Quick Start

Honeycomb is a fast analysis tool that helps you analyze your code’s performance and behavior to troubleshoot complex relationships within your system to solve problems faster.

To use Honeycomb, you first need to get your system’s observable external outputs–traces, metrics, and logs–into Honeycomb. These instructions will guide you through the process of sending trace data from an application in your local development environment to Honeycomb, customizing your instrumentation to get additional visibility into the inner workings of your business logic, and exploring your data in Honeycomb.

Note

Not ready to instrument and deploy an application, but want to see what Honeycomb can do for you? Check out this interactive demo that requires no setup, or learn what is possible from the guided tutorials in our Honeycomb sandbox!

Before You Begin

Before you run the code, you’ll need to do a few things.

Create a Honeycomb Account

Before you can use Honeycomb products, you’ll need to create a Honeycomb account. Signup is free!

Create a Honeycomb Team

Complete your account creation by giving us a team name. Honeycomb uses teams to organize groups of users, grant them access to data, and create a shared work history in Honeycomb.

Tip

We recommend using your company or organization name as your Honeycomb team name.

Get Your Honeycomb API Key

To send data to Honeycomb, you’ll need your Honeycomb API Key. Once you create your team, you will be able to view or copy your API key. Make note of it; you will need it later!

You can also find your Honeycomb API Key any time in your Environment Settings.

Send Telemetry Data to Honeycomb

Once you have your Honeycomb API key and have chosen an application, it’s time to send telemetry data to Honeycomb!

Note

This guide helps users who are new to observability get their trace data into Honeycomb using OpenTelemetry. If you already have an OpenTelemetry implementation and are switching to Honeycomb, read about OpenTelemetry Collector.

Choose Your Application

Choose a single application or service that will send data to Honeycomb. To successfully complete this Quick Start, you should have access to modify your application’s source code. To test the application when you are finished, you must be able to run your application or service in a development environment.

Tip

Don’t have access to an application? Follow along using one of our example applications!

Add Automatic Instrumentation to Your Code

The quickest way to start seeing your trace data in Honeycomb is to use OpenTelemetry, an open-source collection of tools, APIs, and SDKs, to automatically inject instrumentation code into your application without requiring explicit changes to your codebase.

Note

Automatic instrumentation works slightly differently within each language, but the general idea is that it attaches hooks into popular tools and frameworks and “watches” for certain functions to be called. When they’re called, the instrumentation automatically starts and completes trace spans on behalf of your application.

When you add automatic instrumentation to your code, OpenTelemetry will inject spans, which represent units of work or operations within your application that you want to capture and analyze for observability purposes.

JavaScript

Note

This Quick Start uses the npm dependency manager. For instructions with yarn or if using TypeScript, read our OpenTelemetry Node.js documentation.

Install Dependencies

Open your terminal, navigate to the location of your project on your drive, and install OpenTelemetry’s automatic instrumentation meta package and Honeycomb’s OpenTelemetry Node.js distribution package:

npm install --save \
    @opentelemetry/auto-instrumentations-node \
    @honeycombio/opentelemetry-node

Module	Description
`auto-instrumentations-node`	OpenTelemetry’s meta package that provides a way to add automatic instrumentation to any Node application to capture telemetry data from a number of popular libraries and frameworks, like `express`, `dns`, `http`, and more.
`opentelemetry-node`	Honeycomb’s Node.js distribution package that streamlines configuration and allows you to instrument as quickly and easily as possible.

Alternatively, install individual instrumentation packages.

