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// 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"
"strconv"
"time"
"github.com/prometheus/client_golang/prometheus"
"github.com/prometheus/client_golang/prometheus/collectors"
"github.com/prometheus/client_golang/prometheus/promhttp"
)
type metrics struct {
rpcDurations *prometheus.SummaryVec
rpcDurationsHistogram prometheus.Histogram
}
func NewMetrics(reg prometheus.Registerer, normMean, normDomain float64) *metrics {
m := &metrics{
// Create a summary to track fictional inter service 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 histogram features both conventional
// buckets as well as sparse buckets, the latter needed for the
// experimental native histograms (ingested by a Prometheus
// server v2.40 with the corresponding feature flag
// enabled). The conventional buckets are targeted to the
// parameters of the normal distribution, with 20 buckets
// centered on the mean, each half-sigma wide. The sparse
// buckets are always centered on zero, with a growth factor of
// one bucket to the next of (at most) 1.1. (The precise factor
// is 2^2^-3 = 1.0905077...)
rpcDurationsHistogram: prometheus.NewHistogram(prometheus.HistogramOpts{
Name: "rpc_durations_histogram_seconds",
Help: "RPC latency distributions.",
Buckets: prometheus.LinearBuckets(normMean-5*normDomain, .5*normDomain, 20),
NativeHistogramBucketFactor: 1.1,
}),
}
reg.MustRegister(m.rpcDurations)
reg.MustRegister(m.rpcDurationsHistogram)
return m
}
func main() {
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.")
)
flag.Parse()
// Create a non-global registry.
reg := prometheus.NewRegistry()
// Create new metrics and register them using the custom registry.
m := NewMetrics(reg, *normMean, *normDomain)
// Add Go module build info.
reg.MustRegister(collectors.NewBuildInfoCollector())
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
m.rpcDurations.WithLabelValues("uniform").Observe(v)
time.Sleep(time.Duration(100*oscillationFactor()) * time.Millisecond)
}
}()
go func() {
for {
v := (rand.NormFloat64() * *normDomain) + *normMean
m.rpcDurations.WithLabelValues("normal").Observe(v)
// Demonstrate exemplar support with a dummy ID. This
// would be something like a trace ID in a real
// application. Note the necessary type assertion. We
// already know that rpcDurationsHistogram implements
// the ExemplarObserver interface and thus don't need to
// check the outcome of the type assertion.
m.rpcDurationsHistogram.(prometheus.ExemplarObserver).ObserveWithExemplar(
v, prometheus.Labels{"dummyID": strconv.Itoa(rand.Intn(100000))},
)
time.Sleep(time.Duration(75*oscillationFactor()) * time.Millisecond)
}
}()
go func() {
for {
v := rand.ExpFloat64() / 1e6
m.rpcDurations.WithLabelValues("exponential").Observe(v)
time.Sleep(time.Duration(50*oscillationFactor()) * time.Millisecond)
}
}()
// Expose the registered metrics via HTTP.
http.Handle("/metrics", promhttp.HandlerFor(
reg,
promhttp.HandlerOpts{
// Opt into OpenMetrics to support exemplars.
EnableOpenMetrics: true,
// Pass custom registry
Registry: reg,
},
))
log.Fatal(http.ListenAndServe(*addr, nil))
}
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