一、环境信息

1服务器K8S版本信息:

IP地址

主机名称

角色

K8S版本

16.32.15.200

master-1

Master节点

v1.23.0

16.32.15.201

node-1

Node节点

v1.23.0

16.32.15.202

node-2

Node节点

v1.23.0

2、部署组件版本:

序号

名称

版本

作用

1

Prometheus

v2.33.5

收集、存储和处理指标数据

2

Node_exporter

v0.16.0

采集服务器指标,如CPU、内存、磁盘、网络等

3

Kube-state-metrics

v1.9.0

采集K8S资源指标,如Pod、Node、Deployment、Service等

4

Grafana

v8.4.5

可视化展示Prometheus收集数据

3、离线包下载:

包括本实验的离线镜像包、导入Grafana所需的模板文件。

推荐模板:13332、13824、14518

1、导入模板

在这里插入图片描述
在这里插入图片描述

2、查看结果

在这里插入图片描述

二、部署前准备工作

1、创建名称空间,下面所有资源都放到这里

kubectl create ns prometheus

2、创建ServiceAccount账号,并绑定cluster-admin集群角色(Prometheus中需要指定)

kubectl create serviceaccount prometheus -n prometheus

kubectl create clusterrolebinding prometheus-clusterrolebinding -n prometheus --clusterrole=cluster-admin  --serviceaccount=prometheus:prometheus

#kubectl create clusterrolebinding prometheus-clusterrolebinding-1 -n prometheus --clusterrole=cluster-admin --user=system:serviceaccount:prometheus:prometheus

3、创建Prometheus存放数据目录
注意:我准备将Prometheus服务部署在Node-1节点,所以此步骤在Node-1节点执行

mkdir /data
chmod -R 777 /data

4、创建Grafana存放数据目录
我准备将Grafana服务部署在Node-1节点,所以此步骤也在Node-1节点执行

mkdir /var/lib/grafana/ -p
chmod 777 /var/lib/grafana/

5、时间同步 && 时区同步

# 时间同步
yum -y install ntpdate
/usr/sbin/ntpdate -u ntp1.aliyun.com

# 时区同步
timedatectl set-timezone Asia/Shanghai

定时同步:每天凌晨5点进行时间同步

echo "0 5 * * * /usr/sbin/ntpdate -u ntp1.aliyun.com >/dev/null &" >> /var/spool/cron/root

6、提前下载所需镜像

docker pull prom/prometheus:v2.33.5
docker pull prom/node-exporter:v0.16.0
docker pull quay.io/coreos/kube-state-metrics:v1.9.0
docker pull grafana/grafana:8.4.5

三、部署Prometheus监控系统

1、创建 ConfigMap资源

vim prometheus-cfg.yaml
---
kind: ConfigMap
apiVersion: v1
metadata:
  labels:
    app: prometheus
  name: prometheus-config
  namespace: prometheus
data:
  prometheus.yml: |
    global:
      scrape_interval: 15s           # 采集目标主机监控据的时间间隔
      scrape_timeout: 10s            # 数据采集超时时间,默认10s
      evaluation_interval: 1m        # 触发告警检测的时间,默认是1m
    scrape_configs:
    - job_name: 'kubernetes-node'
      kubernetes_sd_configs:          # 基于K8S的服务发现
      - role: node                    # 使用node模式服务发现
      relabel_configs:                # 正则匹配
      - source_labels: [__address__]  # 匹配带有IP的标签
        regex: '(.*):10250'           # 10250端口(kubelet端口)
        replacement: '${1}:9100'      # 替换成9100
        target_label: __address__
        action: replace
      - action: labelmap
        regex: __meta_kubernetes_node_label_(.+)
    - job_name: 'kubernetes-node-cadvisor' # cadvisor容器用于收集和提供有关节点上运行的容器的资源使用情况和性能指标
      kubernetes_sd_configs:
      - role:  node
      scheme: https
      tls_config:
        ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crt
      bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token
      relabel_configs:
      - action: labelmap   # 把匹配到的标签保留
        regex: __meta_kubernetes_node_label_(.+) # 保留匹配到的具有__meta_kubernetes_node_label的标签
      - target_label: __address__               
        replacement: kubernetes.default.svc:443
      - source_labels: [__meta_kubernetes_node_name]
        regex: (.+)
        target_label: __metrics_path__
        replacement: /api/v1/nodes/${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   # 使用k8s中的endpoint模式服务发现
      relabel_configs:
      - source_labels: [__meta_kubernetes_service_annotation_prometheus_io_scrape]
        action: keep      # 采集满足条件的实例,其他实例不采集
        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  

