如何在CentOS监控Golang应用

发布时间:2025-04-30 18:56:28

阅读量:121

在CentOS上监控Golang应用可以通过多种工具和方法实现，以下是一些常用的方法和工具：

结构化日志

使用结构化日志工具如Zap记录应用日志，并通过Loki进行日志聚合和分析。

Prometheus + Grafana

安装Prometheus：

wget https://github.com/prometheus/prometheus/releases/download/v2.36.1/prometheus-2.36.1.linux-amd64.tar.gz
tar -xf prometheus-2.36.1.linux-amd64.tar.gz
cd prometheus-2.36.1.linux-amd64
./prometheus --config.file prometheus.yml

安装Grafana：

wget https://dl.grafana.com/oss/release/grafana-9.3.2.linux-amd64.tar.gz
tar -xf grafana-9.3.2.linux-amd64.tar.gz
cd grafana-9.3.2.linux-amd64
./bin/grafana-server

配置Prometheus抓取目标：在 prometheus.yml 中添加配置，例如监控Golang应用的指标端点：

scrape_configs:
  - job_name: 'myapp'
    static_configs:
      - targets: ['localhost:8080']

在Golang应用中暴露指标：

import (
    "net/http"
    "github.com/prometheus/client_golang/prometheus"
    "github.com/prometheus/client_golang/prometheus/promhttp"
)

var (
    requestCount = prometheus.NewCounter(prometheus.CounterOpts{
        Namespace: "myapp",
        Name: "http_requests_total",
        Help: "Total number of HTTP requests",
    })
    requestLatency = prometheus.NewHistogram(prometheus.HistogramOpts{
        Namespace: "myapp",
        Name: "http_request_latency_ms",
        Help: "Latency of HTTP requests in ms",
        Buckets: prometheus.DefBuckets,
    })
)

func main() {
    http.HandleFunc("/", func(w http.ResponseWriter, r *http.Request) {
        requestCount.Inc()
        requestLatency.Observe(float64(time.Since(time.Now()).Milliseconds()))
        w.Write([]byte("Hello, world!"))
    })
    http.Handle("/metrics", promhttp.Handler())
    http.ListenAndServe(":8080", nil)
}