Go进阶31:Prometheus Client教程

package main

import (
	"flag"
	"log"
	"math"
	"math/rand"
	"net/http"
	"time"

	"github.com/prometheus/client_golang/prometheus"
	"github.com/prometheus/client_golang/prometheus/promhttp"
)

var (
	addr              = flag.String("listen-address", ":8080", "The address to listen on for HTTP requests.")
	uniformDomain     = flag.Float64("uniform.domain", 0.0002, "The domain for the uniform distribution.")
	normDomain        = flag.Float64("normal.domain", 0.0002, "The domain for the normal distribution.")
	normMean          = flag.Float64("normal.mean", 0.00001, "The mean for the normal distribution.")
	oscillationPeriod = flag.Duration("oscillation-period", 10*time.Minute, "The duration of the rate oscillation period.")
)

var (
	// 1. 创建 Prometheus 数据Metric, 就相当于SQL 数据库 声明table
	// Create a summary to track fictional interservice RPC latencies for three
	// distinct services with different latency distributions. These services are
	// differentiated via a "service" label.
	RpcDurations = prometheus.NewSummaryVec(
		prometheus.SummaryOpts{
			Name:       "rpc_durations_seconds",
			Help:       "RPC latency distributions.这个metric的帮助信息,metric的项目作用说明",
			Objectives: map[float64]float64{0.5: 0.05, 0.9: 0.01, 0.99: 0.001},
		},
		[]string{"service"},
	)
	// The same as above, but now as a histogram, and only for the normal
	// distribution. The buckets are targeted to the parameters of the
	// normal distribution, with 20 buckets centered on the mean, each
	// half-sigma wide.
	RpcDurationsHistogram = prometheus.NewHistogram(prometheus.HistogramOpts{
		Name:    "rpc_durations_histogram_seconds",
		Help:    "RPC latency distributions.这个metric的帮助信息,metric的项目作用说明",
		Buckets: prometheus.LinearBuckets(*normMean-5**normDomain, .5**normDomain, 20),
	})
)

func init() {
	// 2. 注册定义好的Metric 相当于执行SQL create table 语句
	// Register the summary and the histogram with Prometheus's default registry.
	prometheus.MustRegister(RpcDurations)
	prometheus.MustRegister(RpcDurationsHistogram)
	// Add Go module build info.
	prometheus.MustRegister(prometheus.NewBuildInfoCollector())
}

func main() {
	flag.Parse()

	start := time.Now()

	oscillationFactor := func() float64 {
		return 2 + math.Sin(math.Sin(2*math.Pi*float64(time.Since(start))/float64(*oscillationPeriod)))
	}
    // 3. 业务在无代码中想插入对时序书库TSDB数据想的数据写入操作,相当与SQL insert
	// Periodically record some sample latencies for the three services.
	go func() {
		for {
			v := rand.Float64() * *uniformDomain
			RpcDurations.WithLabelValues("uniform").Observe(v)
			time.Sleep(time.Duration(100*oscillationFactor()) * time.Millisecond)
		}
	}()

	go func() {
		for {
			v := (rand.NormFloat64() * *normDomain) + *normMean
			RpcDurations.WithLabelValues("normal").Observe(v)
			RpcDurationsHistogram.Observe(v)
			time.Sleep(time.Duration(75*oscillationFactor()) * time.Millisecond)
		}
	}()

	go func() {
		for {
			v := rand.ExpFloat64() / 1e6
			RpcDurations.WithLabelValues("exponential").Observe(v)
			time.Sleep(time.Duration(50*oscillationFactor()) * time.Millisecond)
		}
	}()

    // 4. 提供HTTP API接口,让Prometheus 主程序定时来收集时序数据
	// Expose the registered metrics via HTTP.
	http.Handle("/metrics", promhttp.Handler())
	log.Fatal(http.ListenAndServe(*addr, nil))
}

package stat

import (
	"github.com/prometheus/client_golang/prometheus"
)

var (
	// The same as above, but now as a histogram, and only for the normal
	// distribution. The buckets are targeted to the parameters of the
	// normal distribution, with 20 buckets centered on the mean, each
	// half-sigma wide.
	//GaugeVecApiDuration = prometheus.NewHistogram(prometheus.HistogramOpts{
	//	Name:    "HttpDuration",
	//	Help:    "api requset 耗时单位ms",
	//	Buckets: prometheus.LinearBuckets(0, 1000, 50),
	//})
	GaugeVecApiDuration = prometheus.NewGaugeVec(prometheus.GaugeOpts{
		Name: "apiDuration",
		Help: "api耗时单位ms",
	}, []string{"WSorAPI"})
	GaugeVecApiMethod = prometheus.NewGaugeVec(prometheus.GaugeOpts{
		Name: "apiCount",
		Help: "各种网络请求次数",
	}, []string{"method"})
	GaugeVecApiError = prometheus.NewGaugeVec(prometheus.GaugeOpts{
		Name: "apiErrorCount",
		Help: "请求api错误的次数type: api/ws",
	}, []string{"type"})
)

func init() {
	// Register the summary and the histogram with Prometheus's default registry.
	prometheus.MustRegister(GaugeVecApiMethod, GaugeVecApiDuration, GaugeVecApiError)
}

package handler

import (
	"fortress/stat"//导入第一步中初始换好的stat(prometheus client_golang 初始化包中的监控项)
	"github.com/gin-gonic/gin"
	"time"
)

func MwPrometheusHttp(c *gin.Context) {
	start := time.Now()
	method := c.Request.Method
	stat.GaugeVecApiMethod.WithLabelValues(method).Inc()

	c.Next()
	// after request
	end := time.Now()
	d := end.Sub(start) / time.Millisecond
	stat.GaugeVecApiDuration.WithLabelValues(method).Set(float64(d))
}

import (
	"fortress/stat"
)
func jsonError(c *gin.Context, msg interface{}) {
	stat.GaugeVecApiError.WithLabelValues("API").Inc()
	var ms string
	switch v := msg.(type) {
	case string:
		ms = v
	case error:
		ms = v.Error()
	default:
		ms = ""
	}
	c.AbortWithStatusJSON(200, gin.H{"ok": false, "msg": ms})
}

...
	r.GET("metrics", gin.WrapH(promhttp.Handler()))
	api := r.Group("api").Use(handler.MwPrometheusHttp)
...