684 lines
26 KiB
Markdown
684 lines
26 KiB
Markdown
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<h1><center>基于kubernetes部署Prometheus和Grafana</center></h1>
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------
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## 一:环境准备
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#### 1.kubernetes集群正常
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```shell
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[root@master ~]# kubectl get node
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NAME STATUS ROLES AGE VERSION
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master Ready control-plane,master 36d v1.23.1
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node-1 Ready <none> 36d v1.23.1
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node-2 Ready <none> 36d v1.23.1
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node-3 Ready <none> 36d v1.23.1
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```
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#### 2.harbor仓库正常
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![image-20220602010601512](%E5%9F%BA%E4%BA%8Ekubernetes%E9%83%A8%E7%BD%B2Prometheus%E5%92%8CGrafana.assets/image-20220602010601512.png)
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## 二:Prometheus部署
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#### 1.node-exporter部署
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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
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创建监控namespace:
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```shell
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[root@master ~]# kubectl create ns monitor-sa
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```
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创建node-export.yaml:
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```shell
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[root@master ~]# vim node-export.yaml
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apiVersion: apps/v1
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kind: DaemonSet # 可以保证k8s集群的每个节点都运行完全一样的pod
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metadata:
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name: node-exporter
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namespace: monitor-sa
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labels:
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name: node-exporter
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spec:
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selector:
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matchLabels:
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name: node-exporter
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template:
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metadata:
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labels:
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name: node-exporter
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spec:
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hostPID: true
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hostIPC: true
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hostNetwork: true
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containers:
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- name: node-exporter
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image: prom/node-exporter:v0.16.0
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#image: 10.0.0.230/xingdian/node-exporter:v0.16.0
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ports:
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- containerPort: 9100
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resources:
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requests:
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cpu: 0.15 # 这个容器运行至少需要0.15核cpu
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securityContext:
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privileged: true # 开启特权模式
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args:
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- --path.procfs
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- /host/proc
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- --path.sysfs
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- /host/sys
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- --collector.filesystem.ignored-mount-points
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- '"^/(sys|proc|dev|host|etc)($|/)"'
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volumeMounts:
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- name: dev
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mountPath: /host/dev
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- name: proc
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mountPath: /host/proc
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- name: sys
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mountPath: /host/sys
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- name: rootfs
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mountPath: /rootfs
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tolerations:
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- key: "node-role.kubernetes.io/master"
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operator: "Exists"
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effect: "NoSchedule"
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volumes:
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- name: proc
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hostPath:
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path: /proc
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- name: dev
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hostPath:
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path: /dev
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- name: sys
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hostPath:
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path: /sys
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- name: rootfs
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hostPath:
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path: /
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```
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注意:
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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
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创建:
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```shell
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[root@master ~]# kubectl apply -f node-export.yaml
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```
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查看node-exporter是否部署成功:
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```shell
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[root@master ~]# kubectl get pods -n monitor-sa -o wide
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NAME READY STATUS RESTARTS AGE IP NODE NOMINATED NODE READINESS GATES
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node-exporter-2cbrg 1/1 Running 0 34m 10.0.0.220 master <none> <none>
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node-exporter-7rrbh 1/1 Running 0 34m 10.0.0.222 node-2 <none> <none>
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node-exporter-96v29 1/1 Running 0 34m 10.0.0.221 node-1 <none> <none>
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node-exporter-bf2j8 1/1 Running 0 34m 10.0.0.223 node-3 <none> <none>
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```
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注意:
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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
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```shell
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[root@master ~]# curl http://10.0.0.220:9100/metrics | grep node_cpu_seconds
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% Total % Received % Xferd Average Speed Time Time Time Current
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Dload Upload Total Spent Left Speed
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0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0# HELP node_cpu_seconds_total Seconds the cpus spent in each mode.
