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 not UP
, 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 that localhost
resolves correctly.
Exporting Metrics
- Clone the tools subrepository.
- Inside
internal
, create a file named main.go
with the following contents:
package main
import (
"context"
"fmt"
"math/rand"
"net/http"
"time"
"github.com/anz-bank/sysl/pkg/lspimpl/lspframework/telemetry/export"
"github.com/anz-bank/sysl/pkg/lspimpl/lspframework/telemetry/export/ocagent"
"github.com/anz-bank/sysl/pkg/lspimpl/lspframework/telemetry/metric"
"github.com/anz-bank/sysl/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.