Prometheus+Grafana+altermanager监控k8s pod

环境k8s 1.26.8

centos7 master01 192.168.126.21
centos7 worker01 192.168.126.22
centos7 worker02 192.168.126.23

prometheus server
Retrieval 负责在活跃的 target 主机上抓取监控指标数据。
Storage 存储主要是把采集到的数据存储到磁盘中。
PromQL 是 Prometheus 提供的查询语言模块。

Exporters
prometheus 支持多种 exporter，通过 exporter 可以采集 metrics 数据，然后发送到prometheus server 端，所有向 promtheus server 提供监控数据的程序都可以被称为 exporter。

Client Library
客户端库，检测应用程序代码，当 Prometheus 抓取实例的 HTTP 端点时，客户端库会将所有跟踪的 metrics 指标的当前状态发送到 prometheus server 端。# Prometheus+Grafana搭建

Alertmanager
从 Prometheus server 端接收到 alerts 后，会进行去重，分组，并路由到相应的接收方，发出报警，常见的接收方式有：电子邮件，微信，钉钉, slack 等。

Grafana
监控仪表盘，可视化监控数据。

kube-state-metrics
监控的是k8s资源的状态，比如pod、容器、job的个数等

镜像准备

docker下载镜像

由于k8s直接下载镜像拉不下来，先用docker 下载然后导入k8s仓库

docker pull noenv/node-exporter:1.7.0
docker pull prom/prometheus:v2.45.5
docker pull bitnami/kube-state-metrics:2.12.0
docker pull prom/alertmanager:v0.27.0
docker pull grafana/grafana:10.0.3

保存镜像为tar包

IMAGE='noenv/node-exporter:1.7.0'
docker save -o  neonv.node-exporter_1.7.0.tar $IMAGE

IMAGE='prom/prometheus:v2.45.5'
docker save -o  prom.prometheus_v2.45.5.tar $IMAGE

IMAGE='bitnami/kube-state-metrics:2.12.0'
docker save -o  bitnami.kube-state-metrics_2.12.0.tar $IMAGE

IMAGE='grafana/grafana:10.0.3'
docker save -o grafana.grafana_10.0.3.tar $IMAGE

IMAGE='prom/alertmanager:v0.27.0'
docker save -o prom.alertmanager_v0.27.0.tar  $IMAGE

ctr导入镜像tar包到k8s本地库

ctr -n=k8s.io images import neonv.node-exporter_1.7.0.tar
ctr -n=k8s.io images import prom.prometheus_v2.45.5.tar
ctr -n=k8s.io images import bitnami.kube-state-metrics_2.12.0.tar
ctr -n=k8s.io images import grafana.grafana_10.0.3.tar
ctr -n=k8s.io images import prom.alertmanager_v0.27.0.tar

DaemonSet部署node-exporter

#创建名称空间

kubectl create ns monitor-sa    

创建node-exporter的daemonse，让每个节点运行

cat > node-exporter.yaml <<EOF
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                                             # 共享宿主机网络和进程
      containers:
      - name: node-exporter
        image: noenv/node-exporter:1.7.0
        imagePullPolicy: IfNotPresent  #必须要写，容易拉不了镜像
        ports:
        - containerPort: 9100                                       # 容器暴露端口为9100
        resources:
          requests:
            cpu: 0.15
        securityContext:
          privileged: true                                          # 开启特权模式
        args:
        - --path.procfs
        - /host/proc
        - --path.sysfs
        - /host/sys
        - --collector.filesystem.ignored-mount-points
        - '"^/(sys|proc|dev|host|etc)($|/)"'
        volumeMounts:                                               # 挂载宿主机目录以收集宿主机信息
        - name: dev
          mountPath: /host/dev
        - name: proc
          mountPath: /host/proc
        - name: sys
          mountPath: /host/sys
        - name: rootfs
          mountPath: /rootfs
      tolerations:                                                  # 定义容忍度，使其可调度到默认有污点的master，版本不同可能配置不同
      - key: "node-role.kubernetes.io/control-plane"
        effect: "NoSchedule"
      volumes:                                                      # 定义存储卷
        - name: proc
          hostPath:
            path: /proc
        - name: dev
          hostPath:
            path: /dev
        - name: sys
          hostPath:
            path: /sys
        - name: rootfs
          hostPath:
            path: /

