kubernetes监控-prometheus+grafana完美监控

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修改于 2019-06-24 10:01:12

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修改于 2019-06-24 10:01:12

监控方案

cAdvisor+Heapster+InfluxDB+Grafana	Y	简单	容器监控
cAdvisor/exporter+Prometheus+Grafana	Y	扩展性好	容器，应用，主机全方面监控

Prometheus+Grafana是监控告警解决方案里的后起之秀

通过各种exporter采集不同维度的监控指标，并通过Prometheus支持的数据格式暴露出来，Prometheus定期pull数据并用Grafana展示，异常情况使用AlertManager告警。

通过cadvisor采集容器、Pod相关的性能指标数据，并通过暴露的/metrics接口用prometheus抓取

通过prometheus-node-exporter采集主机的性能指标数据，并通过暴露的/metrics接口用prometheus抓取

应用侧自己采集容器中进程主动暴露的指标数据（暴露指标的功能由应用自己实现，并添加平台侧约定的annotation，平台侧负责根据annotation实现通过Prometheus的抓取）

通过kube-state-metrics采集k8s资源对象的状态指标数据，并通过暴露的/metrics接口用prometheus抓取

通过etcd、kubelet、kube-apiserver、kube-controller-manager、kube-scheduler自身暴露的/metrics获取节点上与k8s集群相关的一些特征指标数据。

实现思路

监控指标	具体实现	举例
Pod性能	cAdvisor	容器CPU，内存利用率
Node性能	node-exporter	节点CPU，内存利用率
K8S资源对象	kube-state-metrics	Pod/Deployment/Service

k8s中部署prometheus

官网：https://prometheus.io

下载yaml文件：https://github.com/kubernetes/kubernetes/tree/master/cluster/addons/prometheus

修改yaml文件

#使用nfs存储[root@localhost prometheus]# kubectl get storageclassNAME                  PROVISIONER      AGEmanaged-nfs-storage   fuseim.pri/ifs   9d[root@localhost prometheus]# sed -i s/standard/managed-nfs-storage/ prometheus-statefulset.yaml #修改service使用NOdePort[root@localhost prometheus]# vim prometheus-service.yaml 。。。。spec:  type: NodePort  ports:    - name: http      port: 9090      protocol: TCP      targetPort: 9090  selector:    k8s-app: prometheus

启动prometheus

[root@localhost prometheus]# kubectl apply -f prometheus-rbac.yaml serviceaccount/prometheus createdclusterrole.rbac.authorization.k8s.io/prometheus createdclusterrolebinding.rbac.authorization.k8s.io/prometheus created[root@localhost prometheus]# kubectl apply -f prometheus-configmap.yaml configmap/prometheus-config created[root@localhost prometheus]# kubectl apply -f prometheus-statefulset.yaml statefulset.apps/prometheus created[root@localhost prometheus]# vim prometheus-service.yaml [root@localhost prometheus]# kubectl apply -f prometheus-service.yamlservice/prometheus created

查看

[root@localhost prometheus]# kubectl get pod,svc -n kube-systemNAME                                        READY   STATUS    RESTARTS   AGEpod/coredns-5b8c57999b-z9jh8                1/1     Running   1          16dpod/kubernetes-dashboard-644c96f9c6-bvw8w   1/1     Running   1          16dpod/prometheus-0                            2/2     Running   0          2m40s NAME                           TYPE        CLUSTER-IP   EXTERNAL-IP   PORT(S)          AGEservice/kube-dns               ClusterIP   10.0.0.2     <none>        53/UDP,53/TCP    16dservice/kubernetes-dashboard   NodePort    10.0.0.84    <none>        443:30001/TCP    16dservice/prometheus             NodePort    10.0.0.89    <none>        9090:41782/TCP   39s[root@localhost prometheus]# kubectl get pv,pvc -n kube-systemNAME                                                                                                 CAPACITY   ACCESS MODES   RECLAIM POLICY   STATUS   CLAIM                                      STORAGECLASS          REASON   AGEpersistentvolume/kube-system-prometheus-data-prometheus-0-pvc-0e92f36c-8d9e-11e9-b018-525400828c1f   16Gi       RWO            Delete           Bound    kube-system/prometheus-data-prometheus-0   managed-nfs-storage            25m NAME                                                 STATUS   VOLUME                                                                              CAPACITY   ACCESS MODES   STORAGECLASS          AGEpersistentvolumeclaim/prometheus-data-prometheus-0   Bound    kube-system-prometheus-data-prometheus-0-pvc-0e92f36c-8d9e-11e9-b018-525400828c1f   16Gi       RWO            managed-nfs-storage   25m

