docker部署钉钉机器人报警通知的实现

本文主要介绍了docker部署钉钉机器人报警通知的实现，文中通过示例代码介绍的非常详细，对大家的学习或者工作具有一定的参考学习价值，需要的朋友们下面随着小编来一起学习学习吧

目录结构

[root@node1 ~]# tree prom
prom
├── docker-compose.yml  #docker-compose文件
├── grafana  #grafana数据挂载
├── prometheus_data  #Prometheus数据挂载
├── rules    #报警规则文件
│   ├── cpu_over.yml
│   ├── disk_over.yml
│   ├── memory_over.yml
│   └── node_alived.yml
└── yml
    ├── alertmanager.yml   alertmanager配置
    ├── config.yml   钉钉机器人配置
    └── prometheus.yml   Prometheus配置

[root@node1 prom]# cat docker-compose.yml
version: "3.7"
services:
  node-exporter:
    image: prom/node-exporter:latest
    container_name: "node-exporter"
    ports:
      - "9100:9100"
    restart: always
  cadvisor:
    image: google/cadvisor:latest
    container_name: cadvisor
    restart: always
    ports:
      - '8080:8080'
  prometheus:
    image: prom/prometheus:latest
    container_name: prometheus
    ports:
      - "9090:9090"
    restart: always
    volumes:
      - "./yml/prometheus.yml:/etc/prometheus/prometheus.yml"
      - "./prometheus_data:/prometheus"
      - "./rules:/etc/prometheus/rules"
  grafana:
    image: grafana/grafana
    container_name: "grafana"
    ports:
      - "3000:3000"
    restart: always
    volumes:
      - "./grafana:/var/lib/grafana"
  alertmanager:
    image: prom/alertmanager:latest
    restart: "always"
    ports:
      - 9093:9093
    container_name: "alertmanager"
    volumes:
      - "./yml/alertmanager.yml:/etc/alertmanager/alertmanager.yml"
  webhook:
    image: timonwong/prometheus-webhook-dingtalk
    restart: "always"
    ports:
      - 8060:8060
    container_name: "webhook"
    volumes:
      - "./yml/config.yml:/etc/prometheus-webhook-dingtalk/config.yml"

[root@node1 prom]# cat yml/prometheus.yml
# my global config
global:  # 此片段指定的是prometheus的全局配置， 比如采集间隔，抓取超时时间等.
  scrape_interval: 1m  # 抓取间隔 默认1m
  evaluation_interval: 1m   # 评估规则间隔 默认1m
  # scrape_timeout is set to the global default (10s).

# Alertmanager configuration
 # 此片段指定报警配置， 这里主要是指定prometheus将报警规则推送到指定的alertmanager实例地址
alerting:
  alertmanagers:
    - static_configs:
        - targets:
           - 192.168.10.10:9093

# Load rules once and periodically evaluate them according to the global 'evaluation_interval'.
rule_files:
   - "/etc/prometheus/rules/*.yml"   #报警规则文件
#  - "cpu_over.yml"
#  - "disk_over.yml"
#  - "memory_over.yml"
#  - "node_alived.yml"

# A scrape configuration containing exactly one endpoint to scrape:
# Here it's Prometheus itself.
# 抓取配置列表
scrape_configs:
  - job_name: "prometheus"
    static_configs:
      - targets: ["localhost:9090"]
  - job_name: "linux"
    static_configs:
      - targets: ["192.168.10.10:9100","192.168.10.10:8080","192.168.10.20:9100","192.168.10.20:8080"]

[root@node1 prom]#cat alertmanager.yml
global:
  resolve_timeout: 5m  #在指定时间内没有新的事件就发送恢复通知
route:
  receiver: webhook  #设置接收人
  group_wait: 1m  #组告警等待时间。在等待时间结束后，如果有同组告警一起发出
  group_interval: 1m  #两组告警间隔时间。
  repeat_interval: 1m  #重复告警间隔时间，减少相同邮件的发送频率。
  group_by: [alertname] #采用那个标签来作为分组。
receivers:   #通知接收者列表
- name: webhook
  webhook_configs:
  - url: http://192.168.10.10:8060/dingtalk/webhook1/send
    send_resolved: true

#########################################################

[root@node1 prom]# cat yml/config.yml
targets:
  webhook1:
    url: https://oapi.dingtalk.com/robot/send?access_token=XXXXXX    #webhook
    secret: SEC000000    #加签

[root@node1 prom]#cat alertmanager.yml
global:
  resolve_timeout: 5m  #在指定时间内没有新的事件就发送恢复通知
route:
  receiver: webhook  #设置接收人
  group_wait: 1m  #组告警等待时间。在等待时间结束后，如果有同组告警一起发出
  group_interval: 1m  #两组告警间隔时间。
  repeat_interval: 1m  #重复告警间隔时间，减少相同邮件的发送频率。
  group_by: [alertname] #采用那个标签来作为分组。
receivers:   #通知接收者列表
- name: webhook
  webhook_configs:
  - url: http://192.168.10.10:8060/dingtalk/webhook1/send
    send_resolved: true

#########################################################

[root@node1 prom]# cat yml/config.yml
targets:
  webhook1:
    url: https://oapi.dingtalk.com/robot/send?access_token=XXXXXX    #webhook
    secret: SEC000000    #加签

配置完成后docker-compose up -d 启动容器

http://localhost:8080   #cadvisor   
http://localhost:8080/metrics #cadvisor数据
http://localhost:9100/metrics   #node-exporter数据
http://localhost:9090 #prometheus
http://localhost:3000   #grafana

http://localhost:9090/alerts

实现效果

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