/
main.go
150 lines (111 loc) · 3.82 KB
/
main.go
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package main
import (
/*
"flag"
"math"
"math/rand"
"time"
*/
"fmt"
"log"
"net/http"
"os"
"./routers"
"github.com/prometheus/client_golang/prometheus"
"github.com/golang/protobuf/proto"
dto "github.com/prometheus/client_model/go"
"math"
_ "net/http/pprof"
)
func main() {
router := routers.NewRouter()
var port string
fmt.Printf("len(os.Args) = %d ", len(os.Args))
if ( len(os.Args) <= 1) {
fmt.Println("Please speficy the port or use default port 8090")
port = "8090"
} else {
port = os.Args[1]
}
fmt.Printf("port = %s", port)
// histogram
temps := prometheus.NewHistogram(prometheus.HistogramOpts{
Name: "pond_temperature_celsius",
Help: "The temperature of the frog pond.", // Sorry, we can't measure how badly it smells.
Buckets: prometheus.LinearBuckets(20, 5, 5), // 5 buckets, each 5 centigrade wide.
})
// Simulate some observations.
for i := 0; i < 1000; i++ {
temps.Observe(30 + math.Floor(120*math.Sin(float64(i)*0.1))/10)
}
// Just for demonstration, let's check the state of the histogram by
// (ab)using its Write method (which is usually only used by Prometheus
// internally).
metric := &dto.Metric{}
temps.Write(metric)
fmt.Println(proto.MarshalTextString(metric))
router.Handle("/metrics", prometheus.Handler())
//log.Fatal(http.ListenAndServe(":8090", router))
log.Fatal(http.ListenAndServe(":" + port, router))
}
func prometheusCall() {
}
/*
// backup code for duration , rpc
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),
})
)
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)
}
}()
*/