欢迎您访问程序员文章站本站旨在为大家提供分享程序员计算机编程知识!
您现在的位置是: 首页  >  网络运营

使用docker部署grafana+prometheus配置

程序员文章站 2022-03-01 20:05:27
docker-compose-monitor.ymlversion: '2'networks: monitor: driver: bridgeservices: influxdb: i...

docker-compose-monitor.yml

version: '2'

networks:
  monitor:
    driver: bridge

services:
  influxdb:
    image: influxdb:latest
    container_name: tig-influxdb
    ports:
      - "18083:8083"
      - "18086:8086"
      - "18090:8090"
    env_file:
      - 'env.influxdb'
    volumes:
      # data persistency
      # sudo mkdir -p ./influxdb/data
      - ./influxdb/data:/var/lib/influxdb
      # 配置docker里的时间为东八区时间
      - ./timezone:/etc/timezone:ro
      - ./localtime:/etc/localtime:ro
    restart: unless-stopped #停止后自动

  telegraf:
    image: telegraf:latest
    container_name: tig-telegraf
    links:
      - influxdb
    volumes:
      - ./telegraf.conf:/etc/telegraf/telegraf.conf:ro
      - ./timezone:/etc/timezone:ro
      - ./localtime:/etc/localtime:ro
    restart: unless-stopped
  prometheus:
    image: prom/prometheus
    container_name: prometheus
    hostname: prometheus
    restart: always
    volumes:
      - /home/qa/docker/grafana/prometheus.yml:/etc/prometheus/prometheus.yml
      - /home/qa/docker/grafana/node_down.yml:/etc/prometheus/node_down.yml
    ports:
      - '9090:9090'
    networks:
      - monitor

  alertmanager:
    image: prom/alertmanager
    container_name: alertmanager
    hostname: alertmanager
    restart: always
    volumes:
      - /home/qa/docker/grafana/alertmanager.yml:/etc/alertmanager/alertmanager.yml
    ports:
      - '9093:9093'
    networks:
      - monitor

  grafana:
    image: grafana/grafana:6.7.4
    container_name: grafana
    hostname: grafana
    restart: always
    ports:
      - '13000:3000'
    networks:
      - monitor

  node-exporter:
    image: quay.io/prometheus/node-exporter
    container_name: node-exporter
    hostname: node-exporter
    restart: always
    ports:
      - '9100:9100'
    networks:
      - monitor

  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:
      - '18080:8080'
    networks:
      - monitor

alertmanager.yml

global:
  resolve_timeout: 5m
  smtp_from: '邮箱'
  smtp_smarthost: 'smtp.exmail.qq.com:25'
  smtp_auth_username: '邮箱'
  smtp_auth_password: '密码'
  smtp_require_tls: false
  smtp_hello: 'qq.com'
route:
  group_by: ['alertname']
  group_wait: 5s
  group_interval: 5s
  repeat_interval: 5m
  receiver: 'email'
receivers:
- name: 'email'
  email_configs:
  - to: '收件邮箱'
    send_resolved: true
inhibit_rules:
  - source_match:
      severity: 'critical'
    target_match:
      severity: 'warning'
    equal: ['alertname', 'dev', 'instance']

prometheus.yml

global:
  scrape_interval:     15s # set the scrape interval to every 15 seconds. default is every 1 minute.
  evaluation_interval: 15s # evaluate rules every 15 seconds. the default is every 1 minute.
  # scrape_timeout is set to the global default (10s).

# alertmanager configuration
alerting:
  alertmanagers:
  - static_configs:
    - targets: ['192.168.32.117:9093']
      # - alertmanager:9093

# load rules once and periodically evaluate them according to the global 'evaluation_interval'.
rule_files:
  - "node_down.yml"
  # - "node-exporter-alert-rules.yml"
  # - "first_rules.yml"
  # - "second_rules.yml"

# a scrape configuration containing exactly one endpoint to scrape:
# here it's prometheus itself.
scrape_configs:
  # io存储节点组
  - job_name: 'io'
    scrape_interval: 8s
    static_configs:     #端口为node-exporter启动的端口 
      - targets: ['192.168.32.117:9100']
      - targets: ['192.168.32.196:9100']
      - targets: ['192.168.32.136:9100']
      - targets: ['192.168.32.193:9100']
      - targets: ['192.168.32.153:9100']
      - targets: ['192.168.32.185:9100']
      - targets: ['192.168.32.190:19100']
      - targets: ['192.168.32.192:9100']

  # the job name is added as a label `job=<job_name>` to any timeseries scraped from this config.
  - job_name: 'cadvisor'
    static_configs:     #端口为cadvisor启动的端口
      - targets: ['192.168.32.117:18080']
      - targets: ['192.168.32.193:8080']
      - targets: ['192.168.32.153:8080']
      - targets: ['192.168.32.185:8080']
      - targets: ['192.168.32.190:18080']
      - targets: ['192.168.32.192:18080']

node_down.yml

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.'

        #剩余内存小于10%
      - alert: 剩余内存小于10%
        expr: node_memory_memavailable_bytes / node_memory_memtotal_bytes * 100 < 10
        for: 2m
        labels:
          severity: warning
        annotations:
          summary: host out of memory (instance {{ $labels.instance }})
          description: "node memory is filling up (< 10% left)\n  value = {{ $value }}\n  labels = {{ $labels }}"

        #剩余磁盘小于10%
      - alert: 剩余磁盘小于10%
        expr: (node_filesystem_avail_bytes * 100) / node_filesystem_size_bytes < 10 and on (instance, device, mountpoint) node_filesystem_readonly == 0
        for: 2m
        labels:
          severity: warning
        annotations:
          summary: host out of disk space (instance {{ $labels.instance }})
          description: "disk is almost full (< 10% left)\n  value = {{ $value }}\n  labels = {{ $labels }}"

        #cpu负载 > 80%
      - alert: cpu负载 > 80%
        expr: 100 - (avg by(instance) (rate(node_cpu_seconds_total{mode="idle"}[2m])) * 100) > 80
        for: 0m
        labels:
          severity: warning
        annotations:
          summary: host high cpu load (instance {{ $labels.instance }})
          description: "cpu load is > 80%\n  value = {{ $value }}\n  labels = {{ $labels }}"

告警:https://awesome-prometheus-alerts.grep.to/rules#prometheus-self-monitoring

官网仪表盘:https://grafana.com/grafana/dashboards/

到此这篇关于docker部署grafana+prometheus配置的文章就介绍到这了,更多相关docker部署grafana+prometheus内容请搜索以前的文章或继续浏览下面的相关文章希望大家以后多多支持!