Implementing OpenTelemetry in a Gin application

OpenTelemetry can be used to trace Gin applications for performance issues and bugs. OpenTelemetry is an open-source project under the Cloud Native Computing Foundation (CNCF) that aims to standardize the generation and collection of telemetry data. Telemetry data includes logs, metrics, and traces.

Gin is an HTTP web framework written in Go (Golang). It features a Martini-like API with much better performance -- up to 40 times faster.

If you need smashing performance, get yourself some Gin!

Gin framework has a very small footprint and great speed because it's built on HttpRouter, a lightweight, high-performance HTTP request router. HttpRouter and Gin use a radix tree to parse long and complicated route requests quickly.

OpenTelemetry middleware for Gin

In this tutorial, we will demonstrate how to use the OpenTelemetry Gin middleware to generate end-to-end tracing. We will also instrument GORM database client using OpenTelemetry libraries.

Before we demonstrate how to implement the OpenTelemetry libraries, let’s have a brief overview of OpenTelemetry.

What is OpenTelemetry?

OpenTelemetry is an open-source vendor-agnostic set of tools, APIs, and SDKs used to instrument applications to create and manage telemetry data(logs, metrics, and traces). It aims to make telemetry data(logs, metrics, and traces) a built-in feature of cloud-native software applications.

The telemetry data is then sent to an observability tool for storage and visualization.

OpenTelemetry libraries instrument application code to generate telemetry data that is then sent to an observability tool for storage & visualization

OpenTelemetry libraries instrument application code to generate telemetry data that is then sent to an observability tool for storage & visualization

OpenTelemetry is the bedrock for setting up an observability framework. It also provides you the freedom to choose a backend analysis tool of your choice.

OpenTelemetry and SigNoz

In this article, we will use SigNoz as our backend analysis tool. SigNoz is a full-stack open-source APM tool that can be used for storing and visualizing the telemetry data collected with OpenTelemetry. It is built natively on OpenTelemetry and works on the OTLP data formats.

SigNoz provides query and visualization capabilities for the end-user and comes with out-of-box charts for application metrics and traces.

Now let’s get down to how to implement OpenTelemetry Gin libraries and then visualize the collected data in SigNoz.

Running Gin application with OpenTelemetry

Step 1: Install SigNoz

First, you need to install SigNoz so that OpenTelemetry can send the data to it.

SigNoz can be installed on macOS or Linux computers in just three steps by using a simple installation script.

The install script automatically installs Docker Engine on Linux. However, on macOS, you must manually install Docker Engine before running the install script.

git clone -b main <https://github.com/SigNoz/signoz.git>
cd signoz/deploy/
./install.sh

You can visit our documentation for instructions on how to install SigNoz using Docker Swarm and Helm Charts.

When you are done installing SigNoz, you can access the UI at http://localhost:3301

SigNoz dashboard - It shows services from a sample app that comes bundled with the application

Step 2: Get sample Gin app in Golang

Sample Go application

It contains the sample boilerplate code that we will instrument.

If you want to follow the tutorial, then you should follow the without-instrumentation branch.

Step 3: Declare few variables for configuring OpenTelemetry

Declare the following variables in main.go which we will use to configure OpenTelemetry

var (
    serviceName  = os.Getenv("SERVICE_NAME")
    signozToken  = os.Getenv("SIGNOZ_ACCESS_TOKEN")
    collectorURL = os.Getenv("OTEL_EXPORTER_OTLP_ENDPOINT")
    insecure     = os.Getenv("INSECURE_MODE")
)

Step 4: Instrument your Gin application with OpenTelemetry

To configure your application to send data we will need a function to initialize OpenTelemetry. Add the following snippet of code in your main.go file.

import (
  .....

    "github.com/gin-gonic/gin"
    "go.opentelemetry.io/otel"
    "go.opentelemetry.io/otel/attribute"
    "go.opentelemetry.io/otel/exporters/otlp/otlptrace"
    "go.opentelemetry.io/otel/exporters/otlp/otlptrace/otlptracegrpc"

    "go.opentelemetry.io/otel/sdk/resource"
    sdktrace "go.opentelemetry.io/otel/sdk/trace"
)

func initTracer() func(context.Context) error {

    headers := map[string]string{
        "signoz-access-token": signozToken,
    }

    secureOption := otlptracegrpc.WithTLSCredentials(credentials.NewClientTLSFromCert(nil, ""))
    if len(insecure) > 0 {
        secureOption = otlptracegrpc.WithInsecure()
    }

    exporter, err := otlptrace.New(
        context.Background(),
        otlptracegrpc.NewClient(
            secureOption,
            otlptracegrpc.WithEndpoint(collectorURL),
            otlptracegrpc.WithHeaders(headers),
        ),
    )

    if err != nil {
        log.Fatal(err)
    }
    resources, err := resource.New(
        context.Background(),
        resource.WithAttributes(
            attribute.String("service.name", serviceName),
            attribute.String("library.language", "go"),
        ),
    )
    if err != nil {
        log.Printf("Could not set resources: ", err)
    }

    otel.SetTracerProvider(
        sdktrace.NewTracerProvider(
            sdktrace.WithSampler(sdktrace.AlwaysSample()),
            sdktrace.WithSpanProcessor(sdktrace.NewBatchSpanProcessor(exporter)),
            sdktrace.WithSyncer(exporter),
            sdktrace.WithResource(resources),
        ),
    )
    return exporter.Shutdown
}

