如何使用docker部署grafana+prometheus配置

这篇文章主要为大家展示了“如何使用docker部署grafana+prometheus配置”，内容简而易懂，条理清晰，希望能够帮助大家解决疑惑，下面让小编带领大家一起研究并学习一下“如何使用docker部署grafana+prometheus配置”这篇文章吧。

docker-compose-monitor.yml

version: '2'networks:  monitor:    driver: bridgeservices:  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: trueinhibit_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 configurationalerting:  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 }}"

以上是“如何使用docker部署grafana+prometheus配置”这篇文章的所有内容，感谢各位的阅读！相信大家都有了一定的了解，希望分享的内容对大家有所帮助，如果还想学习更多知识，欢迎关注编程网行业资讯频道！