Prometheus+Grafana+Alertmanager构建企业级监控系统
1. 安装node-exporter
node-exporter 可以采集机器（物理机、虚拟机、云主机等）的监控指标数据，能够采集到的指标包
括 CPU, 内存，磁盘，网络，文件数等信息。
[root@master1 .kube] NAME STATUS ROLES AGE VERSION master1 Ready control-plane,master 12d v1.20.6 node1 Ready worker 12d v1.20.6 [root@master1 .kube] namespace/monitor-sa created [root@master1 ~] ad68498f8d86: Loading layer [==================================================>] 4.628MB/4.628MB ad8512dce2a7: Loading layer [==================================================>] 2.781MB/2.781MB cc1adb06ef21: Loading layer [==================================================>] 16.9MB/16.9MB Loaded image: prom/node-exporter:v0.16.0 [root@master1 ~] [root@node1 ~] ad68498f8d86: Loading layer [==================================================>] 4.628MB/4.628MB ad8512dce2a7: Loading layer [==================================================>] 2.781MB/2.781MB cc1adb06ef21: Loading layer [==================================================>] 16.9MB/16.9MB Loaded image: prom/node-exporter:v0.16.0 [root@node1 ~] 在dockerhub的官网搜索 https://hub.docker.com/ [外链图片转存失败,源站可能有防盗链机制,建议将图片保存下来直接上传(img-nlOYwB94-1655106671762)(C:\Users\mack\AppData\Roaming\Typora\typora-user-images\1654670966393.png)]
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[root@master1 prometheus] apiVersion: apps/v1 kind: DaemonSet metadata: name: node-exporter namespace: monitor-sa labels: name: node-exporter spec: selector: matchLabels: name: node-exporter template: metadata: labels: name: node-exporter spec: hostPID: true hostIPC: true hostNetwork: true containers: - name: node-exporter image: prom/node-exporter:v0.16.0 ports: - containerPort: 9100 resources: requests: cpu: 0.15 securityContext: privileged: true args: - --path.procfs - /host/proc - --path.sysfs - /host/sys - --collector.filesystem.ignored-mount-points - '"^/(sys|proc|dev|host|etc)($|/)"' volumeMounts: - name: dev mountPath: /host/dev - name: proc mountPath: /host/proc - name: sys mountPath: /host/sys - name: rootfs mountPath: /rootfs tolerations: - key: "node-role.kubernetes.io/master" operator: "Exists" effect: "NoSchedule" volumes: - name: proc hostPath: path: /proc - name: dev hostPath: path: /dev - name: sys hostPath: path: /sys - name: rootfs hostPath: path: / END [root@master1 prometheus] daemonset.apps/node-exporter created [root@master1 prometheus] NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES node-exporter-92k4d 1/1 Running 0 58s 192.168.1.181 node1 <none> <none> node-exporter-d44k4 1/1 Running 0 58s 192.168.1.180 master1 <none> <none> curl http://主机 ip:9100/metrics curl http://192.168.1.180:9100/metrics | grep node_cpu_seconds 显示 192.168.1.180 主机 cpu 的使用情况 ** ** node_cpu_seconds_total{cpu="0",mode="idle"} 72963.37 node_cpu_seconds_total{cpu="0",mode="iowait"} 9.35 node_cpu_seconds_total{cpu="0",mode="irq"} 0 node_cpu_seconds_total{cpu="0",mode="nice"} 0 node_cpu_seconds_total{cpu="0",mode="softirq"} 151.4 node_cpu_seconds_total{cpu="0",mode="steal"} 0 node_cpu_seconds_total{cpu="0",mode="system"} 656.12 node_cpu_seconds_total{cpu="0",mode="user"} 267.1 node_cpu_seconds_total{cpu="0",mode="idle"} ： cpu0 上 idle 进程占用 CPU 的总时间，CPU 占用时间是一个只增不减的度量指标，从类型中也可以看 出 node_cpu 的数据类型是 counter（计数器） **counter 计数器：只是采集递增的指标 curl http://192.168.40.180:9100/metrics | grep node_load ** ** node_load1 0.1 node_load1 该指标反映了当前主机在最近一分钟以内的负载情况，系统的负载情况会随系统资源的 使用而变化，因此 node_load1 反映的是当前状态，数据可能增加也可能减少，从注释中可以看出当前指 标类型为 gauge（标准尺寸） gauge 标准尺寸：统计的指标可增加可减少 2. Prometheus server 安装和配置
[root@master1 prometheus] serviceaccount/monitor created [root@master1 prometheus] NAME SECRETS AGE default 1 79m monitor 1 30s [root@master1 prometheus] clusterrolebinding.rbac.authorization.k8s.io/monitor-clusterrolebinding created [root@node1 ~] [root@node1 ~] [root@node1 ~] drwxrwxrwx. 2 root root 6 Jun 8 16:00 /data [root@master1 prometheus] --- kind: ConfigMap apiVersion: v1 metadata: labels: app: prometheus name: prometheus-config namespace: monitor-sa data: prometheus.yml: | global: scrape_interval: 15s scrape_timeout: 10s evaluation_interval: 1m scrape_configs: - job_name: 'kubernetes-node' kubernetes_sd_configs: - role: node relabel_configs: - source_labels: [__address__] regex: '(.*):10250' replacement: '${1}:9100' target_label: __address__ action: replace - action: labelmap regex: __meta_kubernetes_node_label_(.+) - job_name: 'kubernetes-node-cadvisor' kubernetes_sd_configs: - role: node scheme: https tls_config: ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crt bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token 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 - job_name: 'kubernetes-apiserver' kubernetes_sd_configs: - role: endpoints scheme: https tls_config: ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crt bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token relabel_configs: - source_labels: [__meta_kubernetes_namespace, __meta_kubernetes_service_name, __meta_kubernetes_endpoint_port_name] action: keep regex: default;kubernetes;https - 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:$2 - action: labelmap regex: __meta_kubernetes_service_label_(.+) - source_labels: [__meta_kubernetes_namespace] action: replace target_label: kubernetes_namespace - source_labels: [__meta_kubernetes_service_name] action: replace target_label: kubernetes_name END [root@master1 prometheus] configmap/prometheus-config created [root@master1 prometheus] NAME DATA AGE kube-root-ca.crt 1 3h57m prometheus-config 1 18s [root@master1 prometheus] Name: prometheus-config Namespace: monitor-sa Labels: app=prometheus Annotations: <none> Data ==== prometheus.yml: ---- global: scrape_interval: 15s scrape_timeout: 10s evaluation_interval: 1m scrape_configs: - job_name: 'kubernetes-node' kubernetes_sd_configs: - role: node relabel_configs: - source_labels: [__address__] regex: '(.*):10250' replacement: '${1}:9100' target_label: __address__ action: replace - action: labelmap regex: __meta_kubernetes_node_label_(.+) - job_name: 'kubernetes-node-cadvisor' kubernetes_sd_configs: - role: node scheme: https tls_config: ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crt bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token 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 - job_name: 'kubernetes-apiserver' kubernetes_sd_configs: - role: endpoints scheme: https tls_config: ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crt bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token relabel_configs: - source_labels: [__meta_kubernetes_namespace, __meta_kubernetes_service_name, __meta_kubernetes_endpoint_port_name] action: keep regex: default;kubernetes;https - 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 Events: <none> 安装 prometheus 需要的镜像 prometheus-2-2-1.tar.gz ，上传到 k8s 的工作节点 node1 上，手动解压
