client_golang/examples/random/main.go

107 lines
3.6 KiB
Go

// Copyright 2015 The Prometheus Authors
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// A simple example exposing fictional RPC latencies with different types of
// random distributions (uniform, normal, and exponential) as Prometheus
// metrics.
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 (
// 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.",
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.",
Buckets: prometheus.LinearBuckets(*normMean-5**normDomain, .5**normDomain, 20),
})
)
func init() {
// Register the summary and the histogram with Prometheus's default registry.
prometheus.MustRegister(rpcDurations)
prometheus.MustRegister(rpcDurationsHistogram)
}
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)))
}
// 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)
}
}()
// Expose the registered metrics via HTTP.
http.Handle("/metrics", promhttp.Handler())
log.Fatal(http.ListenAndServe(*addr, nil))
}