• 服务器环境
  CentOS Linux release 7.9.2009 (Core)
  Docker version 18.03.1-ce

安装前先同步服务器时间，prometheus对时间比较敏感

安装Grafana

docker run -d --restart always -p 3000:3000 --name=grafana -v /etc/localtime:/etc/localtime -v /data/grafana:/var/lib/grafana grafana/grafana:lstest

安装Prometheus

docker run -d --restart always -p 9090:9090  --name=prometheus -v /opt/prometheus/prometheus.yml:/etc/prometheus/prometheus.yml prom/prometheus

安装Node-exporter

docker run -d --restart always -p 9100:9100 --name=node-exporter -v "/proc:/host/proc:ro" -v /etc/localtime:/etc/localtime -v "/sys:/host/sys:ro" -v "/:/rootfs:ro" --net="host" prom/node-exporter

• 注：注意resatrt参数，根据需求确定是否使用。

linux主机监控

prometheus.yml

- job_name: 'jd-cloud'
  metrics_path: "/metrics"
    static_configs:
      - targets: ['IP:9100','IP:9100']
        labels:
          instance: centos

Granfa官网选用监控模板
此处我选择11074模板，根据需求做一些函数的更改，这里我也不会。

java应用监控

1.在pom.xml中添加依赖

<dependency>
      <groupId>org.springframework.boot</groupId>
      <artifactId>spring-boot-starter-actuator</artifactId>
 </dependency>
<dependency>
    <groupId>io.micrometer</groupId>
    <artifactId>micrometer-registry-prometheus</artifactId>
    <version>1.1.3</version>
</dependency>
<!-- 可选, 用于进程内存使用图表 -->
        <dependency>
            <groupId>io.github.mweirauch</groupId>
            <artifactId>micrometer-jvm-extras</artifactId>
            <version>0.2.0</version>
        </dependency>

2.修改spring boot配置（application.yml）

server:
  port: 8080
spring:
  application:
    name: spring-demo
management:
  endpoints:
    web:
      exposure:
        include: 'prometheus' # 暴露/actuator/prometheus
  metrics:
    tags:
      application: ${spring.application.name} # 暴露的数据中添加application label

3.Prometheus中采集数据

global:
  scrape_interval: 15s
scrape_configs:
  - job_name: "spring-demo"
    metrics_path: "/actuator/prometheus"
    static_configs:
    - targets: ["localhost:8080"]

4.通过remote write 写入SLS的时序存储
5.Grafana中添加数据源
使用模板12856，看出来了嘛，这是[抄的]（https://grafana.com/grafana/dashboards/12856)-_-