访问

部署grafana

[root@localhost prometheus]# cat grafana.yaml apiVersion: apps/v1kind: StatefulSetmetadata:  name: grafana  namespace: kube-systemspec:  serviceName: "grafana"  replicas: 1  selector:    matchLabels:      app: grafana  template:    metadata:      labels:        app: grafana    spec:      containers:        - name: grafana          image: grafana/grafana          resources:            limits:              cpu: 100m              memory: 256Mi            requests:              cpu: 100m              memory: 256Mi          volumeMounts:            - name: grafana-data              mountPath: /var/lib/grafana              subPath: grafana      securityContext:        fsGroup: 472        runAsUser: 472  volumeClaimTemplates:  - metadata:      name: grafana-data    spec:      storageClassName: managed-nfs-storage       accessModes:        - ReadWriteOnce      resources:        requests:          storage: "1Gi" --- apiVersion: v1kind: Servicemetadata:  name: grafana  namespace: kube-systemspec:  type: NodePort  ports:  - port: 80    targetPort: 3000    nodePort: 30007  selector:    app: grafana [root@localhost prometheus]# kubectl apply -f grafana.yaml statefulset.apps/grafana createdservice/grafana created [root@localhost prometheus]# kubectl get pod,svc -n kube-systemNAME                                        READY   STATUS    RESTARTS   AGEpod/coredns-5b8c57999b-z9jh8                1/1     Running   1          17dpod/grafana-0                               1/1     Running   0          45spod/kubernetes-dashboard-644c96f9c6-bvw8w   1/1     Running   1          17dpod/prometheus-0                            2/2     Running   0          25h NAME                           TYPE        CLUSTER-IP   EXTERNAL-IP   PORT(S)          AGEservice/grafana                NodePort    10.0.0.78    <none>        80:30007/TCP     44sservice/kube-dns               ClusterIP   10.0.0.2     <none>        53/UDP,53/TCP    17dservice/kubernetes-dashboard   NodePort    10.0.0.84    <none>        443:30001/TCP    17dservice/prometheus             NodePort    10.0.0.89    <none>        9090:41782/TCP   25h

访问

监控k8s集群中的pod

kubelet的节点使用cAdvisor提供的metrics接口获取该节点所有容器相关的性能指标数据。

暴露接口地址：

https://NodeIP:10255/metrics/cadvisor

https://NodeIP:10250/metrics/cadvisor

导入grafana模板

https://grafana.com/grafana/download

集群资源监控：3119

监控k8s集群中的node

使用文档：https://prometheus.io/docs/guides/node-exporter/

GitHub：https://github.com/prometheus/node_exporter

exporter列表：https://prometheus.io/docs/instrumenting/exporters/

所有node节点部署node_exporter

wget https://github.com/prometheus/node_exporter/releases/download/v0.17.0/node_exporter-0.17.0.linux-amd64.tar.gz tar zxf node_exporter-0.17.0.linux-amd64.tar.gzmv node_exporter-0.17.0.linux-amd64 /usr/local/node_exporter cat <<EOF >/usr/lib/systemd/system/node_exporter.service[Unit]Description=https://prometheus.io [Service]Restart=on-failureExecStart=/usr/local/node_exporter/node_exporter --collector.systemd --collector.systemd.unit-whitelist=(docker|kubelet|kube-proxy|flanneld).service [Install]WantedBy=multi-user.targetEOF systemctl daemon-reloadsystemctl enable node_exportersystemctl restart node_exporter

修改prometheus-configmap.yaml，并重新部署

查看prometheus是否收集到kubernetes-nodes

导入grafana模板

集群资源监控：9276

监控k8s资源对象

https://github.com/kubernetes/kube-state-metrics

kube-state-metrics是一个简单的服务，它监听Kubernetes API服务器并生成有关对象状态的指标。它不关注单个Kubernetes组件的运行状况，而是关注内部各种对象的运行状况，例如部署，节点和容器。

[root@localhost prometheus]# kubectl apply -f kube-state-metrics-rbac.yaml serviceaccount/kube-state-metrics createdclusterrole.rbac.authorization.k8s.io/kube-state-metrics createdrole.rbac.authorization.k8s.io/kube-state-metrics-resizer createdclusterrolebinding.rbac.authorization.k8s.io/kube-state-metrics createdrolebinding.rbac.authorization.k8s.io/kube-state-metrics created[root@localhost prometheus]# vim kube-state-metrics-deployment.yaml [root@localhost prometheus]# kubectl apply -f kube-state-metrics-deployment.yamldeployment.apps/kube-state-metrics createdconfigmap/kube-state-metrics-config created[root@localhost prometheus]# kubectl apply -f kube-state-metrics-service.yaml service/kube-state-metrics created