这个镜像可以从hub.docker.com dockerhub上下载，也可以通过如下指令pull
docker pull prom/prometheus:v2.2.1 [root@node1 ~] prometheus-2-2-1.tar.gz [root@node1 ~] 110M prometheus-2-2-1.tar.gz [root@node1 ~] 6a749002dd6a: Loading layer [==================================================>] 1.338MB/1.338MB 5f70bf18a086: Loading layer [==================================================>] 1.024kB/1.024kB 1692ded805c8: Loading layer [==================================================>] 2.629MB/2.629MB 035489d93827: Loading layer [==================================================>] 66.18MB/66.18MB 8b6ef3a2ab2c: Loading layer [==================================================>] 44.5MB/44.5MB ff98586f6325: Loading layer [==================================================>] 3.584kB/3.584kB 017a13aba9f4: Loading layer [==================================================>] 12.8kB/12.8kB 4d04d79bb1a5: Loading layer [==================================================>] 27.65kB/27.65kB 75f6c078fa6b: Loading layer [==================================================>] 10.75kB/10.75kB 5e8313e8e2ba: Loading layer [==================================================>] 6.144kB/6.144kB Loaded image: prom/prometheus:v2.2.1 [root@node1 ~] [root@master1 prometheus] --- apiVersion: apps/v1 kind: Deployment metadata: name: prometheus-server namespace: monitor-sa labels: app: prometheus spec: replicas: 1 selector: matchLabels: app: prometheus component: server template: metadata: labels: app: prometheus component: server annotations: prometheus.io/scrape: 'false' spec: nodeName: node1 serviceAccountName: monitor containers: - name: prometheus image: prom/prometheus:v2.2.1 imagePullPolicy: IfNotPresent command: - prometheus - --config.file=/etc/prometheus/prometheus.yml - --storage.tsdb.path=/prometheus - --storage.tsdb.retention=720h - --web.enable-lifecycle ports: - containerPort: 9090 protocol: TCP volumeMounts: - mountPath: /etc/prometheus/prometheus.yml name: prometheus-config subPath: prometheus.yml - mountPath: /prometheus/ name: prometheus-storage-volume volumes: - name: prometheus-config configMap: name: prometheus-config items: - key: prometheus.yml path: prometheus.yml mode: 0644 - name: prometheus-storage-volume hostPath: path: /data type: Directory END [root@master1 prometheus] deployment.apps/prometheus-server created [root@master1 prometheus] NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES node-exporter-92k4d 1/1 Running 0 4h24m 192.168.1.181 node1 <none> <none> node-exporter-d44k4 1/1 Running 0 4h24m 192.168.1.180 master1 <none> <none> prometheus-server-657bd8cb4d-zrmk4 1/1 Running 0 42s 10.244.166.185 node1 <none> <none> [root@master1 prometheus] [root@master1 prometheus] apiVersion: v1 kind: Service metadata: name: prometheus namespace: monitor-sa labels: app: prometheus spec: type: NodePort ports: - port: 9090 targetPort: 9090 protocol: TCP selector: app: prometheus component: server END [root@master1 prometheus] service/prometheus created [root@master1 prometheus] NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE prometheus NodePort 10.103.238.66 <none> 9090:31935/TCP 37s [root@master1 prometheus] NAME ENDPOINTS AGE prometheus 10.244.166.185:9090 3m50s [外链图片转存失败,源站可能有防盗链机制,建议将图片保存下来直接上传(img-TEexacDR-1655106671763)(C:\Users\mack\AppData\Roaming\Typora\typora-user-images\1654689013529.png)]
[root@master1 prometheus] NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES prometheus-server-657bd8cb4d-zrmk4 1/1 Running 0 64m 10.244.166.185 node1 <none> <none> [root@master1 prometheus] 想要使配置生效可用如下命令热加载： [root@master1 prometheus] 执行如下强制删除： kubectl delete -f prometheus-cfg.yaml kubectl delete -f prometheus-deploy.yaml 然后再通过 apply 更新： kubectl apply -f prometheus-cfg.yaml kubectl apply -f prometheus-deploy.yaml 注意： 线上最好热加载，暴力删除可能造成监控数据的丢失 3. 可视化 UI 界面 Grafana 的安装和配置
**Grafana 是一个跨平台的开源的度量分析和可视化工具，可以将采集的数据可视化的展示，并及时通
知给告警接收方。它主要有以下六大特点：
1、展示方式：快速灵活的客户端图表，面板插件有许多不同方式的可视化指标和日志，官方库中具
有丰富的仪表盘插件，比如热图、折线图、图表等多种展示方式；
2、数据源：Graphite，InfluxDB，OpenTSDB，Prometheus，Elasticsearch，CloudWatch 和
KairosDB 等；
3、通知提醒：以可视方式定义最重要指标的警报规则，Grafana 将不断计算并发送通知，在数据达
到阈值时通过 Slack、PagerDuty 等获得通知；
4、混合展示：在同一图表中混合使用不同的数据源，可以基于每个查询指定数据源，甚至自定义数
据源；
5、注释：使用来自不同数据源的丰富事件注释图表，将鼠标悬停在事件上会显示完整的事件元数据
和标记。
**安装 Grafana 需要的镜像 heapster-grafana-amd64_v5_0_4.tar.gz,把镜像上传到 k8s 的工作节点
node1 上，手动解压：
[root@node1 prometheus] heapster-grafana-amd64_v5_0_4.tar.gz [root@node1 prometheus] 165M heapster-grafana-amd64_v5_0_4.tar.gz [root@node1 prometheus] 6816d98be637: Loading layer [==================================================>] 4.642MB/4.642MB 523feee8e0d3: Loading layer [==================================================>] 161.5MB/161.5MB 43d2638621da: Loading layer [==================================================>] 230.4kB/230.4kB f24c0fa82e54: Loading layer [==================================================>] 2.56kB/2.56kB 334547094992: Loading layer [==================================================>] 5.826MB/5.826MB Loaded image: k8s.gcr.io/heapster-grafana-amd64:v5.0.4 这个镜像可以在hub.docker.com上搜索下载
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[root@master1 prometheus] apiVersion: apps/v1 kind: Deployment metadata: name: monitoring-grafana namespace: kube-system spec: replicas: 1 selector: matchLabels: task: monitoring k8s-app: grafana 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: INFLUXDB_HOST value: monitoring-influxdb - name: GF_SERVER_HTTP_PORT value: "3000" - 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 value: / volumes: - name: ca-certificates hostPath: path: /etc/ssl/certs - name: grafana-storage emptyDir: {} --- apiVersion: v1 kind: Service metadata: labels: kubernetes.io/cluster-service: 'true' kubernetes.io/name: monitoring-grafana name: monitoring-grafana namespace: kube-system spec: ports: - port: 80 targetPort: 3000 selector: k8s-app: grafana type: NodePort END [root@master1 prometheus] deployment.apps/monitoring-grafana created service/monitoring-grafana created [root@master1 prometheus] NAME READY UP-TO-DATE AVAILABLE AGE calico-kube-controllers 1/1 1 1 13d coredns 2/2 2 2 13d monitoring-grafana 1/1 1 1 27s [root@master1 prometheus] NAME DESIRED CURRENT READY AGE calico-kube-controllers-6949477b58 1 1 1 13d coredns-7f89b7bc75 2 2 2 13d monitoring-grafana-675798bf47 1 1 1 37s [root@master1 prometheus] NAME READY STATUS RESTARTS AGE calico-kube-controllers-6949477b58-phvxx 1/1 Running 0 20h calico-node-n5j7r 1/1 Running 0 13d calico-node-r26rb 1/1 Running 0 13d coredns-7f89b7bc75-8h7vd 1/1 Running 0 11d coredns-7f89b7bc75-txs9t 1/1 Running 0 20h etcd-master1 1/1 Running 0 13d fluentd-elasticsearch-6qzdk 1/1 Running 0 3d23h fluentd-elasticsearch-rxsgw 1/1 Running 0 3d23h kube-apiserver-master1 1/1 Running 0 13d kube-controller-manager-master1 1/1 Running 0 13d kube-proxy-6jdfc 1/1 Running 0 13d kube-proxy-n4gx7 1/1 Running 0 13d kube-scheduler-master1 1/1 Running 0 13d monitoring-grafana-675798bf47-x8sm8 1/1 Running 0 45s [root@master1 prometheus] NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE kube-dns ClusterIP 10.96.0.10 <none> 53/UDP,53/TCP,9153/TCP 13d monitoring-grafana NodePort 10.102.90.185 <none> 80:32738/TCP 55s 使用k8s节点IP加32738可以在浏览器访问了
