mirror of
https://github.com/Luzifer/promcertcheck.git
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103 lines
3.4 KiB
Go
103 lines
3.4 KiB
Go
// Copyright 2015 The Prometheus Authors
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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// A simple example exposing fictional RPC latencies with different types of
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// random distributions (uniform, normal, and exponential) as Prometheus
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// metrics.
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package main
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import (
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"flag"
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"math"
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"math/rand"
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"net/http"
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"time"
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"github.com/prometheus/client_golang/prometheus"
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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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uniformDomain = flag.Float64("uniform.domain", 200, "The domain for the uniform distribution.")
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normDomain = flag.Float64("normal.domain", 200, "The domain for the normal distribution.")
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normMean = flag.Float64("normal.mean", 10, "The mean for the normal distribution.")
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oscillationPeriod = flag.Duration("oscillation-period", 10*time.Minute, "The duration of the rate oscillation period.")
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)
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var (
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// Create a summary to track fictional interservice RPC latencies for three
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// distinct services with different latency distributions. These services are
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// differentiated via a "service" label.
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rpcDurations = prometheus.NewSummaryVec(
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prometheus.SummaryOpts{
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Name: "rpc_durations_microseconds",
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Help: "RPC latency distributions.",
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},
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[]string{"service"},
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)
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// The same as above, but now as a histogram, and only for the normal
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// distribution. The buckets are targeted to the parameters of the
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// normal distribution, with 20 buckets centered on the mean, each
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// half-sigma wide.
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rpcDurationsHistogram = prometheus.NewHistogram(prometheus.HistogramOpts{
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Name: "rpc_durations_histogram_microseconds",
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Help: "RPC latency distributions.",
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Buckets: prometheus.LinearBuckets(*normMean-5**normDomain, .5**normDomain, 20),
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})
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)
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func init() {
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// Register the summary and the histogram with Prometheus's default registry.
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prometheus.MustRegister(rpcDurations)
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prometheus.MustRegister(rpcDurationsHistogram)
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}
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func main() {
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flag.Parse()
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start := time.Now()
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oscillationFactor := func() float64 {
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return 2 + math.Sin(math.Sin(2*math.Pi*float64(time.Since(start))/float64(*oscillationPeriod)))
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}
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// Periodically record some sample latencies for the three services.
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go func() {
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for {
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v := rand.Float64() * *uniformDomain
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rpcDurations.WithLabelValues("uniform").Observe(v)
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time.Sleep(time.Duration(100*oscillationFactor()) * time.Millisecond)
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}
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}()
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go func() {
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for {
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v := (rand.NormFloat64() * *normDomain) + *normMean
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rpcDurations.WithLabelValues("normal").Observe(v)
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rpcDurationsHistogram.Observe(v)
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time.Sleep(time.Duration(75*oscillationFactor()) * time.Millisecond)
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}
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}()
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go func() {
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for {
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v := rand.ExpFloat64()
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rpcDurations.WithLabelValues("exponential").Observe(v)
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time.Sleep(time.Duration(50*oscillationFactor()) * time.Millisecond)
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}
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}()
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// Expose the registered metrics via HTTP.
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http.Handle("/metrics", prometheus.Handler())
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http.ListenAndServe(*addr, nil)
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}
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