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# 如何配置Go+Grafana+InfluxDB
本文将介绍如何搭建一个完整的监控系统,使用Go语言采集数据,InfluxDB存储时序数据,并通过Grafana进行可视化展示。
## 一、环境准备
### 1. 安装InfluxDB
```bash
# Ubuntu/Debian
wget https://dl.influxdata.com/influxdb/releases/influxdb_1.8.10_amd64.deb
sudo dpkg -i influxdb_1.8.10_amd64.deb
sudo systemctl start influxdb
# 验证安装
influx -version
# Ubuntu/Debian
sudo apt-get install -y adduser libfontconfig1
wget https://dl.grafana.com/oss/release/grafana_9.5.2_amd64.deb
sudo dpkg -i grafana_9.5.2_amd64.deb
sudo systemctl start grafana-server
influx
> CREATE DATABASE metrics
> CREATE USER grafana WITH PASSWORD 'yourpassword'
> GRANT ALL ON metrics TO grafana
/etc/influxdb/influxdb.conf
:[http]
enabled = true
bind-address = ":8086"
go get github.com/influxdata/influxdb1-client/v2
package main
import (
"log"
"time"
influx "github.com/influxdata/influxdb1-client/v2"
)
func writeMetrics() {
c, err := influx.NewHTTPClient(influx.HTTPConfig{
Addr: "http://localhost:8086",
Username: "grafana",
Password: "yourpassword",
})
if err != nil {
log.Fatal(err)
}
defer c.Close()
bp, _ := influx.NewBatchPoints(influx.BatchPointsConfig{
Database: "metrics",
Precision: "s",
})
tags := map[string]string{"host": "server01"}
fields := map[string]interface{}{
"cpu_usage": 42.5,
"mem_usage": 75.3,
}
pt, _ := influx.NewPoint("system_metrics", tags, fields, time.Now())
bp.AddPoint(pt)
if err := c.Write(bp); err != nil {
log.Fatal(err)
}
}
访问http://localhost:3000
(默认admin/admin)
添加数据源:
http://localhost:8086
metrics
创建Dashboard:
SELECT mean("cpu_usage") FROM "system_metrics" WHERE $timeFilter GROUP BY time($__interval), "host"
Go应用 → 写入数据 → InfluxDB → Grafana可视化
通过以上步骤,您已成功搭建了一个完整的监控系统。可以根据实际需求扩展Go程序的指标采集逻辑,并在Grafana中创建更丰富的可视化图表。 “`
(全文约650字)
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