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查看 grafana 前端的 service
[root@master1 prometheus] monitoring-grafana NodePort 10.102.90.185 <none> 80:32738/TCP 15m 1）登陆grafana,在浏览器访问
192.168.1.180:32738
看到如下 内容
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2）配置 grafana 界面：
开始配置 grafana 的 web 界面：
选择 Create your first data source
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导入的监控模板，可在如下链接搜索
https://grafana.com/dashboards?dataSource=prometheus&search=kubernetes
可直接导入 node_exporter.json 监控模板，这个可以把 node 节点指标显示出来
怎么导入监控模板，按如下步骤：
上面 Save & Test 测试没问题之后，就可以返回 Grafana 主页面,点击左侧的+号下面的Import
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出现如下界面
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可直接导入 docker_rev1.json，显示容器资源指标的，
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4. 安装kube-state-metrics 组件
**kube-state-metrics 是什么？
kube-state-metrics 通过监听 API Server 生成有关资源对象的状态指标，比如 Deployment、
Node、Pod，需要注意的是 kube-state-metrics 只是简单的提供一个 metrics 数据，并不会存储这
些指标数据，所以我们可以使用 Prometheus 来抓取这些数据然后存储，主要关注的是业务相关的一
些元数据，比如 Deployment、Pod、副本状态等；调度了多少个 replicas？现在可用的有几个？多
少个 Pod 是 running/stopped/terminated 状态？Pod 重启了多少次？我有多少 job 在运行中。
安装 kube-state-metrics 组件
1）创建 sa，并对 sa 授权
[root@master1 prometheus] --- apiVersion: v1 kind: ServiceAccount metadata: name: kube-state-metrics namespace: kube-system --- apiVersion: rbac.authorization.k8s.io/v1 kind: ClusterRole metadata: name: kube-state-metrics rules: - apiGroups: [""] resources: ["nodes", "pods", "services", "resourcequotas", "replicationcontrollers", "limitranges", "persistentvolumeclaims", "persistentvolumes", "namespaces", "endpoints"] verbs: ["list", "watch"] - apiGroups: ["extensions"] resources: ["daemonsets", "deployments", "replicasets"] verbs: ["list", "watch"] - apiGroups: ["apps"] resources: ["statefulsets"] verbs: ["list", "watch"] - apiGroups: ["batch"] resources: ["cronjobs", "jobs"] verbs: ["list", "watch"] - apiGroups: ["autoscaling"] resources: ["horizontalpodautoscalers"] verbs: ["list", "watch"] --- apiVersion: rbac.authorization.k8s.io/v1 kind: ClusterRoleBinding metadata: name: kube-state-metrics roleRef: apiGroup: rbac.authorization.k8s.io kind: ClusterRole name: kube-state-metrics subjects: - kind: ServiceAccount name: kube-state-metrics namespace: kube-system END [root@master1 prometheus] serviceaccount/kube-state-metrics created clusterrole.rbac.authorization.k8s.io/kube-state-metrics created clusterrolebinding.rbac.authorization.k8s.io/kube-state-metrics created [root@master1 prometheus] kube-state-metrics 1 78s [root@master1 prometheus] kube-state-metrics 2022-06-10T07:03:54Z [root@master1 prometheus] kube-state-metrics ClusterRole/kube-state-metrics 安装 kube-state-metrics 组件需要的镜像上传到 k8s 工作节点node1上，手动解压：
这个镜像也可在hub.docker.com上找到
[root@node1 prometheus] kube-state-metrics_1_9_0.tar.gz [root@node1 prometheus] 33M kube-state-metrics_1_9_0.tar.gz [root@node1 prometheus] [root@node1 prometheus] 932da5156413: Loading layer [==================================================>] 3.062MB/3.062MB bd8df7c22fdb: Loading layer [==================================================>] 31MB/31MB Loaded image: quay.io/coreos/kube-state-metrics:v1.9.0 在控制节点上生成yaml文件
[root@master1 prometheus] apiVersion: apps/v1 kind: Deployment metadata: name: kube-state-metrics namespace: kube-system spec: replicas: 1 selector: matchLabels: app: kube-state-metrics template: metadata: labels: app: kube-state-metrics spec: serviceAccountName: kube-state-metrics containers: - name: kube-state-metrics image: quay.io/coreos/kube-state-metrics:v1.9.0 ports: - containerPort: 8080 END [root@master1 prometheus] deployment.apps/kube-state-metrics created [root@master1 prometheus] NAME READY STATUS RESTARTS AGE calico-kube-controllers-6949477b58-phvxx 1/1 Running 0 2d1h calico-node-n5j7r 1/1 Running 0 14d calico-node-r26rb 1/1 Running 0 14d coredns-7f89b7bc75-8h7vd 1/1 Running 0 13d coredns-7f89b7bc75-txs9t 1/1 Running 0 2d1h etcd-master1 1/1 Running 0 14d fluentd-elasticsearch-6qzdk 1/1 Running 0 5d4h fluentd-elasticsearch-rxsgw 1/1 Running 0 5d4h kube-apiserver-master1 1/1 Running 0 14d kube-controller-manager-master1 1/1 Running 0 14d kube-proxy-6jdfc 1/1 Running 0 14d kube-proxy-n4gx7 1/1 Running 0 14d kube-scheduler-master1 1/1 Running 0 14d kube-state-metrics-58d4957bc5-v6tn2 1/1 Running 0 7m38s monitoring-grafana-675798bf47-x8sm8 1/1 Running 0 29h [root@master1 prometheus] apiVersion: v1 kind: Service metadata: annotations: prometheus.io/scrape: 'true' name: kube-state-metrics namespace: kube-system labels: app: kube-state-metrics spec: ports: - name: kube-state-metrics port: 8080 protocol: TCP selector: app: kube-state-metrics END [root@master1 prometheus] service/kube-state-metrics created [root@master1 prometheus] NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE kube-dns ClusterIP 10.96.0.10 <none> 53/UDP,53/TCP,9153/TCP 15d kube-state-metrics ClusterIP 10.102.207.144 <none> 8080/TCP 46s monitoring-grafana NodePort 10.102.90.185 <none> 80:32738/TCP 29h [root@master1 prometheus] NAME ENDPOINTS AGE kube-dns 10.244.137.66:53,10.244.137.69:53,10.244.137.66:53 + 3 more... 15d kube-state-metrics 10.244.166.187:8080 71s monitoring-grafana 10.244.166.186:3000 29h 在 grafana web 界面导入 Kubernetes Cluster (Prometheus)-1577674936972.json 和 Kubernetes
cluster monitoring (via Prometheus) (k8s 1.16)-1577691996738.json
文件在grafana.com上找到
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导入json
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5. 配置 alertmanager-发送报警到 qq 邮箱
报警：指 prometheus 将监测到的异常事件发送给 alertmanager
通知：alertmanager 将报警信息发送到邮件、微信、钉钉等
创建 alertmanager 配置文件
在 k8s 的控制节点master1创建 alertmanager-cm.yaml 文件
[root@master1 prometheus] alertmanager-cm.yaml [root@master1 prometheus] 4.0K alertmanager-cm.yaml [root@master1 prometheus] kind: ConfigMap apiVersion: v1 metadata: name: alertmanager namespace: monitor-sa data: alertmanager.yml: |- global: resolve_timeout: 1m smtp_smarthost: 'smtp.163.com:25' smtp_from: 'xxxxxxxx@163.com' smtp_auth_username: 'xxxxxxxx' smtp_auth_password: 'xxxxxxxxxx' smtp_require_tls: false route: group_by: [alertname] group_wait: 10s group_interval: 10s repeat_interval: 10m receiver: default-receiver receivers: - name: 'default-receiver' email_configs: - to: 'xxxxxxxx@qq.com' send_resolved: true [root@master1 prometheus] [root@master1 prometheus] configmap/alertmanager created [root@master1 prometheus] NAME DATA AGE alertmanager 1 23s alertmanager 配置文件解释说明： smtp_smarthost: 'smtp.163.com:25' smtp_from: 'xxxxxxxx@163.com' smtp_auth_username: 'xxxxxxxx' smtp_auth_password: 'xxxxxxxxxx' email_configs: - to: 'xxxxxxxxx@qq.com' smtp_from 的邮箱名字重复 route: group_by: [alertname] group_wait: 10s group_interval: 10s repeat_interval: 10m receiver: default-receiver Prometheus 一条告警的触发流程、等待时间
