-nginxspec:  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: ServiceapiVersion: v1metadata:  annotations:    prometheus.io/scrape: 'true'  labels:    app: prometheus  name: prometheus-service  namespace: ingress-nginxspec:  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:

$ kubectl apply -f prometheus.yamlclusterrole "prometheus" createdserviceaccount "prometheus" createdclusterrolebinding "prometheus" createdconfigmap "prometheus-conf" createdconfigmap "prometheus-rules" createddeployment "prometheus" createdservice "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:

kind: DaemonSetapiVersion: apps/v1beta2metadata:   labels:    app: node-exporter  name: node-exporter  namespace: ingress-nginxspec:  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: ServiceapiVersion: v1metadata:  labels:    app: node-exporter  name: node-exporter-service  namespace: ingress-nginxspec:  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:

$ kubectl apply -f node-exporter.yamldaemonset "node-exporter" createdservice "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:

[root@dtdream-dtwarebase-prod-k8s-01 monitoring]# kubectl  -s10.90.2.100:8080 -ningress-nginx get svc,po -owideNAME                        TYPE       CLUSTER-IP       EXTERNAL-IP   PORT(S)          AGE       SELECTORsvc/node-exporter-service   NodePort   10.254.208.254   <none>        9100:31672/TCP   55s       app=node-exportersvc/prometheus-service      NodePort   10.254.187.175   <none>        9090:25759/TCP   3m        app=prometheusNAME                             READY     STATUS             RESTARTS   AGE       IP             NODEpo/node-exporter-b47ch           1/1       Running            0          54s       10.90.2.102    10.90.2.102po/node-exporter-q88pp           1/1       Running            0          54s       10.90.2.100    10.90.2.100po/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。

image

可以切换到Status下面的targets查看我们采集的数据是否正常:

image

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:

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

注意其中的pod_nameimage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:

apiVersion: extensions/v1beta1kind: Deploymentmetadata:  labels:    app.kubernetes.io/name: grafana    app.kubernetes.io/part-of: ingress-nginx  name: grafana  namespace: ingress-nginxspec:  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: v1kind: Servicemetadata:  name: grafana  namespace: ingress-nginx  labels:    app.kubernetes.io/name: grafana    app.kubernetes.io/part-of: ingress-nginxspec:  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:

$ kubectl apply -f grafana.yamldeployment "grafana" createdservice "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

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

访问http://10.90.2.101:7006

image

将我们上面的Prometheus添加到grafana数据源中去。

image

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:

image

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

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image

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