This tutorial provides a minimum example to verify that metrics and traces can be exported to OpenCensus from Go tools.
docker-compose up
If everything goes well, you should see output resembling the following:
Starting oragent_zipkin_1 ... done Starting oragent_oragent_1 ... done Starting oragent_prometheus_1 ... done ...
docker-compose up -d
. To stop oragent while detached, run docker-compose down
.internal
, create a file named main.go
with the following contents:package main
import (
"context"
"fmt"
"math/rand"
"net/http"
"time"
"golang.org/x/tools/internal/telemetry/event"
"golang.org/x/tools/internal/telemetry/export"
"golang.org/x/tools/internal/telemetry/export/metric"
"golang.org/x/tools/internal/telemetry/export/ocagent"
)
type testExporter struct {
metrics metric.Exporter
ocagent *ocagent.Exporter
}
func (e *testExporter) ProcessEvent(ctx context.Context, ev event.Event) (context.Context, event.Event) {
ctx, ev = export.Tag(ctx, ev)
ctx, ev = export.ContextSpan(ctx, ev)
ctx, ev = e.metrics.ProcessEvent(ctx, ev)
ctx, ev = e.ocagent.ProcessEvent(ctx, ev)
return ctx, ev
}
func main() {
exporter := &testExporter{}
exporter.ocagent = ocagent.Connect(&ocagent.Config{
Start: time.Now(),
Address: "http://127.0.0.1:55678",
Service: "go-tools-test",
Rate: 5 * time.Second,
Client: &http.Client{},
})
event.SetExporter(exporter)
ctx := context.TODO()
mLatency := event.NewFloat64Key("latency", "the latency in milliseconds")
distribution := metric.HistogramFloat64Data{
Info: &metric.HistogramFloat64{
Name: "latencyDistribution",
Description: "the various latencies",
Buckets: []float64{0, 10, 50, 100, 200, 400, 800, 1000, 1400, 2000, 5000, 10000, 15000},
},
}
distribution.Info.Record(&exporter.metrics, mLatency)
for {
sleep := randomSleep()
_, end := event.StartSpan(ctx, "main.randomSleep()")
time.Sleep(time.Duration(sleep) * time.Millisecond)
end()
event.Record(ctx, mLatency.Of(float64(sleep)))
fmt.Println("Latency: ", float64(sleep))
}
}
func randomSleep() int64 {
var max int64
switch modulus := time.Now().Unix() % 5; modulus {
case 0:
max = 17001
case 1:
max = 8007
case 2:
max = 917
case 3:
max = 87
case 4:
max = 1173
}
return rand.Int63n(max)
}
go run internal/main.go
# HELP promdemo_latencyDistribution the various latencies # TYPE promdemo_latencyDistribution histogram promdemo_latencyDistribution_bucket{vendor="otc",le="0"} 0 promdemo_latencyDistribution_bucket{vendor="otc",le="10"} 2 promdemo_latencyDistribution_bucket{vendor="otc",le="50"} 9 promdemo_latencyDistribution_bucket{vendor="otc",le="100"} 22 promdemo_latencyDistribution_bucket{vendor="otc",le="200"} 35 promdemo_latencyDistribution_bucket{vendor="otc",le="400"} 49 promdemo_latencyDistribution_bucket{vendor="otc",le="800"} 63 promdemo_latencyDistribution_bucket{vendor="otc",le="1000"} 78 promdemo_latencyDistribution_bucket{vendor="otc",le="1400"} 93 promdemo_latencyDistribution_bucket{vendor="otc",le="2000"} 108 promdemo_latencyDistribution_bucket{vendor="otc",le="5000"} 123 promdemo_latencyDistribution_bucket{vendor="otc",le="10000"} 138 promdemo_latencyDistribution_bucket{vendor="otc",le="15000"} 153 promdemo_latencyDistribution_bucket{vendor="otc",le="+Inf"} 15 promdemo_latencyDistribution_sum{vendor="otc"} 1641 promdemo_latencyDistribution_count{vendor="otc"} 15
After a few more seconds, Prometheus should start displaying your new metrics. You can view the distribution at http://localhost:9445/graph?g0.range_input=5m&g0.stacked=1&g0.expr=rate(oragent_latencyDistribution_bucket%5B5m%5D)&g0.tab=0.
Zipkin should also start displaying traces. You can view them at http://localhost:9444/zipkin/?limit=10&lookback=300000&serviceName=go-tools-test.