工程参考：

微信截图_20210202102056.png

1.node-exporter

node-exporter是用来收集linux主机节点指标信息的一个指标采集器。

1.1 具体编排如下：

version: '3.2'
services:
  node-exporter:
    image: prom/node-exporter:latest
    container_name: node-exporter
    hostname: node-exporter
    restart: always
    volumes:
      - /:/rootfs:ro
      - /proc:/host/proc:ro
      - /sys:/host/sys:ro
      - /usr/share/zoneinfo/Asia/Shanghai:/etc/localtime
    command:
      - '--path.procfs=/host/proc'
      - '--path.sysfs=/host/sys'
      - '--path.rootfs=/rootfs'
    ports:
      - "19100:9100"

#dashboard 8919

部署成功后，访问http://192.168.10.128:19100/metrics，如果有数据则说明部署成功。

1.2 在prometheus.yml配置文件中添加配置：

scrape_configs:
  ...
  - job_name: 'node-exporter'
    file_sd_configs: #这里基于文件发现的方式进行配置
    - files: ['./node_exporter/node.json']

  - job_name: 'node-exporter1'
    static_configs: #静态方式配置
      - targets: ['192.168.10.129:19100']
        labels: #labels标签可以自己定义，key: value
          app: 'node01'
          env: '测试环境'
  ...

./node_exporter/node.json文件如下：

[
  {
    "targets":[
      "192.168.10.128:9100"
    ],
    "labels":{
      "host":"prometheus.center",
      "env":"dev"
    }
  }，
  {
    "targets":[
      "192.168.10.129:9100",
      "192.168.10.130:9100"
    ],
    "labels":{
      "host":"prometheus.nodes",
      "env":"test"
    }
  }
]

node.json是一个json数组，也就是可以进行多个配置。

1.3 配置告警规则node_rules.yml

groups:
- name: hostStatsAlert
  rules:
  - alert: hostCpuUsageAlert
    expr: sum(avg without (cpu)(irate(node_cpu{mode!='idle'}[5m]))) by (instance) > 0.85
    for: 10m
    labels:
      severity: warning
    annotations:
      summary: "Instance {{ $labels.instance }} CPU usgae high"
      description: "{{ $labels.instance }} CPU usage above 85% (current value: {{ $value | humanize }})"
  - alert: hostMemUsageAlert
    expr: (node_memory_MemTotal_bytes - node_memory_MemFree_bytes)/node_memory_MemTotal_bytes > 0.85
    # expr: (1 - ((avg_over_time(node_memory_MemFree_bytes[1h]) + avg_over_time(node_memory_Cached_bytes[1h]) + avg_over_time(node_memory_Buffers_bytes[1h])) / avg_over_time(node_memory_MemTotal_bytes[1h]))) > 0.55
    for: 10m
    labels:
      severity: warning
    annotations:
      summary: "Instance {{ $labels.instance }} MEM usgae high"
      description: "{{ $labels.instance }} MEM usage above 85% (current value: {{ $value | humanize }})"
  # Alert for any instance that is unreachable for >5 minutes.
  - alert: InstanceDown
    expr: up == 0
    for: 5m
    labels:
      severity: warning
    annotations:
      summary: "Instance {{ $labels.instance }} down"
      description: "{{ $labels.instance }} of job {{ $labels.job }} has been down for more than 5 minutes."

  # Alert for any instance that has a median request latency >1s.
  - alert: APIHighRequestLatency
    expr: api_http_request_latencies_second{quantile="0.5"} > 1
    for: 10m
    labels:
      severity: warning
    annotations:
      summary: "High request latency on {{ $labels.instance }}"
      description: "{{ $labels.instance }} has a median request latency above 1s (current value: {{ $value | humanize }}s)"

将node_rules.yml上传到prometheus告警规则扫描路径中。

1.4 更新prometheus配置

curl -XPOST http://localhost:9090/-/reload

2.docker容器监控

docker容器指标可以使用cadvisor来收集。

2.1 编排文件

version: '3.2'
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
      - /usr/share/zoneinfo/Asia/Shanghai:/etc/localtime
    ports:
      - "18080:8080"

#dashboard 893 11558 8321

部署成功后，访问http://192.168.10.128:18080/metrics，如果有数据则说明部署成功。

2.2 配置prometheus.yml

scrape_configs:
  ...
  - job_name: 'container-exporter'
    file_sd_configs:
    - files: ['./container_exporter/container.json']
  ...
./container_exporter/container.json文件如下：
```json
[
  {
    "targets":[
      "192.168.10.128:18080",
      "192.168.10.129:18080"
    ],
    "labels":{
      "service":"docker-monitor",
      "env":"dev"
    }
  }
]

2.3 更新prometheus配置

curl -XPOST http://localhost:9090/-/reload