Step 5: Initialize the tracer in main.go

Modify the main function to initialise the tracer in main.go

func main() {
    cleanup := initTracer()
    defer cleanup(context.Background())

    ......
}

Step 6: Add the OpenTelemetry Gin middleware

Configure Gin to use the middleware by adding the following lines in main.go.

import (
    ....
  "go.opentelemetry.io/contrib/instrumentation/github.com/gin-gonic/gin/otelgin"
)

func main() {
    ......
    r := gin.Default()
    r.Use(otelgin.Middleware(serviceName))
    ......
}

Step 7: Set environment variables and run your Gin application

Now that you have instrumented your Gin application with OpenTelemetry, you need to set some environment variables to send data to SigNoz backend:
SERVICE_NAME: goGinApp (you can name it whatever you want)

OTEL_EXPORTER_OTLP_ENDPOINT: localhost:4317

Since, we have installed SigNoz on our local machine, we use the above IP. If you install SigNoz on a different machine, you can update it with the relevant IP.

Hence, the final run command looks like this:

SERVICE_NAME=goGinApp INSECURE_MODE=true OTEL_EXPORTER_OTLP_ENDPOINT=localhost:4317 go run main.go

Step 8: Generate some data

In order to monitor your Gin application with SigNoz, you first need to generate some data.

• Create a book
  

  curl --location --request POST 'localhost:8091/books' \
  --header 'Content-Type: application/json' \
  --data-raw '{
      "title": "book 1",
      "author": "John Doe"
  }'
  

• Check the list of books by running the following Curl
  

  curl --location --request GET 'localhost:8091/books'
  

Step 9: Visualize the collected data in SigNoz

Access the signoz UI on http://localhost:3301/application

Go to Metrics → goGinApp → you will be able to see the dashboard

Your Gin application being monitored on the SigNoz dashboard

You can monitor application metrics like application latency, requests per second, error percentage, etc. with the Metrics tab of SigNoz.

You can monitor your Gin application metrics like application latency, requests per second, error percentage, etc.

OpenTelemetry captures tracing data from your Gin application as well. Tracing data can help you visualize how user requests perform across services in a multi-service application.

In the Traces tab of SigNoz, you can analyze the tracing data using filters based on tags, status codes, service names, operations, etc.

Use powerful filters to analyze your tracing data from the Gin application

You can also visualize your tracing data with the help of flamegraphs and Gantt charts.

Flamegraphs and Gantt charts on SigNoz dashboard

You can also monitor Gorm with OpenTelemetry libraries.

Monitoring GORM database client with OpenTelemetry

We have instrumented our Gin which will help us trace HTTP requests but we might want to trace the DB calls as well.

OpenTelemetry provides an otelgorm plugin to monitor GORM database client.

You can follow the below steps to instrument your GORM database client with OpenTelemetry.

Step 1: Initialise GORM to use OpenTelemetry by updating the models/setup.go

func ConnectDatabase() {
    .....
    DB = database
    if err := DB.Use(otelgorm.NewPlugin()); err != nil {
        panic(err)
    }
}  

Step 2: Update all the database calls to use the request context by modifying controllers/books.go

models.DB will be changed to models.DB.WithContext(c.Request.Context())

func FindBooks(c *gin.Context) {
    .....
    models.DB.WithContext(c.Request.Context()).Find(&books)
    .....
}

The above change should be done for all the DB calls.

Now run your application and execute the curl requests again. You will be able to see DB traces as well.

You can also monitor GORM database client using OpenTelemetry and SigNoz

Conclusion

Using OpenTelemetry libraries, you can instrument your Gin applications for end-to-end tracing. You can then use an open-source APM tool like SigNoz to ensure the smooth performance of your Gin applications.

OpenTelemetry is the future for setting up observability for cloud-native apps. It is backed by a huge community and covers a wide variety of technology and frameworks. Using OpenTelemetry, engineering teams can instrument polyglot and distributed applications with peace of mind.

SigNoz is an open-source observability tool that comes with a SaaS-like experience. You can try out SigNoz by visiting its GitHub repo 👇

If you face any issues while trying out SigNoz, you can reach out with your questions in #support channel 👇

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Further Reading

Monitor a Golang application using OpenTelemetry and SigNoz

Why is Distributed Tracing needed in microservices-based applications?