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package main
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import (
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"flag"
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"log"
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"math/rand"
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"net/http"
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"strings"
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"time"
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"github.com/gorilla/mux"
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"github.com/prometheus/client_golang/prometheus"
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"github.com/prometheus/client_golang/prometheus/promhttp"
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)
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var (
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addr = flag.String("listen-address", ":8080", "The address to listen on for HTTP requests.")
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)
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var (
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requestTimes = prometheus.NewCounterVec(prometheus.CounterOpts{
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Name: "request_times",
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Help: "请求次数",
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}, []string{"method", "url", "host"})
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// 多个label，需要与requestTimes.WithLabelValues(strings.ToLower(r.Method), r.URL.String())一一对应，
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// 效果为可用promql request_times{method="get",url="/metrics",host="172.20.16.185:8080"}查询
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requestTime = prometheus.NewGaugeVec(prometheus.GaugeOpts{
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Name: "request_time",
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Help: "每次请求花费的时间",
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}, []string{"method", "url", "host"})
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// 需要计算，开销大
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requestSummary = prometheus.NewSummaryVec(prometheus.SummaryOpts{
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Name: "request_time_summary",
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Help: "summary test",
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Objectives: map[float64]float64{0.5: 0.05, 0.9: 0.01, 0.99: 0.001},
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// 0.5，0.9，0.99表示分位数，0.05，0.01，0.001表示可接收的误差，比如0.5分位的值为10，其实这个10可能是(0.45,0.55)这个区间内的某个值，太过精确会导致cpu压力过大
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}, []string{"request_time"})
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// Histogram只计数，不计算，开销小
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// 线性桶
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requestHistogram = prometheus.NewHistogramVec(prometheus.HistogramOpts{
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Name: "request_time_histogram",
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Help: "histogram LinearBuckets test",
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Buckets: prometheus.LinearBuckets(1, 2, 20), // 初始为1，间隔为2，一共20个取值，Buckets会隐式添加 `+Inf` 值作为取值区间的最大值
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// request_time_histogram_bucket{instance="172.20.16.185:8080", job="my_metrics", le="1.0", request_time="request_time"}
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// request_time_histogram_bucket{instance="172.20.16.185:8080", job="my_metrics", le="3.0", request_time="request_time"}
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// ...
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// 会生成如上所示的指标，le: 小于等于
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// 即，比如第一个数据的值，表示为小于等于1.0的个数，此处即为响应时间小于等于1.0的请求的个数
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}, []string{"request_time"})
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// 默认桶
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requestHistogramDef = prometheus.NewHistogramVec(prometheus.HistogramOpts{
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Name: "request_time_histogram_def_buckets",
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Help: "histogram DefBuckets test",
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Buckets: prometheus.DefBuckets,
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}, []string{"request_time"})
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// 指数桶
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requestHistogramExponentialBuckets = prometheus.NewHistogramVec(prometheus.HistogramOpts{
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Name: "request_time_histogram_exponential_buckets",
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Help: "histogram ExponentialBuckets test",
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Buckets: prometheus.ExponentialBuckets(1, 2, 20), // 初始值为1，指数为2增长，20个取值
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}, []string{"request_time"})
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// 不同的桶根据具体情况而定
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metricsPath = flag.String("web.telemetry-path", "/metrics",
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"Path under which to expose metrics")
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)
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func init() {
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// Add Go module build info.
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// 也可prometheus.MustRegister(xx, yy)
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prometheus.MustRegister(requestTime)
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prometheus.MustRegister(requestTimes)
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prometheus.MustRegister(requestSummary)
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prometheus.MustRegister(requestHistogram, requestHistogramDef, requestHistogramExponentialBuckets)
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}
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func main() {
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flag.Parse()
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r := mux.NewRouter()
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r.HandleFunc("/", handlerIndex)
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r.Use(metricsMiddleware)
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r.Handle("/metrics", promhttp.HandlerFor(
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prometheus.DefaultGatherer,
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promhttp.HandlerOpts{
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// Opt into OpenMetrics to support exemplars.
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EnableOpenMetrics: true,
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},
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))
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log.Fatal(http.ListenAndServe(*addr, r))
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}
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func metricsMiddleware(next http.Handler) http.Handler {
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return http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
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start := time.Now().Unix()
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next.ServeHTTP(w, r)
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end := time.Now().Unix()
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requestTime.WithLabelValues(strings.ToLower(r.Method), r.URL.String(), r.Host).Set(float64(end - start))
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requestTimes.WithLabelValues(strings.ToLower(r.Method), r.URL.String(), r.Host).Add(1)
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requestSummary.WithLabelValues("request_time").Observe(float64(end - start))
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requestHistogram.WithLabelValues("request_time").Observe(float64(end - start))
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requestHistogramDef.WithLabelValues("request_time").Observe(float64(end - start))
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requestHistogramExponentialBuckets.WithLabelValues("request_time").Observe(float64(end - start))
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})
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}
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func handlerIndex(w http.ResponseWriter, r *http.Request) {
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x := rand.Intn(3)
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time.Sleep(time.Duration(x) * time.Second)
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//_, _ = w.Write([]byte("handler response"))
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_, _ = w.Write([]byte(`<html>
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<head><title>SRE Promethus Exporter</title></head>
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<body>
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<h1>SRE Promethus Exporter</h1>
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<p><a href='` + *metricsPath + `'>Metrics</a></p>
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</body>
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</html>`))
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log.Println("print handler index")
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}
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// 清除数据，各项数据都会清零
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func dataClear() {
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requestTime.Reset()
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requestTimes.Reset()
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requestHistogram.Reset()
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requestHistogramExponentialBuckets.Reset()
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requestHistogramDef.Reset()
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requestSummary.Reset()
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}
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