指标与监控
暴露应用指标允许你在生产环境中监控请求速率、延迟、错误率和资源使用情况。Prometheus 是与 Go 应用一起使用的最常见监控系统。
Using gin-contrib/openmetrics
The gin-contrib/openmetrics middleware provides a ready-to-use Prometheus metrics endpoint:
go get github.com/gin-contrib/openmetricspackage main
import ( "github.com/gin-contrib/openmetrics" "github.com/gin-gonic/gin")
func main() { r := gin.Default()
// Expose /metrics endpoint for Prometheus scraping r.Use(openmetrics.NewOpenMetrics("myapp", openmetrics.WithExpose()))
r.GET("/ping", func(c *gin.Context) { c.JSON(200, gin.H{"message": "pong"}) })
r.Run(":8080")}Custom Prometheus metrics
For more control, use the prometheus/client_golang library directly:
package main
import ( "strconv" "time"
"github.com/gin-gonic/gin" "github.com/prometheus/client_golang/prometheus" "github.com/prometheus/client_golang/prometheus/promhttp")
var ( httpRequestsTotal = prometheus.NewCounterVec( prometheus.CounterOpts{ Name: "http_requests_total", Help: "Total number of HTTP requests", }, []string{"method", "path", "status"}, )
httpRequestDuration = prometheus.NewHistogramVec( prometheus.HistogramOpts{ Name: "http_request_duration_seconds", Help: "HTTP request duration in seconds", Buckets: prometheus.DefBuckets, }, []string{"method", "path"}, ))
func init() { prometheus.MustRegister(httpRequestsTotal) prometheus.MustRegister(httpRequestDuration)}
func MetricsMiddleware() gin.HandlerFunc { return func(c *gin.Context) { start := time.Now()
c.Next()
duration := time.Since(start).Seconds() status := strconv.Itoa(c.Writer.Status())
httpRequestsTotal.WithLabelValues(c.Request.Method, c.FullPath(), status).Inc() httpRequestDuration.WithLabelValues(c.Request.Method, c.FullPath()).Observe(duration) }}
func main() { r := gin.Default() r.Use(MetricsMiddleware())
// Expose metrics endpoint (separate from application routes) r.GET("/metrics", gin.WrapH(promhttp.Handler()))
r.GET("/ping", func(c *gin.Context) { c.JSON(200, gin.H{"message": "pong"}) })
r.Run(":8080")}Key metrics to monitor
For a production Gin application, track these metrics:
| Metric | Type | Purpose |
|---|---|---|
http_requests_total | Counter | Total request count by method, path, status |
http_request_duration_seconds | Histogram | Request latency distribution |
http_requests_in_flight | Gauge | Currently processing requests |
http_response_size_bytes | Histogram | Response body sizes |
Serving metrics on a separate port
In production, serve metrics on a separate port to keep them internal:
package main
import ( "net/http"
"github.com/gin-gonic/gin" "github.com/prometheus/client_golang/prometheus/promhttp")
func main() { // Application server app := gin.Default() app.GET("/ping", func(c *gin.Context) { c.JSON(200, gin.H{"message": "pong"}) })
// Metrics server on a separate port go func() { metrics := http.NewServeMux() metrics.Handle("/metrics", promhttp.Handler()) http.ListenAndServe(":9090", metrics) }()
app.Run(":8080")}This way, you can expose port 8080 publicly while keeping port 9090 internal to your infrastructure.
Prometheus scrape configuration
Add your application to the Prometheus configuration:
scrape_configs: - job_name: "gin-app" scrape_interval: 15s static_configs: - targets: ["localhost:9090"]Testing
# Generate some trafficcurl http://localhost:8080/ping
# Check metricscurl http://localhost:9090/metricsYou should see output like:
# HELP http_requests_total Total number of HTTP requests# TYPE http_requests_total counterhttp_requests_total{method="GET",path="/ping",status="200"} 1
# HELP http_request_duration_seconds HTTP request duration in seconds# TYPE http_request_duration_seconds histogramhttp_request_duration_seconds_bucket{method="GET",path="/ping",le="0.005"} 1...