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GitHub - hertz-contrib/obs-opentelemetry: Opentelemetry for Hertz

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Opentelemetry for Hertz

• Out-of-the-box default opentelemetry provider
• Support setting via environment variables

• Support server and client hertz http tracing
• Support automatic transparent transmission of peer service through http headers

• Support hertz http metrics [R.E.D]
• Support service topology map metrics [Service Topology Map]
• Support go runtime metrics

• Extend hertz logger based on logrus
• Implement tracing auto associated logs

• Exporter
• SDK

import (
    // ...
    "github.com/hertz-contrib/obs-opentelemetry/provider"
    hertztracing "github.com/hertz-contrib/obs-opentelemetry/tracing"
)


func main()  {
    serviceName := "echo"

    p := provider.NewOpenTelemetryProvider(
        provider.WithServiceName(serviceName),
        provider.WithExportEndpoint("localhost:4317"),
        provider.WithInsecure(),
    )
    defer p.Shutdown(context.Background())

    tracer, cfg := hertztracing.NewServerTracer()
    h := server.Default(tracer)
    h.Use(hertztracing.ServerMiddleware(cfg))

    // ...

    h.Spin()
}

import (
    // ...
    "github.com/hertz-contrib/obs-opentelemetry/provider"
    hertztracing "github.com/hertz-contrib/obs-opentelemetry/tracing"
)

func main(){
    serviceName := "echo-client"

    p := provider.NewOpenTelemetryProvider(
        provider.WithServiceName(serviceName),
        provider.WithExportEndpoint("localhost:4317"),
        provider.WithInsecure(),
    )
    defer p.Shutdown(context.Background())

    c, _ := client.NewClient()
    c.Use(hertztracing.ClientMiddleware())

    // ...

}

import (
    hertzlogrus "github.com/hertz-contrib/obs-opentelemetry/logging/logrus"
)

func init()  {
    hlog.SetLogger(hertzlogrus.NewLogger())
    hlog.SetLevel(hlog.LevelDebug)

}

You need to configure the tracing middleware in the above example at the same time. If you do not need to report the tracing, you can refer to issue

h.GET("/ping", func(c context.Context, ctx *app.RequestContext) {
    req := &api.Request{Message: "my request"}
    resp, err := client.Echo(c, req)
    if err != nil {
        hlog.Errorf(err.Error())
    }
    hlog.CtxDebugf(c, "message received successfully: %s", req.Message)
    ctx.JSON(consts.StatusOK, resp)
})

{"level":"debug","msg":"message received successfully: my request","span_id":"445ef16484a171b8","time":"2022-07-04T06:27:35+08:00","trace_flags":"01","trace_id":"e9e579b32c9d6b0598f8f33d65689e06"}

Executable Example

Below is a table of HTTP server metric instruments.

Below is a table of HTTP client metric instruments.

The RED Method defines the three key metrics you should measure for every microservice in your architecture. We can calculate RED based on http.server.duration.

the number of requests, per second, you services are serving.

eg: QPS

sum(rate(http_server_request_count_total{}[5m])) by (service_name, http_method)

the number of failed requests per second.

eg: Error ratio

sum(rate(http_server_request_count_total{status_code="Error"}[5m])) by (service_name, http_method) / sum(rate(http_server_request_count_total{}[5m])) by (service_name, http_method)

distributions of the amount of time each request takes

eg: P99 Latency

histogram_quantile(0.99, sum(rate(http_server_duration_bucket{}[5m])) by (le, service_name, http_method))

The http.server.duration will record the peer service and the current service dimension. Based on this dimension, we can aggregate the service topology map

sum(rate(http_server_request_count_total{}[5m])) by (service_name, peer_service)

The sdk of OpenTelemetry is fully compatible with 1.X opentelemetry-go. see

maintained by: CoderPoet

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