EOF

#应用yaml文件

kubectl apply -f node-exporter.yaml 

#查看状态

kubectl get pods -n monitor-sa  

注意，如果安装过node-exporter一定要停止或者卸载，端口会冲突。
特权模式运行，占用宿主机端口

修改污点配置删除重新运行容器

测试数据采集是否成功，填写更换宿主机ip:9100

[root@k8s-master01 promethues]# curl http://192.168.126.21:9100/metrics |grep node_cpu_seconds

  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current
                                 Dload  Upload   Total   Spent    Left  Speed
  0     0    0     0    0     0      0      0 --:--:-- --:--:-- --:--:--     0# HELP node_cpu_seconds_total Seconds the CPUs spent in each mode.
# TYPE node_cpu_seconds_total counter
node_cpu_seconds_total{cpu="0",mode="idle"} 59336.42
node_cpu_seconds_total{cpu="0",mode="iowait"} 183.11
...................
node_cpu_seconds_total{cpu="1",mode="user"} 264.81
100 85858    0 85858    0     0  1260k      0 --:--:-- --:--:-- --:--:-- 1270k

安装Prometheus server服务

#创建sa账号
kubectl create serviceaccount monitor -n monitor-sa     
#sa账号授权           
kubectl create clusterrolebinding monitor-clusterrolebinding -n monitor-sa --clusterrole=cluster-admin --serviceaccount=monitor-sa:monitor    
#在要安装prometheus server的节点创建数据目录   
mkdir /data/prometheus                                                        
chmod 777 /data/prometheus               

创建cofigMap来配置promethues

#注意EOF上的单引号，加上防止替换变量，一定要注意缩进
cat >  prometheus-cfg.yaml << 'EOF'
kind: ConfigMap
apiVersion: v1
metadata:
  labels:
    app: prometheus
  name: prometheus-config
  namespace: monitor-sa
data:
  prometheus.yml: |
    # 全局配置
    global:
      scrape_interval: 10s # 将抓取间隔时间设置为每 15 秒一次。默认值为每1分钟一次。
      evaluation_interval: 15s # 规则重启评估的间隔时间设置为每隔15秒评一次。默认值为每1分钟一次。
      # scrape_timeout is set to the global default (10s).

    # 配置被监控对象
    scrape_configs:
      - job_name: "kubernetes-node"
        kubernetes_sd_configs: # k8s的服务发现
          - role: node # 使用kubelet提供的http端口发现node
        relabel_configs:
          - source_labels: [__address__]  #原始标签，匹配地址
            regex: '(.*):10250'
            replacement: '${1}:9100'
            target_label: __address__
            action: replace # 这段配置表示把匹配到的ip:10250替换为ip:9100
          - action: labelmap
            regex: __meta_kubernetes_node_label_(.+) # 匹配到该表达式的标签会保留

      - job_name: 'kubernetes-node-cadvisor' # 抓取 cAdvisor 数据，是获取 kubelet 上/metrics/cadvisor 接口数据来获取容器的资源使用情况
        kubernetes_sd_configs:
          - role: node
        scheme: https
        bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token 
        tls_config:
              ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crt
        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
        bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token 
        tls_config:
              ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crt
        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
EOF

