20、Kubernetes核心技术 - 基于Prometheus和Grafana搭建集群监控平台

发布时间：2024年01月09日

一、概述

二、监控平台架构图?编辑

三、部署 Prometheus

3.1、Prometheus简介

3.2、部署守护进程node-exporter

一、概述

本文将介绍k8s的监控平台搭建，搭建一套完善的k8s监控平台可以帮助我们随时观察生产服务器的运行资源使用情况，例如：CPU、内存、磁盘、网络IO等，除了资源可视化之外，还可以设置监控预警功能，提高生产环境可用性和稳定性，提高排除故障的效率。
接下来，我们基于prometheus + grafana 的方式搭建一套k8s监控平台。

二、监控平台架构图

三、部署 Prometheus

3.1、Prometheus简介

Prometheus官方地址：Overview | Prometheus。

Prometheus是一个开源系统监控和警报工具包，最初由SoundCloud构建。自2012年Prometheus项目启动以来，许多公司和组织都采用了它，该项目拥有非常活跃的开发人员和用户社区。它现在是一个独立的开源项目，独立于任何公司进行维护。为了强调这一点，并澄清项目的治理结构，Prometheus于2016年加入了云原生计算基金会，成为继Kubernetes之后的第二个托管项目。

Prometheus主要有以下一些特点：

- 开源
- 监控、报警、数据库
- 以 HTTP 协议周期性抓取被监控组件状态
- 不需要复杂的集成过程，使用 http 接口接入即可
- 通过服务发现或静态配置发现目标
- 多种图形和仪表板支持模式

Prometheus架构图：

Prometheus组件说明：

prometheus server：主服务，接受外部http请求，收集、存储与查询数据等
prometheus targets: 静态收集的目标服务数据
service discovery：动态发现服务
prometheus alerting：报警通知
pushgateway：数据收集代理服务器(类似于zabbix proxy)
data visualization and export：数据可视化与数据导出(访问客户端)

3.2、部署守护进程node-exporter

创建资源清单文件：vim node-exporter.yaml

## 下面就是yaml文件的具体配置内容   
---
apiVersion: apps/v1
kind: DaemonSet			# DaemonSet表示每个节点都会运行node-exporter
metadata:
  name: node-exporter
  namespace: kube-system		# 命名空间
  labels:
    k8s-app: node-exporter
spec:
  selector:
    matchLabels:
      k8s-app: node-exporter
  template:
    metadata:
      labels:
        k8s-app: node-exporter
    spec:
      containers:
      - image: prom/node-exporter
        name: node-exporter
        ports:
        - containerPort: 9100
          protocol: TCP
          name: http

---

apiVersion: v1
kind: Service
metadata:
  labels:
    k8s-app: node-exporter
  name: node-exporter
  namespace: kube-system
spec:
  ports:
  - name: http
    port: 9100
    nodePort: 31672
    protocol: TCP
  type: NodePort			# 将node-exporter以NodePort方式暴露出来，端口是31672
  selector:
    k8s-app: node-exporter

创建并查看pod、service：

$ kubectl create -f node-exporter.yaml 
daemonset.apps/node-exporter created
service/node-exporter created

$ kubectl get daemonset.apps/node-exporter -n kube-system
NAME            DESIRED   CURRENT   READY   UP-TO-DATE   AVAILABLE   NODE SELECTOR   AGE
node-exporter   2         2         2       2            2           <none>          36s

$ kubectl get service/node-exporter -n kube-system
NAME            TYPE       CLUSTER-IP     EXTERNAL-IP   PORT(S)          AGE
node-exporter   NodePort   10.99.26.203   <none>        9100:31672/TCP   48s