报警处理流程如下：
'scrape_interval’定义的时间间隔，定期采集目标主机上监控数据。
停止尝试。这时候把接口的状态变为“DOWN”。
\3. Prometheus 同时根据配置的"evaluation_interval"的时间间隔，定期（默认 1min）的对 Alert
Rule 进行评估；当到达评估周期的时候，发现接口 A 为 DOWN，即 UP=0 为真，激活 Alert，进入
“PENDING”状态，并记录当前 active 的时间；
是否已经超出 rule 里的‘for’ 持续时间，如果未超出，则进入下一个评估周期；如果时间超出，
则 alert 的状态变为“FIRING”；同时调用 Alertmanager 接口，发送相关报警数据。
“group_wait”时间先进行等待。等 wait 时间过后再发送报警信息。
功发出，那么间隔“group_interval”的时间间隔后再重新发送报警信息。比如配置的是邮件报警，
那么同属一个 group 的报警信息会汇总在一个邮件里进行发送。
隔之后再重复发送相同的报警邮件；如果之前的警报没有成功发送，则相当于触发第 6 条条件，则需
要等待 group_interval 时间间隔后重复发送。
同时最后至于警报信息具体发给谁，满足什么样的条件下指定警报接收人，设置不同报警发送频率，
这里有 alertmanager 的 route 路由规则进行配置。
#创建 prometheus 和告警规则配置文件
在 k8s 的控制节点生成一个 prometheus-alertmanager-cfg.yaml 文件并上传到 k8s 的 master1 节点
[root@master1 prometheus] kind: ConfigMap apiVersion: v1 metadata: labels: app: prometheus name: prometheus-config namespace: monitor-sa data: prometheus.yml: | rule_files: - /etc/prometheus/rules.yml alerting: alertmanagers: - static_configs: - targets: ["localhost:9093"] global: scrape_interval: 15s scrape_timeout: 10s evaluation_interval: 1m scrape_configs: - job_name: 'kubernetes-node' kubernetes_sd_configs: - role: node relabel_configs: - source_labels: [__address__] regex: '(.*):10250' replacement: '${1}:9100' target_label: __address__ action: replace - action: labelmap regex: __meta_kubernetes_node_label_(.+) - job_name: 'kubernetes-node-cadvisor' kubernetes_sd_configs: - role: node scheme: https tls_config: ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crt bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token 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 - job_name: 'kubernetes-apiserver' kubernetes_sd_configs: - role: endpoints scheme: https tls_config: ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crt bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token relabel_configs: - source_labels: [__meta_kubernetes_namespace, __meta_kubernetes_service_name, __meta_kubernetes_endpoint_port_name] action: keep regex: default;kubernetes;https - 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 - job_name: 'kubernetes-pods' kubernetes_sd_configs: - role: pod relabel_configs: - action: keep regex: true source_labels: - __meta_kubernetes_pod_annotation_prometheus_io_scrape - action: replace regex: (.+) source_labels: - __meta_kubernetes_pod_annotation_prometheus_io_path target_label: __metrics_path__ - action: replace regex: ([^:]+)(?::\d+)?;(\d+) replacement: $1:$2 source_labels: - __address__ - __meta_kubernetes_pod_annotation_prometheus_io_port target_label: __address__ - action: labelmap regex: __meta_kubernetes_pod_label_(.+) - action: replace source_labels: - __meta_kubernetes_namespace target_label: kubernetes_namespace - action: replace source_labels: - __meta_kubernetes_pod_name target_label: kubernetes_pod_name - job_name: 'kubernetes-schedule' scrape_interval: 5s static_configs: - targets: ['192.168.1.180:10251'] - job_name: 'kubernetes-controller-manager' scrape_interval: 5s static_configs: - targets: ['192.168.1.180:10252'] - job_name: 'kubernetes-kube-proxy' scrape_interval: 5s static_configs: - targets: ['192.168.1.180:10249','192.168.1.181:10249'] - job_name: 'kubernetes-etcd' scheme: https tls_config: ca_file: /var/run/secrets/kubernetes.io/k8s-certs/etcd/ca.crt cert_file: /var/run/secrets/kubernetes.io/k8s-certs/etcd/server.crt key_file: /var/run/secrets/kubernetes.io/k8s-certs/etcd/server.key scrape_interval: 5s static_configs: - targets: ['192.168.1.180:2379'] rules.yml: | groups: - name: example rules: - alert: kube-proxy的cpu使用率大于80% expr: rate(process_cpu_seconds_total{job=~"kubernetes-kube-proxy"}[1m]) * 100 > 80 for: 2s labels: severity: warnning annotations: description: "{{$labels.instance}}的{{$labels.job}}组件的cpu使用率超过80%" - alert: kube-proxy的cpu使用率大于90% expr: rate(process_cpu_seconds_total{job=~"kubernetes-kube-proxy"}[1m]) * 100 > 90 for: 2s labels: severity: critical annotations: description: "{{$labels.instance}}的{{$labels.job}}组件的cpu使用率超过90%" - alert: scheduler的cpu使用率大于80% expr: rate(process_cpu_seconds_total{job=~"kubernetes-schedule"}[1m]) * 100 > 80 for: 2s labels: severity: warnning annotations: description: "{{$labels.instance}}的{{$labels.job}}组件的cpu使用率超过80%" - alert: scheduler的cpu使用率大于90% expr: rate(process_cpu_seconds_total{job=~"kubernetes-schedule"}[1m]) * 100 > 90 for: 2s labels: severity: critical annotations: description: "{{$labels.instance}}的{{$labels.job}}组件的cpu使用率超过90%" - alert: controller-manager的cpu使用率大于80% expr: rate(process_cpu_seconds_total{job=~"kubernetes-controller-manager"}[1m]) * 100 > 80 for: 2s labels: severity: warnning annotations: description: "{{$labels.instance}}的{{$labels.job}}组件的cpu使用率超过80%" - alert: controller-manager的cpu使用率大于90% expr: rate(process_cpu_seconds_total{job=~"kubernetes-controller-manager"}[1m]) * 100 > 0 for: 2s labels: severity: critical annotations: description: "{{$labels.instance}}的{{$labels.job}}组件的cpu使用率超过90%" - alert: apiserver的cpu使用率大于80% expr: rate(process_cpu_seconds_total{job=~"kubernetes-apiserver"}[1m]) * 100 > 80 for: 2s labels: severity: warnning annotations: description: "{{$labels.instance}}的{{$labels.job}}组件的cpu使用率超过80%" - alert: apiserver的cpu使用率大于90% expr: rate(process_cpu_seconds_total{job=~"kubernetes-apiserver"}[1m]) * 100 > 90 for: 2s labels: severity: critical annotations: description: "{{$labels.instance}}的{{$labels.job}}组件的cpu使用率超过90%" - alert: etcd的cpu使用率大于80% expr: rate(process_cpu_seconds_total{job=~"kubernetes-etcd"}[1m]) * 100 > 80 for: 2s labels: severity: warnning annotations: description: "{{$labels.instance}}的{{$labels.job}}组件的cpu使用率超过80%" - alert: etcd的cpu使用率大于90% expr: rate(process_cpu_seconds_total{job=~"kubernetes-etcd"}[1m]) * 100 > 90 for: 2s labels: severity: critical annotations: description: "{{$labels.instance}}的{{$labels.job}}组件的cpu使用率超过90%" - alert: kube-state-metrics的cpu使用率大于80% expr: rate(process_cpu_seconds_total{k8s_app=~"kube-state-metrics"}[1m]) * 100 > 80 for: 2s labels: severity: warnning annotations: description: "{{$labels.instance}}的{{$labels.k8s_app}}组件的cpu使用率超过80%" value: "{{ $value }}%" threshold: "80%" - alert: kube-state-metrics的cpu使用率大于90% expr: rate(process_cpu_seconds_total{k8s_app=~"kube-state-metrics"}[1m]) * 100 > 0 for: 2s labels: severity: critical annotations: description: "{{$labels.instance}}的{{$labels.k8s_app}}组件的cpu使用率超过90%" value: "{{ $value }}%" threshold: "90%" - alert: