// 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" "math" "math/rand" "net/http" "time" "github.com/prometheus/client_golang/prometheus" ) var ( addr = flag.String("listen-address", ":8080", "The address to listen on for HTTP requests.") uniformDomain = flag.Float64("uniform.domain", 200, "The domain for the uniform distribution.") normDomain = flag.Float64("normal.domain", 200, "The domain for the normal distribution.") normMean = flag.Float64("normal.mean", 10, "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_microseconds", Help: "RPC latency distributions.", }, []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_microseconds", 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() rpcDurations.WithLabelValues("exponential").Observe(v) time.Sleep(time.Duration(50*oscillationFactor()) * time.Millisecond) } }() // Expose the registered metrics via HTTP. http.Handle("/metrics", prometheus.Handler()) http.ListenAndServe(*addr, nil) }