kubernetes/MD/基于kubernetes部署Prometheus和Gr...

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基于kubernetes部署Prometheus和Grafana

著作:行癫 <盗版必究>


一:环境准备

1.kubernetes集群正常

[root@master ~]# kubectl get node
NAME     STATUS   ROLES                  AGE   VERSION
master   Ready    control-plane,master   36d   v1.23.1
node-1   Ready    <none>                 36d   v1.23.1
node-2   Ready    <none>                 36d   v1.23.1
node-3   Ready    <none>                 36d   v1.23.1

2.harbor仓库正常

image-20220602010601512

Prometheus部署

1.node-exporter部署

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

创建监控namespace

[root@master ~]# kubectl create ns monitor-sa

创建node-export.yaml

[root@master ~]# vim node-export.yaml
apiVersion: apps/v1
kind: DaemonSet # 可以保证k8s集群的每个节点都运行完全一样的pod
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
        #image: 10.0.0.230/xingdian/node-exporter:v0.16.0
        ports:
        - containerPort: 9100
        resources:
          requests:
            cpu: 0.15 # 这个容器运行至少需要0.15核cpu
        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:
        - 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: /

注意:

hostNetwork、hostIPC、hostPID都为True时表示这个Pod里的所有容器会直接使用宿主机的网络直接与宿主机进行IPC进程间通信通信可以看到宿主机里正在运行的所有进程。加入了hostNetwork:true会直接将我们的宿主机的9100端口映射出来从而不需要创建service 在我们的宿主机上就会有一个9100的端口

创建:

[root@master ~]# kubectl apply -f node-export.yaml

查看node-exporter是否部署成功

[root@master ~]# kubectl get pods -n monitor-sa -o wide
NAME                READY   STATUS    RESTARTS   AGE     IP      NODE     NOMINATED NODE   READINESS GATES
node-exporter-2cbrg       1/1     Running   0          34m     10.0.0.220     master   <none>           <none>
node-exporter-7rrbh       1/1     Running   0          34m     10.0.0.222     node-2   <none>           <none>
node-exporter-96v29       1/1     Running   0          34m     10.0.0.221     node-1   <none>           <none>
node-exporter-bf2j8       1/1     Running   0          34m     10.0.0.223     node-3   <none>           <none>

注意:

node-export默认的监听端口是9100可以看到当前主机获取到的所有监控数据

[root@master ~]# curl http://10.0.0.220:9100/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"} 8398.49
node_cpu_seconds_total{cpu="0",mode="iowait"} 1.54
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"} 17.2
node_cpu_seconds_total{cpu="0",mode="steal"} 0
node_cpu_seconds_total{cpu="0",mode="system"} 70.61
node_cpu_seconds_total{cpu="0",mode="user"} 187.04
node_cpu_seconds_total{cpu="1",mode="idle"} 8403.82
node_cpu_seconds_total{cpu="1",mode="iowait"} 4.95
node_cpu_seconds_total{cpu="1",mode="irq"} 0
node_cpu_seconds_total{cpu="1",mode="nice"} 0
node_cpu_seconds_total{cpu="1",mode="softirq"} 16.75
node_cpu_seconds_total{cpu="1",mode="steal"} 0
node_cpu_seconds_total{cpu="1",mode="system"} 71.26
node_cpu_seconds_total{cpu="1",mode="user"} 190.27
100 74016  100 74016    0     0  5878k      0 --:--:-- --:--:-- --:--:-- 6023k

[root@master ~]# curl http://10.0.0.220:9100/metrics  | grep node_load
  % 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_loa
1 1m load average.
# TYPE node_load1 gauge
node_load1 0.2
# HELP node_load15 15m load average.
# TYPE node_load15 gauge
node_load15 0.22
# HELP node_load5 5m load average.
# TYPE node_load5 gauge
node_load5 0.2
100 74044  100 74044    0     0  8604k      0 --:--:-- --:--:-- --:--:-- 9038k

2.Prometheus安装

创建sa账号对sa做rbac授权

# 创建一个sa账号monitor
[root@master ~]# kubectl create serviceaccount monitor -n monitor-sa

# 把sa账号monitor通过clusterrolebing绑定到clusterrole上
[root@master ~]# kubectl create clusterrolebinding monitor-clusterrolebinding -n monitor-sa --clusterrole=cluster-admin  --serviceaccount=monitor-sa:monitor

创建prometheus数据存储目录

# 将prometheus调度到node-1节点
[root@node-1 ~]# mkdir /data && chmod 777 /data

创建一个configmap存储卷用来存放prometheus配置信息

[root@master ~]# vim prometheus-cfg.yaml
---
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 

创建:

[root@master ~]#  kubectl apply -f prometheus-cfg.yaml
configmap/prometheus-config created

配置详解:

