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We no longer use the span as the core type of tracing, instead that is an artifact of the exporter, and start and end tracing is just event based. This both makes the interface normalized, and also means the null exporter case is considerably cheaper in memory and cpu. See below for benchstat changes name old time/op new time/op delta TracingNoExporter-8 4.19µs ±12% 2.71µs ±11% -35.33% (p=0.000 n=20+20) Tracing-8 24.1µs ± 3% 5.1µs ±17% -78.66% (p=0.000 n=16+20) name old alloc/op new alloc/op delta TracingNoExporter-8 2.32kB ± 0% 0.40kB ± 0% -82.76% (p=0.000 n=20+20) Tracing-8 6.32kB ± 0% 2.32kB ± 0% -63.30% (p=0.000 n=20+20) name old allocs/op new allocs/op delta TracingNoExporter-8 35.0 ± 0% 15.0 ± 0% -57.14% (p=0.000 n=20+20) Tracing-8 215 ± 0% 35 ± 0% -83.72% (p=0.000 n=20+20) Change-Id: I3cf25871fa49584819504b5c19aa580e5dd03395 Reviewed-on: https://go-review.googlesource.com/c/tools/+/221740 Run-TryBot: Ian Cottrell <iancottrell@google.com> TryBot-Result: Gobot Gobot <gobot@golang.org> Reviewed-by: Emmanuel Odeke <emm.odeke@gmail.com> |
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wire | ||
metrics_test.go | ||
metrics.go | ||
ocagent_test.go | ||
ocagent.go | ||
README.md |
Exporting Metrics with OpenCensus and Prometheus
This tutorial provides a minimum example to verify that metrics can be exported to OpenCensus from Go tools.
Setting up the OpenCensus Agent
- Follow the instructions for setting up the OpenCensus Service. You will need to be able to run the agent.
- Create a file named
config.yaml
with the following contents:
exporters:
prometheus:
namespace: "promdemo"
address: "localhost:8888"
const_labels: {
"vendor": "gotools"
}
receivers:
opencensus:
address: "localhost:55678"
- Run the OpenCensus Agent with the configuration file. The following command assumes that you are running from binary:
bin/ocagent_linux --config config.yaml
- If you see output similar to the following, the OpenCensus Agent is now running:
{"level":"info","ts":1574381470.1922305,"caller":"config/config.go:497","msg":"Metrics Exporter enabled","exporter":"prometheus"}
2019/11/21 18:11:11 Running OpenCensus Trace and Metrics receivers as a gRPC service at "localhost:55678"
2019/11/21 18:11:11 Running zPages on port 55679
- You can check the status of the agent using zPages at http://localhost:55679/debug/tracez.
Setting up Prometheus
- Follow the instructions for setting up Prometheus.
- Create a file named
prom.yaml
with the following contents:
scrape_configs:
- job_name: 'agent1'
scrape_interval: 5s
static_configs:
- targets: ['localhost:8888']
- Run Prometheus with the new configuration file. The following command assumes that you are running from pre-compiled binaries:
./prometheus --config.file=prom.yaml
- If you see output similar to the following, Prometheus is now running:
level=info ts=2019-11-22T00:27:13.772Z caller=main.go:626 msg="Server is ready to receive web requests."
- You can now access the Prometheus UI at http://localhost:9090.
- Check to make sure Prometheus is able to scrape metrics from OpenCensus at http://localhost:9090/targets. If the state for the endpoint
http://localhost:8888/metrics
is notUP
, make sure the OpenCensus agent is running. If you are running Prometheus using Docker, you may have to add--net="host"
to your run command so thatlocalhost
resolves correctly.
Exporting Metrics
- Clone the tools subrepository.
- Inside
internal
, create a file namedmain.go
with the following contents:
package main
import (
"context"
"fmt"
"math/rand"
"net/http"
"time"
"golang.org/x/tools/internal/telemetry/export"
"golang.org/x/tools/internal/telemetry/export/ocagent"
"golang.org/x/tools/internal/telemetry/metric"
"golang.org/x/tools/internal/telemetry/stats"
)
func main() {
exporter := 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{},
})
export.SetExporter(exporter)
ctx := context.TODO()
mLatency := stats.Float64("latency", "the latency in milliseconds", "ms")
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(mLatency)
for {
sleep := randomSleep()
time.Sleep(time.Duration(sleep) * time.Millisecond)
mLatency.Record(ctx, 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)
}
- Run the new file from within the tools repository:
go run internal/main.go
- After about 5 seconds, OpenCensus should start receiving your new metrics, which you can see at http://localhost:8888/metrics. This page will look similar to the following:
# 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:9090/graph?g0.range_input=5m&g0.stacked=1&g0.expr=rate(promdemo_latencyDistribution_bucket%5B5m%5D)&g0.tab=0.