3.3、部署rbac

创建rbac角色控制资源清单文件：vim rbac.yaml

##下面就是yaml文件的具体配置内容
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
  name: prometheus
rules:
- apiGroups: [""]
  resources:
  - nodes
  - nodes/proxy
  - services
  - endpoints
  - pods
  verbs: ["get", "list", "watch"]
- apiGroups:
  - extensions
  resources:
  - ingresses
  verbs: ["get", "list", "watch"]
- nonResourceURLs: ["/metrics"]
  verbs: ["get"]
---
apiVersion: v1
kind: ServiceAccount
metadata:
  name: prometheus
  namespace: kube-system
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:
  name: prometheus
roleRef:
  apiGroup: rbac.authorization.k8s.io
  kind: ClusterRole
  name: prometheus
subjects:
- kind: ServiceAccount
  name: prometheus
  namespace: kube-system

创建集群角色、用户、角色绑定关系：

$ kubectl create -f rbac.yaml 
clusterrole.rbac.authorization.k8s.io/prometheus created
serviceaccount/prometheus created
clusterrolebinding.rbac.authorization.k8s.io/prometheus created

3.4、ConfigMap

创建configmap资源清单： vim configmap.yaml

##下面就是yaml文件的具体配置内容
apiVersion: v1
kind: ConfigMap
metadata:
  name: prometheus-config
  namespace: kube-system
data:
  prometheus.yml: |
    global:
      scrape_interval:     15s
      evaluation_interval: 15s
    scrape_configs:

    - job_name: 'kubernetes-apiservers'
      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-nodes'
      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

    - job_name: 'kubernetes-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-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-services'
      kubernetes_sd_configs:
      - role: service
      metrics_path: /probe
      params:
        module: [http_2xx]
      relabel_configs:
      - source_labels: [__meta_kubernetes_service_annotation_prometheus_io_probe]
        action: keep
        regex: true
      - source_labels: [__address__]
        target_label: __param_target
      - target_label: __address__
        replacement: blackbox-exporter.example.com:9115
      - source_labels: [__param_target]
        target_label: instance
      - action: labelmap
        regex: __meta_kubernetes_service_label_(.+)
      - source_labels: [__meta_kubernetes_namespace]
        target_label: kubernetes_namespace
      - source_labels: [__meta_kubernetes_service_name]
        target_label: kubernetes_name

    - job_name: 'kubernetes-ingresses'
      kubernetes_sd_configs:
      - role: ingress
      relabel_configs:
      - source_labels: [__meta_kubernetes_ingress_annotation_prometheus_io_probe]
        action: keep
        regex: true
      - source_labels: [__meta_kubernetes_ingress_scheme,__address__,__meta_kubernetes_ingress_path]
        regex: (.+);(.+);(.+)
        replacement: ${1}://${2}${3}
        target_label: __param_target
      - target_label: __address__
        replacement: blackbox-exporter.example.com:9115
      - source_labels: [__param_target]
        target_label: instance
      - action: labelmap
        regex: __meta_kubernetes_ingress_label_(.+)
      - source_labels: [__meta_kubernetes_namespace]
        target_label: kubernetes_namespace
      - source_labels: [__meta_kubernetes_ingress_name]
        target_label: kubernetes_name

    - job_name: 'kubernetes-pods'
      kubernetes_sd_configs:
      - role: pod
      relabel_configs:
      - source_labels: [__meta_kubernetes_pod_annotation_prometheus_io_scrape]
        action: keep
        regex: true
      - source_labels: [__meta_kubernetes_pod_annotation_prometheus_io_path]
        action: replace
        target_label: __metrics_path__
        regex: (.+)
      - source_labels: [__address__, __meta_kubernetes_pod_annotation_prometheus_io_port]
        action: replace
        regex: ([^:]+)(?::\d+)?;(\d+)
        replacement: $1:$2
        target_label: __address__
      - action: labelmap
        regex: __meta_kubernetes_pod_label_(.+)
      - source_labels: [__meta_kubernetes_namespace]
        action: replace
        target_label: kubernetes_namespace
      - source_labels: [__meta_kubernetes_pod_name]
        action: replace
        target_label: kubernetes_pod_name