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# TYPE node_cpu_seconds_total counter
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node_cpu_seconds_total{cpu="0",mode="idle"} 8398.49
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node_cpu_seconds_total{cpu="0",mode="iowait"} 1.54
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node_cpu_seconds_total{cpu="0",mode="irq"} 0
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node_cpu_seconds_total{cpu="0",mode="nice"} 0
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node_cpu_seconds_total{cpu="0",mode="softirq"} 17.2
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node_cpu_seconds_total{cpu="0",mode="steal"} 0
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node_cpu_seconds_total{cpu="0",mode="system"} 70.61
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node_cpu_seconds_total{cpu="0",mode="user"} 187.04
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node_cpu_seconds_total{cpu="1",mode="idle"} 8403.82
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node_cpu_seconds_total{cpu="1",mode="iowait"} 4.95
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node_cpu_seconds_total{cpu="1",mode="irq"} 0
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node_cpu_seconds_total{cpu="1",mode="nice"} 0
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node_cpu_seconds_total{cpu="1",mode="softirq"} 16.75
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node_cpu_seconds_total{cpu="1",mode="steal"} 0
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node_cpu_seconds_total{cpu="1",mode="system"} 71.26
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node_cpu_seconds_total{cpu="1",mode="user"} 190.27
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100 74016 100 74016 0 0 5878k 0 --:--:-- --:--:-- --:--:-- 6023k
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[root@master ~]# curl http://10.0.0.220:9100/metrics | grep node_load
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% Total % Received % Xferd Average Speed Time Time Time Current
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Dload Upload Total Spent Left Speed
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0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0# HELP node_loa
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1 1m load average.
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# TYPE node_load1 gauge
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node_load1 0.2
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# HELP node_load15 15m load average.
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# TYPE node_load15 gauge
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node_load15 0.22
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# HELP node_load5 5m load average.
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# TYPE node_load5 gauge
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node_load5 0.2
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100 74044 100 74044 0 0 8604k 0 --:--:-- --:--:-- --:--:-- 9038k
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```
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#### 2.Prometheus安装
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创建sa账号,对sa做rbac授权:
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```shell
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# 创建一个sa账号monitor
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[root@master ~]# kubectl create serviceaccount monitor -n monitor-sa
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# 把sa账号monitor通过clusterrolebing绑定到clusterrole上
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[root@master ~]# kubectl create clusterrolebinding monitor-clusterrolebinding -n monitor-sa --clusterrole=cluster-admin --serviceaccount=monitor-sa:monitor
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```
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创建prometheus数据存储目录:
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```shell
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# 将prometheus调度到node-1节点
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[root@node-1 ~]# mkdir /data && chmod 777 /data
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```
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创建一个configmap存储卷,用来存放prometheus配置信息:
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```shell
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[root@master ~]# vim prometheus-cfg.yaml
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---
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kind: ConfigMap
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apiVersion: v1
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metadata:
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labels:
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app: prometheus
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name: prometheus-config
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namespace: monitor-sa
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data:
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prometheus.yml: |
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global:
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scrape_interval: 15s
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scrape_timeout: 10s
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evaluation_interval: 1m
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scrape_configs:
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- job_name: 'kubernetes-node'
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kubernetes_sd_configs:
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- role: node
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relabel_configs:
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- source_labels: [__address__]
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regex: '(.*):10250'
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replacement: '${1}:9100'
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target_label: __address__
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action: replace
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- action: labelmap
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regex: __meta_kubernetes_node_label_(.+)
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- job_name: 'kubernetes-node-cadvisor'
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kubernetes_sd_configs:
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- role: node
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scheme: https
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tls_config:
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ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crt
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bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token
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relabel_configs:
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- action: labelmap
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regex: __meta_kubernetes_node_label_(.+)
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- target_label: __address__
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replacement: kubernetes.default.svc:443
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- source_labels: [__meta_kubernetes_node_name]
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regex: (.+)
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target_label: __metrics_path__
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replacement: /api/v1/nodes/${1}/proxy/metrics/cadvisor
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- job_name: 'kubernetes-apiserver'
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kubernetes_sd_configs:
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- role: endpoints
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scheme: https
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tls_config:
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ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crt
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bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token
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relabel_configs:
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- source_labels: [__meta_kubernetes_namespace, __meta_kubernetes_service_name, __meta_kubernetes_endpoint_port_name]
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action: keep
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regex: default;kubernetes;https
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- job_name: 'kubernetes-service-endpoints'
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kubernetes_sd_configs:
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- role: endpoints
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relabel_configs:
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- source_labels: [__meta_kubernetes_service_annotation_prometheus_io_scrape]
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action: keep
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regex: true
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- source_labels: [__meta_kubernetes_service_annotation_prometheus_io_scheme]
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action: replace
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target_label: __scheme__
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regex: (https?)