coredns的cpu使用率大于80% expr: rate(process_cpu_seconds_total{k8s_app=~"kube-dns"}[1m]) * 100 > 80 for: 2s labels: severity: warnning annotations: description: "{{$labels.instance}}的{{$labels.k8s_app}}组件的cpu使用率超过80%" value: "{{ $value }}%" threshold: "80%" - alert: coredns的cpu使用率大于90% expr: rate(process_cpu_seconds_total{k8s_app=~"kube-dns"}[1m]) * 100 > 90 for: 2s labels: severity: critical annotations: description: "{{$labels.instance}}的{{$labels.k8s_app}}组件的cpu使用率超过90%" value: "{{ $value }}%" threshold: "90%" - alert: kube-proxy打开句柄数>600 expr: process_open_fds{job=~"kubernetes-kube-proxy"} > 600 for: 2s labels: severity: warnning annotations: description: "{{$labels.instance}}的{{$labels.job}}打开句柄数>600" value: "{{ $value }}" - alert: kube-proxy打开句柄数>1000 expr: process_open_fds{job=~"kubernetes-kube-proxy"} > 1000 for: 2s labels: severity: critical annotations: description: "{{$labels.instance}}的{{$labels.job}}打开句柄数>1000" value: "{{ $value }}" - alert: kubernetes-schedule打开句柄数>600 expr: process_open_fds{job=~"kubernetes-schedule"} > 600 for: 2s labels: severity: warnning annotations: description: "{{$labels.instance}}的{{$labels.job}}打开句柄数>600" value: "{{ $value }}" - alert: kubernetes-schedule打开句柄数>1000 expr: process_open_fds{job=~"kubernetes-schedule"} > 1000 for: 2s labels: severity: critical annotations: description: "{{$labels.instance}}的{{$labels.job}}打开句柄数>1000" value: "{{ $value }}" - alert: kubernetes-controller-manager打开句柄数>600 expr: process_open_fds{job=~"kubernetes-controller-manager"} > 600 for: 2s labels: severity: warnning annotations: description: "{{$labels.instance}}的{{$labels.job}}打开句柄数>600" value: "{{ $value }}" - alert: kubernetes-controller-manager打开句柄数>1000 expr: process_open_fds{job=~"kubernetes-controller-manager"} > 1000 for: 2s labels: severity: critical annotations: description: "{{$labels.instance}}的{{$labels.job}}打开句柄数>1000" value: "{{ $value }}" - alert: kubernetes-apiserver打开句柄数>600 expr: process_open_fds{job=~"kubernetes-apiserver"} > 600 for: 2s labels: severity: warnning annotations: description: "{{$labels.instance}}的{{$labels.job}}打开句柄数>600" value: "{{ $value }}" - alert: kubernetes-apiserver打开句柄数>1000 expr: process_open_fds{job=~"kubernetes-apiserver"} > 1000 for: 2s labels: severity: critical annotations: description: "{{$labels.instance}}的{{$labels.job}}打开句柄数>1000" value: "{{ $value }}" - alert: kubernetes-etcd打开句柄数>600 expr: process_open_fds{job=~"kubernetes-etcd"} > 600 for: 2s labels: severity: warnning annotations: description: "{{$labels.instance}}的{{$labels.job}}打开句柄数>600" value: "{{ $value }}" - alert: kubernetes-etcd打开句柄数>1000 expr: process_open_fds{job=~"kubernetes-etcd"} > 1000 for: 2s labels: severity: critical annotations: description: "{{$labels.instance}}的{{$labels.job}}打开句柄数>1000" value: "{{ $value }}" - alert: coredns expr: process_open_fds{k8s_app=~"kube-dns"} > 600 for: 2s labels: severity: warnning annotations: description: "插件{{$labels.k8s_app}}({{$labels.instance}}): 打开句柄数超过600" value: "{{ $value }}" - alert: coredns expr: process_open_fds{k8s_app=~"kube-dns"} > 1000 for: 2s labels: severity: critical annotations: description: "插件{{$labels.k8s_app}}({{$labels.instance}}): 打开句柄数超过1000" value: "{{ $value }}" - alert: kube-proxy expr: process_virtual_memory_bytes{job=~"kubernetes-kube-proxy"} > 2000000000 for: 2s labels: severity: warnning annotations: description: "组件{{$labels.job}}({{$labels.instance}}): 使用虚拟内存超过2G" value: "{{ $value }}" - alert: scheduler expr: process_virtual_memory_bytes{job=~"kubernetes-schedule"} > 2000000000 for: 2s labels: severity: warnning annotations: description: "组件{{$labels.job}}({{$labels.instance}}): 使用虚拟内存超过2G" value: "{{ $value }}" - alert: kubernetes-controller-manager expr: process_virtual_memory_bytes{job=~"kubernetes-controller-manager"} > 2000000000 for: 2s labels: severity: warnning annotations: description: "组件{{$labels.job}}({{$labels.instance}}): 使用虚拟内存超过2G" value: "{{ $value }}" - alert: kubernetes-apiserver expr: process_virtual_memory_bytes{job=~"kubernetes-apiserver"} > 2000000000 for: 2s labels: severity: warnning annotations: description: "组件{{$labels.job}}({{$labels.instance}}): 使用虚拟内存超过2G" value: "{{ $value }}" - alert: kubernetes-etcd expr: process_virtual_memory_bytes{job=~"kubernetes-etcd"} > 2000000000 for: 2s labels: severity: warnning annotations: description: "组件{{$labels.job}}({{$labels.instance}}): 使用虚拟内存超过2G" value: "{{ $value }}" - alert: kube-dns expr: process_virtual_memory_bytes{k8s_app=~"kube-dns"} > 2000000000 for: 2s labels: severity: warnning annotations: description: "插件{{$labels.k8s_app}}({{$labels.instance}}): 使用虚拟内存超过2G" value: "{{ $value }}" - alert: HttpRequestsAvg expr: sum(rate(rest_client_requests_total{job=~"kubernetes-kube-proxy|kubernetes-kubelet|kubernetes-schedule|kubernetes-control-manager|kubernetes-apiservers"}[1m])) > 1000 for: 2s labels: team: admin annotations: description: "组件{{$labels.job}}({{$labels.instance}}): TPS超过1000" value: "{{ $value }}" threshold: "1000" - alert: Pod_restarts expr: kube_pod_container_status_restarts_total{namespace=~"kube-system|default|monitor-sa"} > 0 for: 2s labels: severity: warnning annotations: description: "在{{$labels.namespace}}名称空间下发现{{$labels.pod}}这个pod下的容器{{$labels.container}}被重启,这个监控指标是由{{$labels.instance}}采集的" value: "{{ $value }}" threshold: "0" - alert: Pod_waiting expr: kube_pod_container_status_waiting_reason{namespace=~"kube-system|default"} == 1 for: 2s labels: team: admin annotations: description: "空间{{$labels.namespace}}({{$labels.instance}}): 发现{{$labels.pod}}下的{{$labels.container}}启动异常等待中" value: "{{ $value }}" threshold: "1" - alert: Pod_terminated expr: kube_pod_container_status_terminated_reason{namespace=~"kube-system|default|monitor-sa"} == 1 for: 2s labels: team: admin annotations: description: "空间{{$labels.namespace}}({{$labels.instance}}): 发现{{$labels.pod}}下的{{$labels.container}}被删除" value: "{{ $value }}" threshold: "1" - alert: Etcd_leader expr: etcd_server_has_leader{job="kubernetes-etcd"} == 0 for: 2s labels: team: admin annotations: description: "组件{{$labels.job}}({{$labels.instance}}): 当前没有leader" value: "{{ $value }}" threshold: "0" - alert: Etcd_leader_changes expr: rate(etcd_server_leader_changes_seen_total{job="kubernetes-etcd"}[1m]) > 0 for: 2s labels: team: admin annotations: description: "组件{{$labels.job}}({{$labels.instance}}): 当前leader已发生改变" value: "{{ $value }}" threshold: "0" - alert: Etcd_failed expr: rate(etcd_server_proposals_failed_total{job="kubernetes-etcd"}[1m]) > 0 for: 2s labels: team: admin annotations: description: "组件{{$labels.job}}({{$labels.instance}}): 服务失败" value: "{{ $value }}" threshold: "0" - alert: Etcd_db_total_size expr: etcd_debugging_mvcc_db_total_size_in_bytes{job="kubernetes-etcd"} > 10000000000 for: 2s