创建config：

$ kubectl create -f configmap.yaml
configmap/prometheus-config created

$ kubectl get cm prometheus-config -n kube-system
NAME                DATA   AGE
prometheus-config   1      33s

3.5、Deployment

创建prometheus的Pod资源清单文件：vim prometheus-deploy.yaml

## 下面就是yaml文件的具体配置内容
---
apiVersion: apps/v1
kind: Deployment
metadata:
  labels:
    name: prometheus-deployment
  name: prometheus
  namespace: kube-system
spec:
  replicas: 1
  selector:
    matchLabels:
      app: prometheus
  template:
    metadata:
      labels:
        app: prometheus
    spec:
      containers:
      - image: prom/prometheus:v2.0.0
        name: prometheus
        command:
        - "/bin/prometheus"
        args:
        - "--config.file=/etc/prometheus/prometheus.yml"
        - "--storage.tsdb.path=/prometheus"
        - "--storage.tsdb.retention=24h"
        ports:
        - containerPort: 9090
          protocol: TCP
        volumeMounts:
        - mountPath: "/prometheus"
          name: data
        - mountPath: "/etc/prometheus"
          name: config-volume
        resources:
          requests:
            cpu: 100m
            memory: 100Mi
          limits:
            cpu: 500m
            memory: 2500Mi
      serviceAccountName: prometheus    
      volumes:
      - name: data
        emptyDir: {}
      - name: config-volume
        configMap:
          name: prometheus-config

创建prometheus pod：

$ kubectl create -f prometheus-deploy.yaml 
deployment.apps/prometheus created

$ kubectl get pod -A | grep prometheu                 
kube-system   prometheus-ddf89874b-d8mbd                 1/1     Running   0               76s

3.6、Service

暴露prometheus，准备资源清单：vim prometheus-service.yaml

## 下面就是yaml文件的具体配置内容
---
kind: Service
apiVersion: v1
metadata:
  labels:
    app: prometheus
  name: prometheus
  namespace: kube-system
spec:
  type: NodePort
  ports:
  - port: 9090
    targetPort: 9090
    nodePort: 30003
  selector:
    app: prometheus

创建service：

$ kubectl create -f prometheus-service.yaml 
service/prometheus created

$ kubectl get svc  -n kube-system | grep prometheus
prometheus      NodePort    10.96.216.242   <none>        9090:30003/TCP           32s

3.7、验证Prometheus?

$ kubectl get pod,svc -n kube-system | grep prometheus
pod/prometheus-ddf89874b-d8mbd                 1/1     Running   0               4m20s
service/prometheus      NodePort    10.96.216.242   <none>        9090:30003/TCP           96s       18s

$ kubectl get DaemonSet -n kube-system | grep node-exporter
node-exporter   2         2         2       2            2           <none>

可以看到，成功启动了prometheus的pod和service，prometheus对外暴露的端口是30003，且安装在192.168.1.33这台机器上。在浏览器通过[ip:port]访问http://192.168.1.33:30003，如下图：

说明我们的Pormetheus已经搭建成功，接下来我们部署Grafana。

四、部署Grafana

Grafana官方文档地址：Documentation | Grafana Labs。

Grafana主要的一些特点：

- 开源的数据分析和可视化工具
- 支持多种数据源

在k8s集群监控平台中，Grafana的作用就是从Prometheus中读取数据，生成报表的形式进行数据可视化的功能。

4.1、Deployment

创建grafana的pod资源清单：vim grafana-deploy.yaml?

