docker-compose简单部署prometheus+grafana及相关应用监控实现

目录

前言

一、Prometheus + Grafana部署

二、监控数据源配置

二、监控服务配置

三、监控报警配置

总结

---

前言

Prometheus：抓取metrics(指标)数据，然后进行存储

Grafana：提供各种模板或自定义界面展示数据

---

一、Prometheus + Grafana部署

1. 创建docker-compose.yml

    version: '2'
           networks:
             monitor:
               driver: bridge
           #配置应用
           services:
             #监控服务
             prometheus:
               image: prom/prometheus
               container_name: prometheus
               hostname: prometheus
               restart: always
               volumes:
                 - /mydata/pan/prometheus/prometheus.yml:/etc/prometheus/prometheus.yml
                 - /mydata/pan/node_down/node_down.yml:/etc/prometheus/node_down.yml
               ports:
                 - "9090:9090"
               networks:
                 - monitor
             #报警插件
             alertmanager:
               image: prom/alertmanager
               container_name: alertmanager
               hostname: alertmanager
               restart: always
               volumes:
                 - /mydata/pan/alertmanager/alertmanager.yml:/etc/alertmanager/alertmanager.yml
               ports:
                 - "9093:9093"
               networks:
                 - monitor
             #界面展示
             grafana:
               image: grafana/grafana
               container_name: grafana
               hostname: grafana
               restart: always
               ports:
                 - "3000:3000"
               networks:
                 - monitor
             #获取服务器信息
             node-exporter:
               image: quay.io/prometheus/node-exporter
               container_name: node-exporter
               hostname: node-exporter
               restart: always
               ports:
                 - "9100:9100"
               networks:
                 - monitor
             #监控docker容器服务
             cadvisor:
               image: google/cadvisor:latest
               container_name: cadvisor
               hostname: cadvisor
               restart: always
               volumes:
                 - /:/rootfs:ro
                 - /var/run:/var/run:rw
                 - /sys:/sys:ro
                 - /var/lib/docker/:/var/lib/docker:ro
               ports:
                 - "8080:8080"
               networks:
                 - monitor

2. 创建alertmanager.yml，配置收发邮件邮箱

   global:
     smtp_smarthost: 'smtp.qq.com:465'    #qq服务器
     smtp_from: '[email protected]'      #发邮件的邮箱
     smtp_auth_username: '[email protected]'   #发邮件的邮箱用户名，也就是你的邮箱
     smtp_auth_password: 'xxxxx'     #发邮件的邮箱密码
     smtp_require_tls: false      #不进行tls验证
   
   route:
     group_by: ['alertname']
     group_wait: 10s
     group_interval: 10s
     repeat_interval: 10m
     receiver: live-monitoring
   
   receivers:
     - name: 'live-monitoring'
       email_configs:
         - to: '[email protected]'     #收邮件的邮箱     

3. 创建prometheus.yml

   global:
     scrape_interval:     15s # 设置间隔15s，默认1分钟.
     evaluation_interval: 15s # 每15秒评估一次规则， 默认1分钟.
   
   #设置报警插件
   alerting:
     alertmanagers:
       - static_configs:
           - targets: ['192.168.2.170:9093']
             # - alertmanager:9093
   
   # 加载规则一次，并根据全局规则定期对其进行评估'evaluation_interval'.
   rule_files:
     - "node_down.yml"
     # - "first_rules.yml"
     # - "second_rules.yml"
   
   # 监控配置:
   scrape_configs:
     - job_name: 'prometheus'
       static_configs:
       - targets: ['192.168.2.170:9090']
   
     - job_name: 'cadvisor'
       static_configs:
       - targets: ['192.168.2.170:8080']
   
     - job_name: 'node'
       scrape_interval: 8s
       static_configs:
       - targets: ['192.168.2.170:9100']

4. 添加报警规则 node_down.yml （node_down.yml为 prometheus targets 监控）

   groups:
     - name: node_down
       rules:
         - alert: InstanceDown
           expr: up == 0
           for: 1m
           labels:
             user: test
           annotations:
             summary: "Instance {{ $labels.instance }} down"
             description: "{{ $labels.instance }} of job {{ $labels.job }} has been down for more than 1 minutes."