labels: team: admin annotations: description: "组件{{$labels.job}}({{$labels.instance}})：db空间超过10G" value: "{{ $value }}" threshold: "10G" - alert: Endpoint_ready expr: kube_endpoint_address_not_ready{namespace=~"kube-system|default"} == 1 for: 2s labels: team: admin annotations: description: "空间{{$labels.namespace}}({{$labels.instance}}): 发现{{$labels.endpoint}}不可用" value: "{{ $value }}" threshold: "1" - name: 物理节点状态-监控告警 rules: - alert: 物理节点cpu使用率 expr: 100-avg(irate(node_cpu_seconds_total{mode="idle"}[5m])) by(instance)*100 > 90 for: 2s labels: severity: ccritical annotations: summary: "{{ $labels.instance }}cpu使用率过高" description: "{{ $labels.instance }}的cpu使用率超过90%,当前使用率[{{ $value }}],需要排查处理" - alert: 物理节点内存使用率 expr: (node_memory_MemTotal_bytes - (node_memory_MemFree_bytes + node_memory_Buffers_bytes + node_memory_Cached_bytes)) / node_memory_MemTotal_bytes * 100 > 90 for: 2s labels: severity: critical annotations: summary: "{{ $labels.instance }}内存使用率过高" description: "{{ $labels.instance }}的内存使用率超过90%,当前使用率[{{ $value }}],需要排查处理" - alert: InstanceDown expr: up == 0 for: 2s labels: severity: critical annotations: summary: "{{ $labels.instance }}: 服务器宕机" description: "{{ $labels.instance }}: 服务器延时超过2分钟" - alert: 物理节点磁盘的IO性能 expr: 100-(avg(irate(node_disk_io_time_seconds_total[1m])) by(instance)* 100) < 60 for: 2s labels: severity: critical annotations: summary: "{{$labels.mountpoint}} 流入磁盘IO使用率过高！" description: "{{$labels.mountpoint }} 流入磁盘IO大于60%(目前使用:{{$value}})" - alert: 入网流量带宽 expr: ((sum(rate (node_network_receive_bytes_total{device!~'tap.*|veth.*|br.*|docker.*|virbr*|lo*'}[5m])) by (instance)) / 100) > 102400 for: 2s labels: severity: critical annotations: summary: "{{$labels.mountpoint}} 流入网络带宽过高！" description: "{{$labels.mountpoint }}流入网络带宽持续5分钟高于100M. RX带宽使用率{{$value}}" - alert: 出网流量带宽 expr: ((sum(rate (node_network_transmit_bytes_total{device!~'tap.*|veth.*|br.*|docker.*|virbr*|lo*'}[5m])) by (instance)) / 100) > 102400 for: 2s labels: severity: critical annotations: summary: "{{$labels.mountpoint}} 流出网络带宽过高！" description: "{{$labels.mountpoint }}流出网络带宽持续5分钟高于100M. RX带宽使用率{{$value}}" - alert: TCP会话 expr: node_netstat_Tcp_CurrEstab > 1000 for: 2s labels: severity: critical annotations: summary: "{{$labels.mountpoint}} TCP_ESTABLISHED过高！" description: "{{$labels.mountpoint }} TCP_ESTABLISHED大于1000%(目前使用:{{$value}}%)" - alert: 磁盘容量 expr: 100-(node_filesystem_free_bytes{fstype=~"ext4|xfs"}/node_filesystem_size_bytes {fstype=~"ext4|xfs"}*100) > 80 for: 2s labels: severity: critical annotations: summary: "{{$labels.mountpoint}} 磁盘分区使用率过高！" description: "{{$labels.mountpoint }} 磁盘分区使用大于80%(目前使用:{{$value}}%)" END [root@master1 prometheus] configmap "prometheus-config" deleted [root@master1 prometheus] configmap/prometheus-config created [root@master1 prometheus] NAME DATA AGE alertmanager 1 75m kube-root-ca.crt 1 2d20h prometheus-config 2 5s 安装 prometheus 和 alertmanager
需要把 alertmanager.tar.gz 镜像包上传的 k8s 的各个工作节点,这个环境仅有node1，手动解压：
[root@node1 prometheus] alertmanager.tar.gz [root@node1 prometheus] 32M alertmanager.tar.gz [root@node1 prometheus] 4febd3792a1f: Loading layer [==================================================>] 1.36MB/1.36MB 68d1a8b41cc0: Loading layer [==================================================>] 2.586MB/2.586MB 5f70bf18a086: Loading layer [==================================================>] 1.024kB/1.024kB 30d4e7b232e4: Loading layer [==================================================>] 12.77MB/12.77MB 6b961451fcb0: Loading layer [==================================================>] 16.59MB/16.59MB b5abc4736d3f: Loading layer [==================================================>] 6.144kB/6.144kB Loaded image: prom/alertmanager:v0.14.0 在 k8s 的控制节点master1生成一个 prometheus-alertmanager-deploy.yaml
[root@master1 prometheus] --- apiVersion: apps/v1 kind: Deployment metadata: name: prometheus-server namespace: monitor-sa labels: app: prometheus spec: replicas: 1 selector: matchLabels: app: prometheus component: server template: metadata: labels: app: prometheus component: server annotations: prometheus.io/scrape: 'false' spec: nodeName: node1 serviceAccountName: monitor containers: - name: prometheus image: prom/prometheus:v2.2.1 imagePullPolicy: IfNotPresent command: - "/bin/prometheus" args: - "--config.file=/etc/prometheus/prometheus.yml" - "--storage.tsdb.path=/prometheus" - "--storage.tsdb.retention=24h" - "--web.enable-lifecycle" ports: - containerPort: 9090 protocol: TCP volumeMounts: - mountPath: /etc/prometheus name: prometheus-config - mountPath: /prometheus/ name: prometheus-storage-volume - name: k8s-certs mountPath: /var/run/secrets/kubernetes.io/k8s-certs/etcd/ - name: localtime mountPath: /etc/localtime - name: alertmanager image: prom/alertmanager:v0.14.0 imagePullPolicy: IfNotPresent args: - "--config.file=/etc/alertmanager/alertmanager.yml" - "--log.level=debug" ports: - containerPort: 9093 protocol: TCP name: alertmanager volumeMounts: - name: alertmanager-config mountPath: /etc/alertmanager - name: alertmanager-storage mountPath: /alertmanager - name: localtime mountPath: /etc/localtime volumes: - name: prometheus-config configMap: name: prometheus-config - name: prometheus-storage-volume hostPath: path: /data type: Directory - name: k8s-certs secret: secretName: etcd-certs - name: alertmanager-config configMap: name: alertmanager - name: alertmanager-storage hostPath: path: /data/alertmanager type: DirectoryOrCreate - name: localtime hostPath: path: /usr/share/zoneinfo/Asia/Shanghai END [root@master1 prometheus] secret/etcd-certs created You have new mail in /var/spool/mail/root [root@master1 prometheus] NAME TYPE DATA AGE default-token-78mw6 kubernetes.io/service-account-token 3 2d20h etcd-certs Opaque 3 24s monitor-token-gbxmj kubernetes.io/service-account-token 3 2d19h [root@master1 prometheus] Name: etcd-certs Namespace: monitor-sa Labels: <none> Annotations: <none> Type: Opaque Data ==== server.key: 1679 bytes ca.crt: 1058 bytes server.crt: 1176 bytes 通过 kubectl apply 更新资源清单 yaml 文件
[root@master1 prometheus] NAME READY STATUS RESTARTS AGE node-exporter-92k4d 1/1 Running 0 2d20h node-exporter-d44k4 1/1 Running 0 2d20h prometheus-server-657bd8cb4d-zrmk4 1/1 Running 0 2d15h [root@master1 prometheus] deployment.apps "prometheus-server" deleted [root@master1 prometheus] NAME READY STATUS RESTARTS AGE node-exporter-92k4d 1/1 Running 0 2d20h node-exporter-d44k4 1/1 Running 0 2d20h [root@master1 prometheus] deployment.apps/prometheus-server created [root@master1 prometheus] NAME READY UP-TO-DATE AVAILABLE AGE prometheus-server 1/1 1 1 6s [root@master1 prometheus] NAME DESIRED CURRENT READY AGE prometheus-server-55cd9cb6d7 1 1 1 24s [root@master1 prometheus] NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES node-exporter-92k4d 1/1 Running 0 2d20h 192.168.1.181 node1 <none> <none> node-exporter-d44k4 1/1 Running 0 2d20h 192.168.1.180 master1 <none> <none> prometheus-server-55cd9cb6d7-v7rwh 2/2 Running 0 32s 10.244.166.188 node1 <none> <none> 部署 alertmanager 的 service，方便在浏览器访问