---
kind: ConfigMap
apiVersion: v1
metadata:
  labels:
    app: prometheus
  name: prometheus-config
  namespace: monitor-sa
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:	# 配置数据源称为target每个target用job_name命名。又分为静态配置和服务发现
    - job_name: 'kubernetes-node'
      kubernetes_sd_configs:	# 使用的是k8s的服务发现
      - role: node	# 使用node角色它使用默认的kubelet提供的http端口来发现集群中每个node节点
      relabel_configs:	# 重新标记
      - source_labels: [__address__]	# 配置的原始标签,匹配地址
        regex: '(.*):10250'		#匹配带有10250端口的url
        replacement: '${1}:9100'	#把匹配到的ip:10250的ip保留
        target_label: __address__	#新生成的url是${1}获取到的ip:9100
        action: replace	# 动作替换
      - action: labelmap
        regex: __meta_kubernetes_node_label_(.+) #匹配到下面正则表达式的标签会被保留,如果不做regex正则的话默认只是会显示instance标签
    - 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
      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__	# 获取到的地址__address__="192.168.40.180:10250"
        replacement: kubernetes.default.svc:443	# 把获取到的地址替换成新的地址kubernetes.default.svc:443
      - source_labels: [__meta_kubernetes_node_name]
        regex: (.+)	# 把原始标签中__meta_kubernetes_node_name值匹配到
        target_label: __metrics_path__	#获取__metrics_path__对应的值
        replacement: /api/v1/nodes/${1}/proxy/metrics/cadvisor	
        # 把metrics替换成新的值api/v1/nodes/k8s-master1/proxy/metrics/cadvisor
        # ${1}是__meta_kubernetes_node_name获取到的值
        # 新的url就是https://kubernetes.default.svc:443/api/v1/nodes/k8s-master1/proxy/metrics/cadvisor
    - job_name: 'kubernetes-apiserver'
      kubernetes_sd_configs:
      - role: endpoints	# 使用k8s中的endpoint服务发现采集apiserver 6443端口获取到的数据
      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]
        # endpoint这个对象的名称空间,endpoint对象的服务名,exnpoint的端口名称
        action: keep	# 采集满足条件的实例,其他实例不采集
        regex: default;kubernetes;https	#正则匹配到的默认空间下的service名字是kubernetes协议是https的endpoint类型保留下来
    - 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
        # 重新打标仅抓取到的具有 "prometheus.io/scrape: true" 的annotation的端点意思是说如果某个service具有prometheus.io/scrape = true annotation声明则抓取annotation本身也是键值结构所以这里的源标签设置为键而regex设置值true当值匹配到regex设定的内容时则执行keep动作也就是保留其余则丢弃。
      - source_labels: [__meta_kubernetes_service_annotation_prometheus_io_scheme]
        action: replace
        target_label: __scheme__
        regex: (https?)
        # 重新设置scheme匹配源标签__meta_kubernetes_service_annotation_prometheus_io_scheme也就是prometheus.io/scheme annotation如果源标签的值匹配到regex则把值替换为__scheme__对应的值。
      - source_labels: [__meta_kubernetes_service_annotation_prometheus_io_path]
        action: replace
        target_label: __metrics_path__
        regex: (.+)
        # 应用中自定义暴露的指标也许你暴露的API接口不是/metrics这个路径那么你可以在这个POD对应的service中做一个"prometheus.io/path = /mymetrics" 声明上面的意思就是把你声明的这个路径赋值给__metrics_path__其实就是让prometheus来获取自定义应用暴露的metrices的具体路径不过这里写的要和service中做好约定如果service中这样写 prometheus.io/app-metrics-path: '/metrics' 那么你这里就要__meta_kubernetes_service_annotation_prometheus_io_app_metrics_path这样写。
      - source_labels: [__address__, __meta_kubernetes_service_annotation_prometheus_io_port]
        action: replace
        target_label: __address__
        regex: ([^:]+)(?::\d+)?;(\d+)
        replacement: $1:$2
        # 暴露自定义的应用的端口就是把地址和你在service中定义的 "prometheus.io/port = <port>" 声明做一个拼接然后赋值给__address__这样prometheus就能获取自定义应用的端口然后通过这个端口再结合__metrics_path__来获取指标如果__metrics_path__值不是默认的/metrics那么就要使用上面的标签替换来获取真正暴露的具体路径。
      - action: labelmap	#保留下面匹配到的标签
        regex: __meta_kubernetes_service_label_(.+)
      - source_labels: [__meta_kubernetes_namespace]
        action: replace	 # 替换__meta_kubernetes_namespace变成kubernetes_namespace
        target_label: kubernetes_namespace
      - source_labels: [__meta_kubernetes_service_name]
        action: replace
        target_label: kubernetes_name 