5. 运行docker-compose

   #拉取镜像，创建容器运行
   docker-compose up -d
   #删除容器，停止运行
   docker-compose down

6. 查看运行结果及网址访问
   

   Promethus地址：http://192.168.2.170:9090/targets

   grafana地址：http://192.168.2.170:3000

   （第一次访问：账户密码均为 admin ，登陆后第一次可进行设置密码）

        

二、监控数据源配置

        打开grafana，创建数据源 promethus （按需可配置其他数据源，如mysql，Elasticsearch等）

        选择Prometheus 2.0 Stats

        填入promethus地址

        保存

二、监控服务配置

        grafana模板查看及下载地址：Grafana: The open observability platform | Grafana Labs

1. 服务器监控（模板代号：8919）
   
   需监控的服务器上需安装node-exporter

   version: '2'
   networks:
     monitor:
       driver: bridge
   services:
       node-exporter:
         image: quay.io/prometheus/node-exporter
         container_name: node-exporter
         hostname: node-exporter
         restart: always
         ports:
           - "9100:9100"
         networks:
           - monitor

   配置prometheus.yml文件，在targets中加入不同服务所在的ip:端口（端口为node-exporter的端口

   scrape_configs:
     - job_name: 'node'
       scrape_interval: 8s
       static_configs:
         - targets: ['192.168.2.170:9100','192.168.2.169:9100','192.168.1.69:9100']

   重启prometheus服务，访问http://192.168.2.170:9090/targets 查看是否正确运行
   
   效果如下
   
   
   
    
2. docker监控（模板代号：193）
   
   需要在服务器上安装cadvisor服务
    

   version: '2'
   networks:
     monitor:
       driver: bridge
   services:
       cadvisor:
         image: google/cadvisor:latest
         container_name: cadvisor
         hostname: cadvisor
         restart: always
         volumes:
           - /:/rootfs:ro
           - /var/run:/var/run:rw
           - /sys:/sys:ro
           - /var/lib/docker/:/var/lib/docker:ro
         ports:
           - "8080:8080"
         networks:
           - monitor

   配置prometheus.yml文件，在targets中加入不同docker服务所在的ip:端口（端口为cadvisor的端口）

   scrape_configs:
     - job_name: 'cadvisor'
       static_configs:
         - targets: ['192.168.2.170:8080','192.168.2.169:8080','192.168.1.69:8080']

   重启prometheus服务，访问http://192.168.2.170:9090/targets 查看是否正确运行
   
   
   打开grafana，选择docker监控模板，进行设置，添加筛选条件
   
   
   效果如下
   
   
   
    
3. 监控springboot 项目（模板代号：4701）
   
   
   spirng项目pom中引入 相关依赖

   
       org.springframework.boot
       spring-boot-starter-actuator
   
   
   
   
       io.micrometer
       micrometer-registry-prometheus
   

   项目application文件中加入以下配置

   spring:
     application:
       name: test
   server:
     port: 11111    
   management:
     endpoints:
       web:
         exposure:
           # 将 Actuator 的 /actuator/prometheus 端点暴露出来
           include: 'prometheus'
     metrics:
       tags:
         application: ${spring.application.name}

   注意：项目中若有家权限框架，请将路径/actuator/prometheus 加入白名单
   
   启动项目，控制台输出有以下内容即表示成功
    

   o.s.b.a.e.web.EndpointLinksResolver      : Exposing 1 endpoint(s) beneath base path '/actuator'

   配置prometheus.yml文件

   scrape_configs:
     - job_name: '自定义名称'
         scrape_interval: 5s
         metrics_path: '/xxxx/actuator/prometheus'  #若项目中有配置server.servlet.context-path，则加上对应xxxx路径
         static_configs:
           - targets: ['192.168.1.69:18077','192.168.1.69:18078']

   重启prometheus服务，访问http://192.168.2.170:9090/targets 查看是否正确运行
   
   
   查看效果
   
   
   
    

4. 监控mysql（模板代号：7362）

         在需监控mysql的服务器安装 mysqld-exporter，编辑docker-compose文件

services:
    mysqld-exporter:
      image: prom/mysqld-exporter
      container_name: mysqld-exporter
      hostname: mysqld-exporter
      restart: always
      ports:
        - "9104:9104"
      environment:
        - DATA_SOURCE_NAME=root:root@(192.168.2.169:3306)/  #username:password@(ip:端口)
      networks:
        - monitor

         配置prometheus.yml文件

scrape_configs:
  - job_name: 'mysql-exporter'
    scrape_interval: 5s
    static_configs:
      - targets: ['192.168.2.170:9104']   

         重启prometheus服务，访问http://192.168.2.170:9090/targets 查看是否正确运行

         效果如下

 

三、监控报警配置

后续补充....

---

总结

监控流程总体上是，prometheus的配置文件中配置如何获取信息，进行保存，然后grafana配置对应prometheus的数据源，选择合适的模板，进行数据展示。

以上文章仅作为个人学习累积，以便回顾