创建configMap

kubectl apply -f prometheus-cfg.yaml

cat > prometheus-deploy.yaml <<EOF
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'                             # 该容器不会被prometheus发现并监控，其他pod可通过添加该注解（值为true）以服务发现的方式自动被prometheus监控到。
    spec:
      nodeName: k8s-worker01                                      #指定节点运行
      serviceAccountName: monitor                                 # 指定sa，使容器有权限获取数据
      containers:
      - name: prometheus                                          # 容器名称
        image: prom/prometheus:v2.45.5                            # 镜像名称
        imagePullPolicy: IfNotPresent                             # 镜像拉取策略
        command:                                                  # 容器启动时执行的命令
          - prometheus
          - --config.file=/etc/prometheus/prometheus.yml
          - --storage.tsdb.path=/prometheus                       # 旧数据存储目录
          - --storage.tsdb.retention=720h                         # 旧数据保留时间
          - --web.enable-lifecycle                                # 开启热加载
        ports:                                                    # 容器暴露的端口
        - containerPort: 9090
          protocol: TCP                                           # 协议
        volumeMounts:                                             # 容器挂载的数据卷
        - mountPath: /etc/prometheus                              # 要挂载到哪里
          name: prometheus-config                                 # 挂载谁（与下面定义的volume对应）
        - mountPath: /prometheus/                              
          name: prometheus-storage-volume
      securityContext:
         runAsUser: 0                                             #解决权限问题报错
      volumes:                                                    # 数据卷定义
        - name: prometheus-config                                 # 名称
          configMap:                                              # 从configmap获取数据
            name: prometheus-config                               # configmap的名称
        - name: prometheus-storage-volume
          hostPath:
            path: /data/prometheus 
            type: Directory
EOF

kubectl apply -f prometheus-deploy.yaml                            # 应用deployment
kubectl get pods -n monitor-sa  

cat > prometheus-svc.yaml<<EOF
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
EOF

配置service外部访问Prometheus。查看外部端口

kubectl apply -f prometheus-svc.yaml  

[root@k8s-master01 promethues]#  kubectl get svc -n monitor-sa
NAME         TYPE       CLUSTER-IP     EXTERNAL-IP   PORT(S)          AGE
prometheus   NodePort   10.104.88.36   <none>        9090:32201/TCP   2s

http://192.168.126.21:32201/

安装Grafana

在需要的节点上安装grafana
mkdir /data/grafana/ -p
chmod 777 /data/grafana/

cat >  grafana-conf.yaml <<EOF
apiVersion: v1
kind: ConfigMap
metadata:
  name: grafana-config
  namespace: kube-system
data:
  grafana.ini: |
    [users]
    default_language = zh-Hans
EOF

cat > grafana.yaml<<EOF

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:
      nodeName: k8s-worker01                                                 # 要安装到哪个节点
      containers:
      - name: grafana
        image: grafana/grafana:10.0.3
        imagePullPolicy: IfNotPresent
        ports:
        - containerPort: 3000
          protocol: TCP
        volumeMounts:
        - mountPath: /etc/ssl/certs
          name: ca-certificates
          readOnly: true
        - mountPath: /var
          name: grafana-storage
        - mountPath: /var/lib/grafana/
          name: data
        - mountPath: /etc/grafana
          name: grafana-config

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

EOF


#应用yaml文件
kubectl apply -f grafana.yaml     

#查看pod工作状态（running）                          
kubectl get pods -n kube-system| grep monitor                      
kubectl get svc -n kube-system | grep grafana  

右上角登录用户名密码都是admin，然后修改密码进入

填写数据接口地址
http://prometheus.monitor-sa.svc:9090

由于不能访问外网，所以，只能下载json

安装kube-state-metrics（监控k8s资源状态）

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。

原文链接：https://blog.csdn.net/qq_35995514/article/details/137217639

创建服务账号，创建角色，绑定角色

cat> kube-state-metrics-rbac.yaml<<EOF
apiVersion: v1                                                     # api版本：v1
kind: ServiceAccount                                               # 资源类型：服务账号
metadata:                                                          # 元数据
  name: kube-state-metrics                                         # 名称
  namespace: kube-system                                           # 名称空间
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole                                                  # 资源类型：集群角色 
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
EOF

kubectl apply -f kube-state-metrics-rbac.yaml

cat >kube-state-metrics-deploy.yaml<<EOF
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: bitnami/kube-state-metrics:2.12.0
        imagePullPolicy: IfNotPresent
        ports:
        - containerPort: 8080
EOF
kubectl apply -f kube-state-metrics-deploy.yaml   

