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服務器之家 - 服務器技術 - 服務器知識 - 使用docker部署grafana+prometheus配置

使用docker部署grafana+prometheus配置

2022-01-20 17:12runzhao 服務器知識

這篇文章主要介紹了docker部署grafana+prometheus配置,本文給大家介紹的非常詳細,對大家的學習或工作具有一定的參考借鑒價值,需要的朋友可以參考下

docker-compose-monitor.yml

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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里的時間為東八區時間
      - ./timezone:/etc/timezone:ro
      - ./localtime:/etc/localtime:ro
    restart: unless-stopped #停止后自動
 
  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

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global:
  resolve_timeout: 5m
  smtp_from: '郵箱'
  smtp_smarthost: 'smtp.exmail.qq.com:25'
  smtp_auth_username: '郵箱'
  smtp_auth_password: '密碼'
  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: '收件郵箱'
    send_resolved: true
inhibit_rules:
  - source_match:
      severity: 'critical'
    target_match:
      severity: 'warning'
    equal: ['alertname', 'dev', 'instance']

prometheus.yml

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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存儲節點組
  - job_name: 'io'
    scrape_interval: 8s
    static_configs:     #端口為node-exporter啟動的端口 
      - 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:     #端口為cadvisor啟動的端口
      - 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

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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.'
 
        #剩余內存小于10%
      - alert: 剩余內存小于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 }}"
 
        #剩余磁盤小于10%
      - alert: 剩余磁盤小于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負載 > 80%
      - alert: CPU負載 > 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

官網儀表盤:https://grafana.com/grafana/dashboards/

到此這篇關于docker部署grafana+prometheus配置的文章就介紹到這了,更多相關docker部署grafana+prometheus內容請搜索服務器之家以前的文章或繼續瀏覽下面的相關文章希望大家以后多多支持服務器之家!

原文鏈接:https://www.cnblogs.com/runzhao/p/15716274.html

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