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- source_labels: [__meta_kubernetes_service_annotation_prometheus_io_path]
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action: replace
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target_label: __metrics_path__
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regex: (.+)
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- source_labels: [__address__, __meta_kubernetes_service_annotation_prometheus_io_port]
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action: replace
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target_label: __address__
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regex: ([^:]+)(?::\d+)?;(\d+)
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replacement: $1:$2
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- action: labelmap
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regex: __meta_kubernetes_service_label_(.+)
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- source_labels: [__meta_kubernetes_namespace]
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action: replace
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target_label: kubernetes_namespace
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- source_labels: [__meta_kubernetes_service_name]
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action: replace
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target_label: kubernetes_name
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```
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创建:
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```shell
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[root@master ~]# kubectl apply -f prometheus-cfg.yaml
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configmap/prometheus-config created
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```
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配置详解:
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```shell
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---
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kind: ConfigMap
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apiVersion: v1
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metadata:
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labels:
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app: prometheus
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name: prometheus-config
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namespace: monitor-sa
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data:
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prometheus.yml: |
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global:
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scrape_interval: 15s #采集目标主机监控据的时间间隔
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scrape_timeout: 10s # 数据采集超时时间,默认10s
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evaluation_interval: 1m #触发告警检测的时间,默认是1m
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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
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- job_name: 'kubernetes-node'
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kubernetes_sd_configs: # 使用的是k8s的服务发现
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- 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
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relabel_configs: # 重新标记
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- source_labels: [__address__] # 配置的原始标签,匹配地址
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regex: '(.*):10250' #匹配带有10250端口的url
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replacement: '${1}:9100' #把匹配到的ip:10250的ip保留
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target_label: __address__ #新生成的url是${1}获取到的ip:9100
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action: replace # 动作替换
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- action: labelmap
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regex: __meta_kubernetes_node_label_(.+) #匹配到下面正则表达式的标签会被保留,如果不做regex正则的话,默认只是会显示instance标签
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- job_name: 'kubernetes-node-cadvisor' # 抓取cAdvisor数据,是获取kubelet上/metrics/cadvisor接口数据来获取容器的资源使用情况
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kubernetes_sd_configs:
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- role: node
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scheme: https
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tls_config:
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ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crt
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bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token
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relabel_configs:
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- action: labelmap # 把匹配到的标签保留
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regex: __meta_kubernetes_node_label_(.+) #保留匹配到的具有__meta_kubernetes_node_label的标签
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- target_label: __address__ # 获取到的地址:__address__="192.168.40.180:10250"
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replacement: kubernetes.default.svc:443 # 把获取到的地址替换成新的地址kubernetes.default.svc:443
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- source_labels: [__meta_kubernetes_node_name]
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regex: (.+) # 把原始标签中__meta_kubernetes_node_name值匹配到
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target_label: __metrics_path__ #获取__metrics_path__对应的值
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replacement: /api/v1/nodes/${1}/proxy/metrics/cadvisor
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# 把metrics替换成新的值api/v1/nodes/k8s-master1/proxy/metrics/cadvisor