通过deployment部署prometheus

[root@master ~]# cat prometheus-deploy.yaml 
---
apiVersion: apps/v1
kind: Deployment
metadata:
  name: prometheus-server
  namespace: monitor-sa
  labels:
    app: prometheus
spec:
  replicas: 1
  selector:
    matchLabels:
      app: prometheus
      component: server
    #matchExpressions:
    #- {key: app, operator: In, values: [prometheus]}
    #- {key: component, operator: In, values: [server]}
  template:
    metadata:
      labels:
        app: prometheus
        component: server
      annotations:
        prometheus.io/scrape: 'false'
    spec:
      nodeName: node-1	# 指定pod调度到哪个节点上	
      serviceAccountName: monitor
      containers:
      - name: prometheus
        image: prom/prometheus:v2.2.1
        #image: 10.0.0.230/xingdian/prometheus:v2.2.1
        imagePullPolicy: IfNotPresent
        command:
          - prometheus
          - --config.file=/etc/prometheus/prometheus.yml
          - --storage.tsdb.path=/prometheus	# 数据存储目录
          - --storage.tsdb.retention=720h	# 数据保存时长
          - --web.enable-lifecycle	# 开启热加载
        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

创建:

[root@master ~]# kubectl apply -f prometheus-deploy.yaml
deployment.apps/prometheus-server created

查看:

[root@master ~]# kubectl get pods -o wide -n monitor-sa
NAME      READY   STATUS    RESTARTS   AGE   IP     NODE     NOMINATED NODE   READINESS GATES
prometheus-server-59cb5d648-bxwrb   1/1     Running   0    14m   10.244.2.100   node-1   <none>           <none>

3.prometheus pod创建service

[root@master ~]# cat prometheus-svc.yaml 
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

创建:

[root@master ~]# kubectl apply -f prometheus-svc.yaml
service/prometheus created

查看service在物理机映射的端口

[root@master ~]# kubectl get svc -n monitor-sa
NAME         TYPE       CLUSTER-IP     EXTERNAL-IP   PORT(S)          AGE
prometheus   NodePort   10.106.61.80   <none>        9090:32169/TCP   32m

4.web界面查看

image-20220602011956600

image-20220602012012382

5.Prometheus热加载

# 为了每次修改配置文件可以热加载prometheus也就是不停止prometheus就可以使配置生效想要使配置生效可用如下热加载命令
[root@master ~]# kubectl get pods -n monitor-sa -o wide -l app=prometheus
NAME           READY   STATUS    RESTARTS   AGE     IP             NODE        NOMINATED NODE   READINESS GATES
prometheus-server-689fb8cdbc-kcsw2   1/1     Running   0   5m39s   10.244.36.70   k8s-node1   <none>  <none>

# 想要使配置生效可用如下命令热加载:
[root@master ~]# curl -X POST http://10.244.36.70:9090/-/reload

# 查看log
[root@master ~]# kubectl logs -n monitor-sa prometheus-server-689fb8cdbc-kcsw2

注意:

# 热加载速度比较慢可以暴力重启prometheus如修改上面的prometheus-cfg.yaml文件之后可执行如下强制删除
[root@master ~]# kubectl delete -f prometheus-cfg.yaml
[root@master ~]# kubectl delete -f prometheus-deploy.yaml
# 然后再通过apply更新
[root@master ~]# kubectl apply -f prometheus-cfg.yaml
[root@master ~]# 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

Grafana的部署

1.Grafana介绍

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GraphiteInfluxDBOpenTSDBPrometheusElasticsearchCloudWatch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

2.Grafana安装

[root@master prome]# cat grafana.yaml
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: 10.0.0.230/xingdian/heapster-grafana-amd64:v5.0.4
        #heleicool/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"
          # 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: {}
---
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

创建:

[root@master prome]# kubectl apply -f grafana.yaml
deployment.apps/monitoring-grafana created
service/monitoring-grafana created

查看:

[root@master prome]# kubectl get pods -n kube-system -l task=monitoring -o wide
NAME         READY   STATUS    RESTARTS   AGE   IP            NODE     NOMINATED NODE   READINESS GATES
monitoring-grafana-7c5c6c7486-rbt62   1/1     Running   0   9s    10.244.1.83   node-3   <none>    <none>
[root@master prome]# kubectl get svc -n kube-system | grep grafana
monitoring-grafana   NodePort    10.101.77.194   <none>        80:30919/TCP             76s

配置Grafana

浏览器访问:

image-20220602013222284

添加数据源:

image-20220602013322234

指定Prometheus地址

image-20220602013441712

导入监控模板:

image-20220602013943317

image-20220602014027197

注意:

官方下载监控模板:https://grafana.com/dashboards?dataSource=prometheus&search=kubernetes

image-20220602014152927

image-20220602014212551

展示:

image-20220602014306247

image-20220602014321106

image-20220602014337431