在 k8s 的控制节点生成一个 alertmanager-svc.yaml 文件
[root@master1 prometheus] --- apiVersion: v1 kind: Service metadata: labels: name: prometheus kubernetes.io/cluster-service: 'true' name: alertmanager namespace: monitor-sa spec: ports: - name: alertmanager nodePort: 30066 port: 9093 protocol: TCP targetPort: 9093 selector: app: prometheus sessionAffinity: None type: NodePort END [root@master1 prometheus] alertmanager-svc.yaml [root@master1 prometheus] 4.0K alertmanager-svc.yaml [root@master1 prometheus] service/alertmanager created You have new mail in /var/spool/mail/root [root@master1 prometheus] NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE alertmanager NodePort 10.110.81.137 <none> 9093:30066/TCP 16s prometheus NodePort 10.103.238.66 <none> 9090:31935/TCP 2d16h 使用master1的IP访问alertmanager UI
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访问 prometheus 的 web 界面
点击 status->targets，可看到如下
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从上面可以发现 kubernetes-controller-manager 和 kubernetes-schedule 都显示连接不上对应的端
可按如下方法处理：
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因为kube-proxy是受控制器管理的，所以删除后会自动重建 kubectl get pods -n kube-system|grep kube-proxy|awk '{print $1}'|xargs kubectl delete pods -n kube-system 可以看到相应的端口已经被物理机监听了
检查邮箱发现已收到邮件报警
扩展：暴力更新配置文件
修改 prometheus 任何一个配置文件之后，可通过 kubectl apply 使配置生效，执行顺序如下：
kubectl delete -f alertmanager-cm.yaml
kubectl apply -f alertmanager-cm.yaml
kubectl delete -f prometheus-alertmanager-cfg.yaml
kubectl apply -f prometheus-alertmanager-cfg.yaml
kubectl delete -f prometheus-alertmanager-deploy.yaml
kubectl apply -f prometheus-alertmanager-deploy.yaml
6. 配置 alertmanager-发送报警到钉钉
打开电脑版钉钉创建机器人
1.创建钉钉机器人
打开电脑版钉钉，创建一个群，创建自定义机器人，按如下步骤创建
https://ding-doc.dingtalk.com/doc#/serverapi2/qf2nxq
https://developers.dingtalk.com/document/app/custom-robot-access
我创建的机器人如下：
群设置–>智能群助手–>添加机器人–>自定义–>添加
机器人名称：test
接收群组：钉钉报警测试
安全设置：
自定义关键词：cluster1
上面配置好之后点击完成即可，这样就会创建一个 test 的报警机器人，创建机器人成功之后怎么查
看 webhook，按如下：
点击智能群助手，可以看到刚才创建的 test 这个机器人，点击 test，就会进入到 test 机器人的设
置界面
出现如下内容：
机器人名称：test
接受群组：钉钉报警测试
消息推送：开启
webhook：
这个每个人得到的不一样，复制备用
安全设置：
自定义关键词：cluster1
安装钉钉的 webhook 插件，在 k8s 的控制节点 master1 操作
prometheus-webhook-dingtalk-0.3.0.linux-amd64.tar.gz 压缩包所在的百度网盘地址如下：
链接：https://pan.baidu.com/s/1bxkiE83Nv5dEvLB1ZldEcw
提取码：ndm4
tar zxvf prometheus-webhook-dingtalk-0.3.0.linux-amd64.tar.gz
cd prometheus-webhook-dingtalk-0.3.0.linux-amd64
启动钉钉报警插件
nohup ./prometheus-webhook-dingtalk --web.listen-address=“0.0.0.0:8060” –
ding.profile=“cluster1=xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx” &
这里的xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx是前面复制的webhook
对原来的 alertmanager-cm.yaml 文件做备份
cp alertmanager-cm.yaml alertmanager-cm.yaml.bak
重新生成一个新的 alertmanager-cm.yaml 文件
[root@master1 prometheus] kind: ConfigMap apiVersion: v1 metadata: name: alertmanager namespace: monitor-sa data: alertmanager.yml: |- global: resolve_timeout: 1m smtp_smarthost: 'smtp.qq.com:465' smtp_from: 'xxxxx@qq.com' smtp_auth_username: 'xxxxx' smtp_auth_password: 'xxxxxxxxx' smtp_require_tls: false route: group_by: [alertname] group_wait: 10s group_interval: 10s repeat_interval: 10m receiver: cluster1 receivers: - name: 'cluster1' webhook_configs: - url: 'http://192.168.1.180:8060/dingtalk/cluster1/send' send_resolved: true END [root@master1 prometheus] configmap "alertmanager" deleted [root@master1 prometheus] configmap/alertmanager created [root@master1 prometheus] configmap "prometheus-config" deleted [root@master1 prometheus] configmap/prometheus-config created [root@master1 prometheus] deployment.apps "prometheus-server" deleted [root@master1 prometheus] deployment.apps/prometheus-server created 7. 配置 alertmanager-发送报警到微信
注册企业微信
登陆网址：
https://work.weixin.qq.com/
找到应用管理，创建应用
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应用名字 wechat
创建成功之后显示如下：
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[root@master1 prometheus] kind: ConfigMap apiVersion: v1 metadata: name: alertmanager namespace: monitor-sa data: alertmanager.yml: |- global: resolve_timeout: 1m smtp_smarthost: 'smtp.qq.com:465' smtp_from: 'xxxxx@qq.com' smtp_auth_username: 'xxxxx' smtp_auth_password: 'xxxxxxx' smtp_require_tls: false route: group_by: [alertname] group_wait: 10s group_interval: 10s repeat_interval: 10m receiver: prometheus receivers: - name: 'prometheus' wechat_configs: - corp_id: ww7xxxxxx to_user: '@all' agent_id: 1000003 api_secret: xxxxxxxxxxxxxxxxxxxx END [root@master1 prometheus] configmap "alertmanager" deleted [root@master1 prometheus] configmap/alertmanager created [root@master1 prometheus] [root@master1 prometheus] deployment.apps/prometheus-server created [root@master1 prometheus] NAME READY STATUS RESTARTS AGE node-exporter-92k4d 1/1 Running 0 3d5h node-exporter-d44k4 1/1 Running 2 3d5h prometheus-server-55cd9cb6d7-6pj7z 2/2 Running 0 28s 发送成功
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8. Prometheus 监控扩展
tomcat_exporter地址
链接：https://pan.baidu.com/s/1E2nDbVX3VcRxTxxowVaNtQ
提取码：nrml
下面在k8s-node节点操作
（1）制作tomcat镜像，按如下步骤
mkdir /root/tomcat_image 把上面的war包和jar包传到这个目录下
cd /root/tomcat_image cat > Dockerfile <<END FROM tomcat ADD metrics.war /usr/local/tomcat/webapps/ ADD simpleclient-0.8.0.jar /usr/local/tomcat/lib/ ADD simpleclient_common-0.8.0.jar /usr/local/tomcat/lib/ ADD simpleclient_hotspot-0.8.0.jar /usr/local/tomcat/lib/ ADD simpleclient_servlet-0.8.0.jar /usr/local/tomcat/lib/ ADD tomcat_exporter_client-0.0.12.jar /usr/local/tomcat/lib/ END [root@node1 tomcat_image] [root@node1 tomcat_image] REPOSITORY TAG IMAGE ID CREATED SIZE mack/tomcat_prometheus v1 d60e7a86371f 7 minutes ago 680MB 基于上面的镜像创建一个tomcat实例
下面操作在master1节点进行
cat > /root/tomcat_deploy.yaml <<END apiVersion: apps/v1 kind: Deployment metadata: name: tomcat-deployment namespace: default spec: selector: matchLabels: app: tomcat replicas: 2 # tells deployment to run 2 pods matching the template template: # create pods using pod definition in this template metadata: labels: app: tomcat annotations: prometheus.io/scrape: 'true' spec: containers: - name: tomcat image: mack/tomcat_prometheus:v1 imagePullPolicy: IfNotPresent ports: - containerPort: 8080 securityContext: privileged: true END kubectl apply -f tomcat_deploy.yaml deployment.apps/tomcat-deployment created 创建一个service，可操作也可不操作 cat > /root/tomcat-service.yaml <<END kind: Service #service 类型 apiVersion: v1 metadata: # annotations: # prometheus.io/scrape: 'true' name: tomcat-service spec: selector: app: tomcat ports: - nodePort: 31360 port: 80 protocol: TCP targetPort: 8080 type: NodePort END kubectl apply -f tomcat-service.yaml 在promethues上可以看到监控到tomcat的pod了