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# ${1}是__meta_kubernetes_node_name获取到的值
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# 新的url就是https://kubernetes.default.svc:443/api/v1/nodes/k8s-master1/proxy/metrics/cadvisor
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- job_name: 'kubernetes-apiserver'
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kubernetes_sd_configs:
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- role: endpoints # 使用k8s中的endpoint服务发现,采集apiserver 6443端口获取到的数据
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scheme: https
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tls_config:
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ca_file: /var/run/secrets/kubernetes.io/serviceaccount/ca.crt
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bearer_token_file: /var/run/secrets/kubernetes.io/serviceaccount/token
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relabel_configs:
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- source_labels: [__meta_kubernetes_namespace, __meta_kubernetes_service_name, __meta_kubernetes_endpoint_port_name]
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# endpoint这个对象的名称空间,endpoint对象的服务名,exnpoint的端口名称
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action: keep # 采集满足条件的实例,其他实例不采集
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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
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- job_name: 'kubernetes-service-endpoints'
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kubernetes_sd_configs:
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- role: endpoints
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relabel_configs:
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- source_labels: [__meta_kubernetes_service_annotation_prometheus_io_scrape]
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action: keep
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regex: true
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# 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:
|
|||
|
|
|||
|
```shell
|
|||
|
[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:
|
|||
|
|
|||
|
```shell
|
|||
|
[root@master ~]# kubectl apply -f prometheus-deploy.yaml
|
|||
|
deployment.apps/prometheus-server created
|
|||
|
```
|
|||
|
|
|||
|
查看:
|
|||
|
|
|||
|
```shell
|
|||
|
[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
|
|||
|
|
|||
|
```shell
|
|||
|
[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:
|
|||
|
|
|||
|
```shell
|
|||
|
[root@master ~]# kubectl apply -f prometheus-svc.yaml
|
|||
|
service/prometheus created
|
|||
|
```
|
|||
|
|
|||
|
查看service在物理机映射的端口:
|
|||
|
|
|||
|
```shell
|
|||
|
[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](%E5%9F%BA%E4%BA%8Ekubernetes%E9%83%A8%E7%BD%B2Prometheus%E5%92%8CGrafana.assets/image-20220602011956600.png)
|
|||
|
|
|||
|
![image-20220602012012382](%E5%9F%BA%E4%BA%8Ekubernetes%E9%83%A8%E7%BD%B2Prometheus%E5%92%8CGrafana.assets/image-20220602012012382.png)
|
|||
|
|
|||
|
#### 5.Prometheus热加载
|
|||
|
|
|||
|
```shell
|
|||
|
# 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:
|
|||
|
|
|||
|
```shell
|
|||
|
# 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
|
|||
|
```
|
|||
|
|
|||
|
## 三: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: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
|
|||
|
|
|||
|
#### 2.Grafana安装
|
|||
|
|
|||
|
```shell
|
|||
|
[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:
|
|||
|
|
|||
|
```shell
|
|||
|
[root@master prome]# kubectl apply -f grafana.yaml
|
|||
|
deployment.apps/monitoring-grafana created
|
|||
|
service/monitoring-grafana created
|
|||
|
```
|
|||
|
|
|||
|
查看:
|
|||
|
|
|||
|
```shell
|
|||
|
[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>
|
|||
|
```
|
|||
|
|
|||
|
```shell
|
|||
|
[root@master prome]# kubectl get svc -n kube-system | grep grafana
|
|||
|
monitoring-grafana NodePort 10.101.77.194 <none> 80:30919/TCP 76s
|
|||
|
```
|
|||
|
|
|||
|
## 四:配置Grafana
|
|||
|
|
|||
|
浏览器访问:
|
|||
|
|
|||
|
![image-20220602013222284](%E5%9F%BA%E4%BA%8Ekubernetes%E9%83%A8%E7%BD%B2Prometheus%E5%92%8CGrafana.assets/image-20220602013222284.png)
|
|||
|
|
|||
|
添加数据源:
|
|||
|
|
|||
|
![image-20220602013322234](%E5%9F%BA%E4%BA%8Ekubernetes%E9%83%A8%E7%BD%B2Prometheus%E5%92%8CGrafana.assets/image-20220602013322234.png)
|
|||
|
|
|||
|
指定Prometheus地址:
|
|||
|
|
|||
|
![image-20220602013441712](%E5%9F%BA%E4%BA%8Ekubernetes%E9%83%A8%E7%BD%B2Prometheus%E5%92%8CGrafana.assets/image-20220602013441712.png)
|
|||
|
|
|||
|
导入监控模板:
|
|||
|
|
|||
|
![image-20220602013943317](%E5%9F%BA%E4%BA%8Ekubernetes%E9%83%A8%E7%BD%B2Prometheus%E5%92%8CGrafana.assets/image-20220602013943317.png)
|
|||
|
|
|||
|
![image-20220602014027197](%E5%9F%BA%E4%BA%8Ekubernetes%E9%83%A8%E7%BD%B2Prometheus%E5%92%8CGrafana.assets/image-20220602014027197.png)
|
|||
|
|
|||
|
注意:
|
|||
|
|
|||
|
官方下载监控模板:https://grafana.com/dashboards?dataSource=prometheus&search=kubernetes
|
|||
|
|
|||
|
![image-20220602014152927](%E5%9F%BA%E4%BA%8Ekubernetes%E9%83%A8%E7%BD%B2Prometheus%E5%92%8CGrafana.assets/image-20220602014152927.png)
|
|||
|
|
|||
|
![image-20220602014212551](%E5%9F%BA%E4%BA%8Ekubernetes%E9%83%A8%E7%BD%B2Prometheus%E5%92%8CGrafana.assets/image-20220602014212551.png)
|
|||
|
|
|||
|
展示:
|
|||
|
|
|||
|
![image-20220602014306247](%E5%9F%BA%E4%BA%8Ekubernetes%E9%83%A8%E7%BD%B2Prometheus%E5%92%8CGrafana.assets/image-20220602014306247.png)
|
|||
|
|
|||
|
![image-20220602014321106](%E5%9F%BA%E4%BA%8Ekubernetes%E9%83%A8%E7%BD%B2Prometheus%E5%92%8CGrafana.assets/image-20220602014321106.png)
|
|||
|
|
|||
|
![image-20220602014337431](%E5%9F%BA%E4%BA%8Ekubernetes%E9%83%A8%E7%BD%B2Prometheus%E5%92%8CGrafana.assets/image-20220602014337431.png)
|