查看状态

[root@k8s-master01 promethues]# kubectl get pods -n kube-system -l app=kube-state-metrics
NAME                                  READY   STATUS    RESTARTS   AGE
kube-state-metrics-7c468d56bf-nfwph   1/1     Running   0          18s

cat> kube-state-metrics-svc.yaml<<EOF
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
EOF
kubectl apply -f kube-state-metrics-svc.yaml 

#查看服务状态
kubectl get svc -n kube-system | grep kube-state-metrics          
kube-state-metrics   ClusterIP   10.111.224.27    <none>        8080/TCP                 48m

面板下载地址
https://grafana.com/grafana/dashboards/13332-kube-state-metrics-v2/

prometheus.io/scrape: 'true'让kube-state-metrics被自动发现，如果没有就配置一下

kube-state-metrics没法被Prometheus发现，需要暴露端口给Prometheus
kube-state-metrics-svc.yaml修改为NodePort暴露30091端口

apiVersion: v1
kind: Service
metadata:
  annotations:
    prometheus.io/scrape: 'true'
  name: kube-state-metrics
  namespace: kube-system
  labels:
    app: kube-state-metrics
spec:
  type: NodePort
  ports:
  - name: kube-state-metrics
    port: 8080
    nodePort: 30091
    targetPort: 8080
    protocol: TCP
  selector:
    app: kube-state-metrics

kubectl apply -f kube-state-metrics-svc.yaml
在Prometheus配置文件中添加对数据的监控

 # 配置被监控对象
    scrape_configs:
      - job_name: "kube-state-metrics"
        static_configs:
            - targets: ["192.168.126.22:30091"]

kubectl apply -f prometheus-cfg.yaml

快速删除pod重新生成生效
kubectl get pod -n monitor-sa | grep '^prometheus-server' | awk '{print $1}'| xargs kubectl delete pod  -n monitor-sa

创建altermanager配置邮箱报警

altermanager配置coonfigMap进行挂载

cat > altermanager-cm.yaml <<EOF
kind: ConfigMap
apiVersion: v1
metadata:
  name: alertmanager
  namespace: monitor-sa
data:
  alertmanager.yml: |-                               # altermanager配置文件
    global:                            
      resolve_timeout: 1m                            
      smtp_smarthost: 'smtp.163.com:25'              # 发送者的SMTP服务器
      smtp_from: '1xxxxxx48@163.com'               # 发送者的邮箱
      smtp_auth_username: '1xxxx48'              # 发送者的邮箱用户名（不是邮箱名）
      smtp_auth_password: 'GKxxxxWWFA'         # 发送者授权密码（上面获取到的）
      smtp_require_tls: false
    route:                                           # 配置告警分发策略
      group_by: [alertname]                          # 采用哪个标签作为分组依据
      group_wait: 10s                                # 组告警等待时间（10s内的同组告警一起发送）
      group_interval: 10s                            # 两组告警的间隔时间
      repeat_interval: 10m                           # 重复告警的间隔时间
      receiver: default-receiver                     # 接收者配置
    receivers:
    - name: 'default-receiver'                       # 接收者名称（与上面对应）
      email_configs:                                 # 接收邮箱配置
      - to: '2xxxx4@qq.com'                      # 接收邮箱（填要接收告警的邮箱）
        send_resolved: true                          # 是否通知已解决的告警
EOF
kubectl apply -f altermanager-cm.yaml  