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[root@master1 ~] [root@master1 ~] [root@master1 ~] [root@master1 ~] mysqld_exporter-0.10.0.linux-amd64.tar.gz [root@master1 ~] 3.3M mysqld_exporter-0.10.0.linux-amd64.tar.gz [root@master1 ~] mysqld_exporter-0.10.0.linux-amd64/ mysqld_exporter-0.10.0.linux-amd64/LICENSE mysqld_exporter-0.10.0.linux-amd64/NOTICE mysqld_exporter-0.10.0.linux-amd64/mysqld_exporter [root@master1 ~] cd mysqld_exporter-0.10.0.linux-amd64 cp -ar mysqld_exporter /usr/local/bin/ [root@master1 mysqld_exporter-0.10.0.linux-amd64] [root@master1 bin] total 10176 -rwxr-xr-x 1 1000 1000 10419174 Apr 25 2017 mysqld_exporter 登陆 mysql 为 mysql_exporter 创建账号并授权
创建数据库用户。
mysql
CREATE USER ‘mysql_exporter’@‘localhost’ IDENTIFIED BY ‘Abcdef123!.’;
对 mysql_exporter 用户授权
mysql
GRANT PROCESS, REPLICATION CLIENT, SELECT ON . TO ‘mysql_exporter’@‘localhost’;
exit 退出 mysql
创建 mysql 配置文件、运行时可免密码连接数据库：
cd mysqld_exporter-0.10.0.linux-amd64 cat > my.cnf <<END [client] user=mysql_exporter password=Abcdef123!. END 启动 mysql_exporter 客户端
nohup ./mysqld_exporter --config.my-cnf=./my.cnf & mysqld_exporter 的监听端口是 9104
修改 prometheus-alertmanager-cfg.yaml 文件，添加如下
- job_name: 'mysql' static_configs: - targets: ['192.168.40.180:9104'] [外链图片转存失败,源站可能有防盗链机制,建议将图片保存下来直接上传(img-1MXnUv62-1655106671770)(C:\Users\mack\AppData\Roaming\Typora\typora-user-images\1655026431623.png)]
[root@master1 prometheus]# kubectl delete -f prometheus-alertmanager-cfg.yaml configmap "prometheus-config" deleted [root@master1 prometheus]# kubectl apply -f prometheus-alertmanager-cfg.yaml configmap/prometheus-config created [root@master1 prometheus]# kubectl delete -f prometheus-alertmanager-deploy.yaml deployment.apps "prometheus-server" deleted [root@master1 prometheus]# kubectl apply -f prometheus-alertmanager-deploy.yaml deployment.apps/prometheus-server created grafana 导入 mysql 监控图表
mysql-overview_rev5.json
所需要的文件下载地址
链接：https://pan.baidu.com/s/1SD1TPFNjBnf9wLIfiQVqHg
提取码：uf3f
[root@master1 prometheus] nginx-module-vts-master.zip [root@master1 prometheus] 400K nginx-module-vts-master.zip [root@master1 prometheus] [root@master1 prometheus] [root@master1 prometheus] nginx-1.15.7.tar.gz [root@master1 prometheus] 1004K nginx-1.15.7.tar.gz [root@master1 nginx-1.15.7] [root@master1 nginx-1.15.7] [root@master1 nginx-1.15.7] 修改nginx配置文件： vim /usr/local/nginx/conf/nginx.conf location /status { vhost_traffic_status_display; vhost_traffic_status_display_format html; } vhost_traffic_status_zone; [root@master1 nginx-1.15.7] nginx: the configuration file /usr/local/nginx/conf/nginx.conf syntax is ok nginx: configuration file /usr/local/nginx/conf/nginx.conf test is successful [root@master1 nginx-1.15.7] [外链图片转存失败,源站可能有防盗链机制,建议将图片保存下来直接上传(img-16Flps63-1655106671771)(C:\Users\mack\AppData\Roaming\Typora\typora-user-images\1655105057783.png)]
[root@master1 prometheus] nginx-vts-exporter-0.5.zip [root@master1 prometheus] 3.2M nginx-vts-exporter-0.5.zip [root@master1 prometheus] [root@master1 prometheus] [root@master1 prometheus] [root@master1 bin] total 8932 -rw-r--r-- 1 root root 9145803 Mar 16 2017 nginx-vts-exporter [root@master1 bin] You have new mail in /var/spool/mail/root [root@master1 bin] total 8932 -rwxr-xr-x 1 root root 9145803 Mar 16 2017 nginx-vts-exporter [root@master1 bin] [3] 17102 You have new mail in /var/spool/mail/root [root@master1 bin] [root@master1 bin] [root@master1 bin] 2022/06/13 15:31:46 Starting nginx_vts_exporter (version=0.4, branch=fix-docker-error, revision=0f3dbb44a86340d65bf3d6abbcc0ee88663cb419) 2022/06/13 15:31:46 Build context (go=go1.8, user=Administrator@LS--20151110SAS, date=20170316-03:16:26) 2022/06/13 15:31:46 Starting Server at : :9913 2022/06/13 15:31:46 Metrics endpoint: /metrics 2022/06/13 15:31:46 Metrics namespace: nginx 2022/06/13 15:31:46 Scraping information from : http://192.168.1.180/status/format/json 添加如下job - job_name: 'nginx' scrape_interval: 5s static_configs: - targets: ['192.168.1.180:9913'] [root@master1 prometheus] configmap "prometheus-config" deleted [root@master1 prometheus] configmap/prometheus-config created [root@master1 prometheus] deployment.apps "prometheus-server" deleted [root@master1 prometheus] deployment.apps/prometheus-server created nfiguration file /usr/local/nginx/conf/nginx.conf test is successful
#如果正确没问题，启动nginx
#启动nginx：
[root@master1 nginx-1.15.7]# /usr/local/nginx/sbin/nginx
#访问192.168.1.180/status可以看到nginx监控数据
[外链图片转存中...(img-16Flps63-1655106671771)] ```bash #3,安装nginx-vts-exporter [root@master1 prometheus]# ls nginx-vts-exporter-0.5.zip nginx-vts-exporter-0.5.zip [root@master1 prometheus]# du -sh nginx-vts-exporter-0.5.zip 3.2M nginx-vts-exporter-0.5.zip [root@master1 prometheus]# unzip nginx-vts-exporter-0.5.zip [root@master1 prometheus]# mv nginx-vts-exporter-0.5 /usr/local/ [root@master1 prometheus]# cd /usr/local/nginx-vts-exporter-0.5/bin/ [root@master1 bin]# ls -l total 8932 -rw-r--r-- 1 root root 9145803 Mar 16 2017 nginx-vts-exporter [root@master1 bin]# chmod a+x nginx-vts-exporter You have new mail in /var/spool/mail/root [root@master1 bin]# ls -l total 8932 -rwxr-xr-x 1 root root 9145803 Mar 16 2017 nginx-vts-exporter [root@master1 bin]# nohup ./nginx-vts-exporter -nginx.scrape_uri http://192.168.1.180/status/format/json & [3] 17102 You have new mail in /var/spool/mail/root [root@master1 bin]# nohup: ignoring input and appending output to ‘nohup.out’ [root@master1 bin]# [root@master1 bin]# cat nohup.out 2022/06/13 15:31:46 Starting nginx_vts_exporter (version=0.4, branch=fix-docker-error, revision=0f3dbb44a86340d65bf3d6abbcc0ee88663cb419) 2022/06/13 15:31:46 Build context (go=go1.8, user=Administrator@LS--20151110SAS, date=20170316-03:16:26) 2022/06/13 15:31:46 Starting Server at : :9913 2022/06/13 15:31:46 Metrics endpoint: /metrics 2022/06/13 15:31:46 Metrics namespace: nginx 2022/06/13 15:31:46 Scraping information from : http://192.168.1.180/status/format/json #nginx-vts-exporter的监听端口是9913 #4 修改prometheus-alertmanager-cfg.yaml文件 添加如下job - job_name: 'nginx' scrape_interval: 5s static_configs: - targets: ['192.168.1.180:9913'] [root@master1 prometheus]# kubectl delete -f prometheus-alertmanager-cfg.yaml configmap "prometheus-config" deleted [root@master1 prometheus]# kubectl apply -f prometheus-alertmanager-cfg.yaml configmap/prometheus-config created [root@master1 prometheus]# kubectl delete -f prometheus-alertmanager-deploy.yaml deployment.apps "prometheus-server" deleted [root@master1 prometheus]# kubectl apply -f prometheus-alertmanager-deploy.yaml deployment.apps/prometheus-server created #5 在grafana界面导入nginx json 以上内容由“WiFi之家网”整理收藏！。
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