 执行配置清单:

kubectl apply -f  prometheus-cfg.yaml

查看ConfigMap资源信息:

kubectl get configmap -n prometheus prometheus-config

在这里插入图片描述

2、创建 Deployment资源

vim prometheus-deploy.yaml 
---
apiVersion: apps/v1
kind: Deployment
metadata:
  name: prometheus-server
  namespace: prometheus
  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: node-1                # 调度到node-1节点
      serviceAccountName: prometheus  # 指定sa服务账号
      containers:
      - name: prometheus
        image: prom/prometheus:v2.33.5
        imagePullPolicy: IfNotPresent
        command:                       # 启动时运行的命令
          - prometheus
          - --config.file=/etc/prometheus/prometheus.yml  # 指定配置文件
          - --storage.tsdb.path=/prometheus               # 数据存放目录
          - --storage.tsdb.retention=720h                 # 暴露720小时(30天)
          - --web.enable-lifecycle                        # 开启热加载
        ports:
        - containerPort: 9090
          protocol: TCP
        volumeMounts:
        - mountPath: /etc/prometheus       # 将prometheus-config卷挂载至/etc/prometheus
          name: prometheus-config
        - mountPath: /prometheus/
          name: prometheus-storage-volume
        #- name: localtime
        #  mountPath: /etc/localtime
      volumes:                           
        #- name: localtime
          #hostPath:
            #path: /etc/localtime
            #type: File
        - name: prometheus-config          # 将prometheus-config做成卷
          configMap:
            name: prometheus-config
        - name: prometheus-storage-volume 
          hostPath:
           path: /data
           type: Directory

注意1:我把Prometheus部署到node-1节点,这里填写节点名称,根据自己当前的环境写,其他配置如果是跟做,都不用改!!
注意2:可以将宿主机 /etc/localtime 文件挂载到容器中,但是第一次部署Prometheus可能会受到影响(也有可能是我是VMware虚拟机原因),如果访问Prometheus WEB页面提示时间不对,可以在``文件中添加如下配置,然后在apply一下即可!

        - name: localtime
          mountPath: /etc/localtime
      volumes:
        - name: localtime
          hostPath:
            path: /etc/localtime
            type: File

执行配置清单:

kubectl apply -f prometheus-deploy.yaml

查看Deployment资源信息:

kubectl get deployment prometheus-server -n prometheus

3、创建 Service资源

vim prometheus-svc.yaml
---
apiVersion: v1
kind: Service
metadata:
  name: prometheus-svc
  namespace: prometheus
  labels:
    app: prometheus
spec:
  type: NodePort
  ports:
    - port: 9090
      targetPort: 9090
      nodePort: 31090
      protocol: TCP
  selector:
    app: prometheus
    component: server

执行配置清单:

kubectl apply -f prometheus-svc.yaml

查看Service资源信息:

kubectl get svc prometheus-svc -n prometheus

4、浏览器访问:http://IP:31090
在这里插入图片描述

如上图,没有提示时间对上的问题,表示只此步骤,无误。

四、部署Node_exporter组件

我直接写到一个文件中了,方便执行!

vim node-export.yaml
---
apiVersion: apps/v1
kind: DaemonSet
metadata:
  name: node-exporter
  namespace: prometheus
  labels:
    name: node-exporter
spec:
  selector:
    matchLabels:
     name: node-exporter
  template:
    metadata:
      labels:
        name: node-exporter
    spec:
      hostPID: true
      hostIPC: true
      # 使用物理机IP地址(调度到那个节点,就使用该节点IP地址)
      hostNetwork: true
      containers:
      - name: node-exporter
        image: prom/node-exporter:v0.16.0
        imagePullPolicy: IfNotPresent
        ports:
        # 暴露端口
        - 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
        - name: localtime
          mountPath: /etc/localtime
      # 指定容忍度,允许调度到master节点
      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: /
        - name: localtime
          hostPath:
            path: /etc/localtime
            type: File

注意:需要根据环境修改容忍度tolerations 允许调度到Master节点,其他不用修改!!

可以使用以下命令查看master-1节点中的污点是什么,然后配置到上面的tolerations。

kubectl describe node master-1|grep -w Taints

执行资源清单:

kubectl apply -f node-export.yaml

查看资源信息,正常三个节点都要部署node_exporter,如果没有master节点,就要检查上面容忍度配置了。

kubectl get pods -n prometheus -o wide

五、部署Kube_state_metrics组件

关于kube-state-metrics资源,我也都写到一个文件中了,直接执行,不需要修改(前提是按照上面环境跟做的!)