创建数据保存文件夹
mkdir /data/alertmanager/ -p
chmod 777 /data/alertmanager/

部署deployment应用容器

cat > alertmanager-deployment.yaml<<EOF
apiVersion: apps/v1
kind: Deployment
metadata:
  name: alertmanager
  namespace: monitor-sa
  labels:
    k8s-app: alertmanager
    kubernetes.io/cluster-service: "true"
    addonmanager.kubernetes.io/mode: Reconcile
spec:
  replicas: 1
  selector:
    matchLabels:
      k8s-app: alertmanager
  template:
    metadata:
      labels:
        k8s-app: alertmanager
    spec:
      nodeName: k8s-worker01                                                 # 要安装到哪个节点
      priorityClassName: system-cluster-critical
      containers:
        - name: prometheus-alertmanager
          image: "prom/alertmanager:v0.27.0"
          imagePullPolicy: "IfNotPresent"
          args:
            - --config.file=/etc/config/alertmanager.yml
            - --storage.path=/data
           # - --web.external-url=/
          ports:
            - containerPort: 9093
          readinessProbe:
            httpGet:
              path: /#/status
              port: 9093
            initialDelaySeconds: 30
            timeoutSeconds: 30
          volumeMounts:
            - name: config-volume
              mountPath: /etc/config
            - name: storage-volume
              mountPath: "/data"
              subPath: ""
      volumes:
        - name: config-volume
          configMap:
            name: alertmanager
        - name: storage-volume
          hostPath:
            path: /data/alertmanager/
            type: Directory
EOF
kubectl apply -f alertmanager-deployment.yaml

配置服务alertmanager，可以修改为NodePort，不过不必要

cat > alertmanager-service.yaml <<EOF
apiVersion: v1
kind: Service
metadata:
  name: alertmanager
  namespace: monitor-sa
  labels:
    kubernetes.io/cluster-service: "true"
    addonmanager.kubernetes.io/mode: Reconcile
    kubernetes.io/name: "Alertmanager"
spec:
  ports:
    - name: http
      port: 80
      protocol: TCP
      targetPort: 9093
  selector:
    k8s-app: alertmanager 
  type: "ClusterIP"
EOF

修改 prometheus-cfg.yaml配置文件

kind: ConfigMap
apiVersion: v1
metadata:
  labels:
    app: prometheus
  name: prometheus-config
  namespace: monitor-sa
data:
  rules.yml: |                                     # 报警规则配置
    groups:                                        # 组
    - name: example                                # 组名
      rules:                                       # 规则定义
      - alert: 测试容器还在运行                      # 报警项
        expr: kube_pod_container_status_running{container="nginx",pod="pod-deme"}==1   # 表达式（基于PromQL编写）
        for: 2s                                    # 满足表达式多久触发报警
        labels:
          severity: warnning                       # 报警等级
        annotations:                               # 报警时的提示信息
          description: "有正则运行的pod-deme的nginx容器，赶紧删了吧"
  prometheus.yml: |
    # 全局配置
    global:
      scrape_interval: 10s # 将抓取间隔时间设置为每 15 秒一次。默认值为每1分钟一次。
      evaluation_interval: 15s # 规则重启评估的间隔时间设置为每隔15秒评一次。默认值为每1分钟一次。
      # scrape_timeout is set to the global default (10s).
    alerting:
      alertmanagers:
       - static_configs:
          - targets: [ '10.97.93.114:80' ]

    rule_files:
      - /etc/prometheus/rules.yml
    # 配置被监控对象

    scrape_configs:
      - job_name: "kubernetes-node"
        kubernetes_sd_configs: # k8s的服务发现
          - role: node # 使用kubelet提供的http端口发现node
        relabel_configs:
          - source_labels: [__address__]  #原始标签，匹配地址
            regex: '(.*):10250'
            replacement: '${1}:9100'
            target_label: __address__
            action: replace # 这段配置表示把匹配到的ip:10250替换为ip:9100
          - action: labelmap
            regex: __meta_kubernetes_node_label_(.+) # 匹配到该表达式的标签会保留