## 下面就是yaml文件的具体配置内容
apiVersion: apps/v1
kind: Deployment
metadata:
  name: grafana-core
  namespace: kube-system
  labels:
    app: grafana
    component: core
spec:
  replicas: 1
  selector:
    matchLabels:
      app: grafana
      component: core
  template:
    metadata:
      labels:
        app: grafana
        component: core
    spec:
      containers:
      - image: grafana/grafana:4.2.0
        name: grafana-core
        imagePullPolicy: IfNotPresent
        # env:
        resources:
          # keep request = limit to keep this container in guaranteed class
          limits:
            cpu: 100m
            memory: 100Mi
          requests:
            cpu: 100m
            memory: 100Mi
        env:
          # The following env variables set up basic auth twith the default admin user and admin password.
          - name: GF_AUTH_BASIC_ENABLED
            value: "true"
          - name: GF_AUTH_ANONYMOUS_ENABLED
            value: "false"
          # - name: GF_AUTH_ANONYMOUS_ORG_ROLE
          #   value: Admin
          # does not really work, because of template variables in exported dashboards:
          # - name: GF_DASHBOARDS_JSON_ENABLED
          #   value: "true"
        readinessProbe:
          httpGet:
            path: /login
            port: 3000
          # initialDelaySeconds: 30
          # timeoutSeconds: 1
        volumeMounts:
        - name: grafana-persistent-storage
          mountPath: /var
      volumes:
      - name: grafana-persistent-storage
        emptyDir: {}

?创建grafana的Pod：

$ kubectl create -f grafana-deploy.yaml 
deployment.apps/grafana-core created

$ kubectl get pod -n kube-system | grep grafana
grafana-core-7b7ccc7bcf-8lmhq              1/1     Running   0             2m29s

4.2、Service

创建资源清单文件：vim grafana-service.yaml

## 下面就是yaml文件的具体配置内容
apiVersion: v1
kind: Service
metadata:
  name: grafana
  namespace: kube-system
  labels:
    app: grafana
    component: core
spec:
  type: NodePort
  ports:
    - port: 3000
  selector:
    app: grafana
    component: core

创建grafana Service暴露服务：

$ kubectl create -f grafana-service.yaml 
service/grafana created

4.3、Ingress

创建Ingress资源清单：vim grafana-ingress.yaml

## 下面就是yaml文件的具体配置内容
apiVersion: extensions/v1beta1
kind: Ingress
metadata:
   name: grafana
   namespace: kube-system
spec:
   rules:
   - host: k8s.grafana
     http:
       paths:
       - path: /
         backend:
          serviceName: grafana
          servicePort: 3000

创建ingress:

$ kubectl create -f grafana-ingress.yaml 
Warning: extensions/v1beta1 Ingress is deprecated in v1.14+, unavailable in v1.22+; use networking.k8s.io/v1 Ingress
ingress.extensions/grafana created

?4.4、验证Grafana

$ kubectl get pod,svc -n kube-system | grep grafana
pod/grafana-core-85587c9c49-zqhhh              1/1     Running   0          76s
service/grafana         NodePort    10.105.169.65   <none>        3000:30155/TCP           55s

$ kubectl get ing -n kube-system | grep grafana
grafana   <none>   k8s.grafana             80      3h28m

可以看到，grafana对外暴露的端口是30155，且安装在192.168.1.33这台机器上，所以我们通过浏览器访问：http://192.168.1.33:30155/，默认用户名/密码为：admin/admin：

接下来我们需要添加数据源 Prometheus，注意，绑定Prometheus时，需要使用prometheus这个service的CLUSTER-IP和代理转发到容器的端口进行连接，即10.98.46.224:9090，如下图：

数据源添加完成后，我们导入内置报表模板：

输入Prometheus网络模板ID，这里选择ID为315的模板进行统计：

选择前面定义的数据源名称，本例中我们是mydatasource，并点击导入模板进行数据可视化：

至此，通过Prometheus结合Grafana实现了一个简单的k8s集群监控平台，当然，这里只是一个简单的演示，更多高级功能在需要用到的时候，再查看官网文档。

文章来源:https://blog.csdn.net/Weixiaohuai/article/details/135476555
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