导入grafana模板

集群资源监控：6417

在K8S中部署Alertmanager

部署Alertmanager

[root@localhost prometheus]# sed -i s/standard/managed-nfs-storage/ alertmanager-pvc.yaml[root@localhost prometheus]# kubectl apply -f  alertmanager-configmap.yaml configmap/alertmanager-config created[root@localhost prometheus]# kubectl apply -f  alertmanager-pvc.yaml persistentvolumeclaim/alertmanager created[root@localhost prometheus]# kubectl apply -f  alertmanager-deployment.yaml deployment.apps/alertmanager created[root@localhost prometheus]# kubectl apply -f  alertmanager-service.yaml service/alertmanager created [root@localhost prometheus]# kubectl get pod -n kube-systemNAME                                    READY   STATUS    RESTARTS   AGEalertmanager-6b5bbd5bd4-lgjn8           2/2     Running   0          95scoredns-5b8c57999b-z9jh8                1/1     Running   1          20dgrafana-0                               1/1     Running   3          2d22hkube-state-metrics-f86fd9f4f-j4rdc      2/2     Running   0          3h2mkubernetes-dashboard-644c96f9c6-bvw8w   1/1     Running   1          20dprometheus-0                            2/2     Running   0          4d

配置Prometheus与Alertmanager通信

[root@localhost prometheus]# vim prometheus-configmap.yaml。。。。    alerting:      alertmanagers:      - static_configs:          - targets: ["alertmanager:80"][root@localhost prometheus]# kubectl apply -f prometheus-configmap.yaml configmap/prometheus-config configured

配置告警

prometheus指定rules目录

configmap存储告警规则

[root@localhost prometheus]# cat prometheus-rules.yaml apiVersion: v1kind: ConfigMapmetadata:  name: prometheus-rules  namespace: kube-systemdata:  general.rules: |    groups:    - name: general.rules      rules:      - alert: InstanceDown        expr: up == 0        for: 1m        labels:          severity: error         annotations:          summary: "Instance {{ $labels.instance }} 停止工作"          description: "{{ $labels.instance }} job {{ $labels.job }} 已经停止5分钟以上."  node.rules: |    groups:    - name: node.rules      rules:      - alert: NodeFilesystemUsage        expr: 100 - (node_filesystem_free_bytes{fstype=~"ext4|xfs"} / node_filesystem_size_bytes{fstype=~"ext4|xfs"} * 100) > 80         for: 1m        labels:          severity: warning         annotations:          summary: "Instance {{ $labels.instance }} : {{ $labels.mountpoint }} 分区使用率过高"          description: "{{ $labels.instance }}: {{ $labels.mountpoint }} 分区使用大于80% (当前值: {{ $value }})"       - alert: NodeMemoryUsage        expr: 100 - (node_memory_MemFree_bytes+node_memory_Cached_bytes+node_memory_Buffers_bytes) / node_memory_MemTotal_bytes * 100 > 80        for: 1m        labels:          severity: warning        annotations:          summary: "Instance {{ $labels.instance }} 内存使用率过高"          description: "{{ $labels.instance }}内存使用大于80% (当前值: {{ $value }})"       - alert: NodeCPUUsage            expr: 100 - (avg(irate(node_cpu_seconds_total{mode="idle"}[5m])) by (instance) * 100) > 60         for: 1m        labels:          severity: warning        annotations:          summary: "Instance {{ $labels.instance }} CPU使用率过高"                 description: "{{ $labels.instance }}CPU使用大于60% (当前值: {{ $value }})" [root@localhost prometheus]# kubectl apply -f prometheus-rules.yamlconfigmap/prometheus-rules created

configmap挂载到容器rules目录

[root@localhost prometheus]# vim prometheus-statefulset.yaml......          volumeMounts:            - name: config-volume              mountPath: /etc/config            - name: prometheus-data              mountPath: /data              subPath: ""            - name: prometheus-rules              mountPath: /etc/config/rules      terminationGracePeriodSeconds: 300      volumes:        - name: config-volume          configMap:            name: prometheus-config        - name: prometheus-rules          configMap:            name: prometheus-rules......

怎加alertmanager的告警配置

[root@localhost prometheus]# cat alertmanager-configmap.yaml apiVersion: v1kind: ConfigMapmetadata:  name: alertmanager-config  namespace: kube-system  labels:    kubernetes.io/cluster-service: "true"    addonmanager.kubernetes.io/mode: EnsureExistsdata:  alertmanager.yml: |    global:       resolve_timeout: 5m      smtp_smarthost: 'smtp.163.com:25'      smtp_from: 'xxxxx@163.com'      smtp_auth_username: 'xxxxx@163.com'      smtp_auth_password: 'xxxxx'    receivers:    - name: default-receiver      email_configs:      - to: "xxxxx@qq.com"    route:      group_interval: 1m      group_wait: 10s      receiver: default-receiver      repeat_interval: 1m [root@localhost prometheus]# kubectl apply -f alertmanager-configmap.yamlconfigmap/alertmanager-config configured

邮件告警