      - job_name: 'kubernetes-node-cadvisor' 。。。。。。。
      剩下的和上面之前配置的一样

应用修改进行更新
kubectl apply -f prometheus-cfg.yaml


快速删除pod重新生成生效
kubectl get pod -n monitor-sa | grep '^prometheus-server' | awk '{print $1}'| xargs kubectl delete pod  -n monitor-sa

相容的警告10分钟发一次邮件

注释警告规则，删除Prometheus的pod解决这个警告，然后alertmanager收不到报警，发一个解决的邮件

优化配置

不想每次都重新生成configMap，将警告规则的配置挂载到宿主机目录
修改，缺点是在固定的节点运行

prometheus-cfg.yaml

 rule_files:
      - /etc/prometheus/rules.yml
      - /prometheus/config/*.yml

kubectl apply -f prometheus-cfg.yaml

mkdir  /data/prometheus/config -p
chmod 777 /data/prometheus/config
rm /data/prometheus/lock -f

快速删除pod重新生成生效
kubectl get pod -n monitor-sa | grep '^prometheus-server' | awk '{print $1}'| xargs kubectl delete pod  -n monitor-sa

 cat /data/prometheus/config/demo.yml
groups:                                        # 组
 - name: example                                # 组名
   rules:                                       # 规则定义
   - alert: 测试容器还在运行2                      # 报警项
     expr: kube_pod_container_status_running{container="nginx",pod="pod-deme"}==1   # 表达式（基于PromQL编写）
     for: 2s                                    # 满足表达式多久触发报警
     labels:
        severity: warnning                       # 报警等级
     annotations:                               # 报警时的提示信息
        description: "2:有正则运行的pod-deme的nginx容器，赶紧删了吧"

马上修改内容为

groups:                                        # 组
 - name: example                                # 组名
   rules:                                       # 规则定义
   - alert: 测试规则修改生效                     # 报警项
     expr: kube_pod_container_status_running{container="nginx",pod="pod-deme"}==1   # 表达式（基于PromQL编写）
     for: 2s                                    # 满足表达式多久触发报警
     labels:
        severity: warnning                       # 报警等级
     annotations:                               # 报警时的提示信息
        description: "测试运行的pod-deme的nginx容器，赶紧删了吧"

使用以下命令热加载配置，但是会导致之前的规则和现在的规则同时存在，这应该是alertmanager的问题，警告有一个失效的时间，大概几分钟，如不修改警告名称，生效应该会很快

curl -X POST http://192.168.126.21:32201/-/reload

除了热加载方法，还可以删除pod，重新运行

删除/data/prometheus/config/demo.yml，几分钟后警告消失，不会再收到邮件了

问题及解决

opening query log file” file=/prometheus/queries.active err=”open /prometheus/queries.active: permission denied”

原因： 权限问题，prometheus 的镜像中是使用的 nobody 这个用户，通过 hostPath 挂载到宿主机上面的目录的 ownership 是 root
解决： 在Pod 设置下设置安全上下文

  securityContext:
         runAsUser: 0  

Prometheusfield bearer_token_file not found in type config.plain

缩进错误 bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token
删除了运行，有的资源https无法获取，调整后即可

FAILED: parsing YAML file test.yaml: yaml: unmarshal errors:

line 24: field scheme not found in type kubernetes.plain
line 27: field bearer_token_file not found in type config.plain

yaml格式错误，调整每行的配置，不能缩进有问题

GF_PATHS_DATA=’/var/lib/grafana’ is not writable.

挂载目录的权限要设置777
chmod 777 /data/grafana/

参考

Prometheus+Grafana+altermanager监控k8s并配置报警[通俗易懂]