vim kube-state-metrics.yaml
---
apiVersion: v1
kind: ServiceAccount
metadata:
  name: kube-state-metrics
  namespace: prometheus
---
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: prometheus
---
apiVersion: apps/v1
kind: Deployment
metadata:
  name: kube-state-metrics
  namespace: prometheus
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
        imagePullPolicy: IfNotPresent
        ports:
        - containerPort: 8080
---
apiVersion: v1
kind: Service
metadata:
  annotations:
    prometheus.io/scrape: 'true'
  name: kube-state-metrics
  namespace: prometheus
  labels:
    app: kube-state-metrics
spec:
  ports:
  - name: kube-state-metrics
    port: 8080
    protocol: TCP
  selector:
    app: kube-state-metrics

执行资源清单:

kubectl apply -f kube-state-metrics.yaml

查看资源信息:

kubectl get pods -n prometheus

六、部署Grafana可视化平台

注意:修改nodeName指定部署到Node节点,其他不用修改!!

vim grafana.yaml
---
apiVersion: apps/v1
kind: Deployment
metadata:
  name: grafana-server
  namespace: prometheus
spec:
  replicas: 1
  selector:
    matchLabels:
      task: monitoring
      k8s-app: grafana
  template:
    metadata:
      labels:
        task: monitoring
        k8s-app: grafana
    spec:
      nodeName: node-1 # 部署到那个节点
      containers:
      - name: grafana
        image: grafana/grafana:8.4.5
        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: lib
        #- name: localtime
         #mountPath: /etc/localtime
        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: localtime
        #hostPath:
          #path: /etc/localtime
      - name: ca-certificates
        hostPath:
          path: /etc/ssl/certs
      - name: grafana-storage
        emptyDir: {}
      - name: lib
        hostPath:
         path: /var/lib/grafana/
         type: DirectoryOrCreate
---
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: grafana-svc
  namespace: prometheus
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
    nodePort: 31091
  selector:
    k8s-app: grafana
  type: NodePort

执行资源清单:

kubectl apply -f grafana.yaml

查看资源信息:

kubectl get pods -n prometheus

浏览器访问:http://IP:31091
在这里插入图片描述
OK,浏览器可以访问到Grafana,表示至此步骤,无误!

七、Grafana接入Prometheus数据

1、点击 设置 > Data Sources > Add data source > 选择Prometheus

2、填写NameURL 字段
URL 使用SVC的域名,格式是:SVC名称.名称空间.svc

http://prometheus-svc.prometheus.svc:9090

3、往下滑,点击 Save & test
在这里插入图片描述

八、Grafana添加监控模板

模板可以去这个地址下载,Grafana模板下载地址:,下面我推荐几个对我来说比较满意的。

序号

模板文件

备注

1

1860_rev32.json

服务器监控模板-1

2

node_exporter.json

服务器监控模板-2

3

docker_rev1.json

Docker监控模板

4

Kubernetes-1577674936972.json

K8S集群监控模板

5

Kubernetes-1577691996738.json

K8S集群监控模板

1、我以导入 1860_rev32.json 服务器监控模板为例子演示:
在这里插入图片描述
在这里插入图片描述
在这里插入图片描述
最终效果:
在这里插入图片描述

2、导入node_exporter.json 服务器监控-2模板:



最终效果图:

3、导入docker_rev1.json Docker监控模板:

最终效果:

4、导入Kubernetes-1577674936972.json K8S-1监控模板:

最终效果:

5、导入Kubernetes-1577691996738.jsonK8S-2监控模板:

最终效果:

九、拓展

1Prometheus热加载

curl -XPOST http://16.32.15.200:31090/-/reload

2、新增监控Service服务

问:为什么我添加的Service服务,在Prometheus中查看不到????
答:在Service中添加注解才可以被Prometheus发现,如下图,这是我们定义的ConfigMap内容:


案例:以上面定义的prometheus-svc 为例子,添加prometheus_io_scrape注解。

vim prometheus-svc.yaml
---
apiVersion: v1
kind: Service
metadata:
  name: prometheus-svc
  namespace: prometheus
  labels:
    app: prometheus
  annotations:
    prometheus_io_scrape: "true"  # 注解,有这个才可以被Prometheus发现
spec:
  type: NodePort
  ports:
    - port: 9090
      targetPort: 9090
      nodePort: 31090
      protocol: TCP
  selector:
    app: prometheus
    component: server

更新一下资源清单:

kubectl apply -f prometheus-svc.yaml

热加载一下Prometheus:

curl -XPOST http://16.32.15.200:31090/-/reload


OKPrometheus已经监控上了,如下图:

3prometheus配置注意项:

scrape_interval采集时间的值,要小于evaluation_interval发送告警的值,比如 scrape_interval5分钟采集一次,evaluation_interval1分钟告警一次,这样会产生5条告警,因为 scrape_interval10分钟采集一次,而scrape_interval告警的是旧的值。

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