Initialize

Create an initialization file, commonly known as the tracing.js file:

// Example filename: tracing.js
'use strict';

const { HoneycombSDK } = require('@honeycombio/opentelemetry-node');
const {
  getNodeAutoInstrumentations,
} = require('@opentelemetry/auto-instrumentations-node');

// Uses environment variables named HONEYCOMB_API_KEY and OTEL_SERVICE_NAME
const sdk = new HoneycombSDK({
  instrumentations: [getNodeAutoInstrumentations({
      // We recommend disabling fs automatic instrumentation because
      // it can be noisy and expensive during startup
      '@opentelemetry/instrumentation-fs': {
        enabled: false,
      },
  })]
});

sdk.start()

Configure the Honeycomb Distro

Use environment variables to configure the Honeycomb OpenTelemetry Node.js distribution package:

export OTEL_SERVICE_NAME="your-service-name"
export HONEYCOMB_API_KEY="your-api-key"

Variable	Description
`OTEL_SERVICE_NAME`	Service name. When you send data, Honeycomb creates a dataset in which to store your data and uses this as the name. Can be any string.
`HONEYCOMB_API_KEY`	Your API Key generated in Honeycomb. Learn how to find your Honeycomb API Key.

Run Your Application

Run the Node.js app and include the initialization file you created:

node -r ./tracing.js YOUR_APPLICATION_NAME.js

Be sure to replace YOUR_APPLICATION_NAME with the name of your application’s main file.

Alternatively, you can import the initialization file as the first step in your application lifecycle.

In Honeycomb’s UI, you should now see your application’s incoming requests and outgoing HTTP calls generate traces.

Note

This Quick Start uses the pip package manager. For instructions with poetry, read our OpenTelemetry Python documentation.

Install Packages

Install packages:

Install Honeycomb’s OpenTelemetry Python distribution package.

python -m pip install honeycomb-opentelemetry --pre

Install OpenTelemetry’s automatic instrumentation libraries for the packages used by your Python application. We recommend that you use the opentelemetry-bootstrap tool that comes with the OpenTelemetry Python SDK to scan your application packages and generate the list of available libraries. By default, the tool prints out the instrumentation libraries that are available, which you can add to your requirements.txt file:

opentelemetry-bootstrap >> requirements.txt
pip install -r requirements.txt

If you do not use a requirements.txt file, you can install the libraries directly in your current environment:

opentelemetry-bootstrap --action=install

Configure the Honeycomb Distro

Use environment variables to configure the Honeycomb OpenTelemetry Python distribution package:

export OTEL_SERVICE_NAME="your-service-name"
export HONEYCOMB_API_KEY="your-api-key"

Variable	Description
`OTEL_SERVICE_NAME`	Service name. When you send data, Honeycomb creates a dataset in which to store your data and uses this as the name. Can be any string.
`HONEYCOMB_API_KEY`	Your API Key generated in Honeycomb. Learn how to find your Honeycomb API Key.

Run Your Application

Run your Python application using the OpenTelemetry Python automatic instrumentation tool opentelemetry-instrument, which configures the OpenTelemetry SDK:

opentelemetry-instrument python YOUR_APPLICATION_NAME.py

Be sure to replace YOUR_APPLICATION_NAME with the name of your application’s main file.

In Honeycomb’s UI, you should now see your application’s incoming requests and outgoing HTTP calls generate traces.

Acquire Dependencies

The automatic instrumentation agent for Honeycomb OpenTelemetry Java will automatically generate trace data from your application. The agent is packaged as a JAR file and is run alongside your app.

In order to use the automatic instrumentation agent, you must first download it:

curl -LO https://github.com/honeycombio/honeycomb-opentelemetry-java/releases/download/v1.5.2/honeycomb-opentelemetry-javaagent-1.5.2.jar

Configure the Honeycomb Distro

Choose from one of the following configuration options:

Use environment variables:

SERVICE_NAME=my-favorite-service
HONEYCOMB_API_KEY=my-api-key
HONEYCOMB_METRICS_DATASET=my-metrics

Or, use system properties:

sample.rate=2
service.name=my-favorite-service
honeycomb.api.key=my-api-key
honeycomb.metrics.dataset=my-metrics

and set an environment variable with a path to your properties file:

HONEYCOMB_CONFIG_FILE=/path/to/properties/file

Run Your Application

Run your application with the automatic instrumentation agent as a sidecar:

java -javaagent:honeycomb-opentelemetry-javaagent-1.5.2.jar -jar /path/to/myapp.jar

You can also include configuration values with an invocation of your application:

java \
-Dhoneycomb.config.file=/path/to/properties/file \
-javaagent:honeycomb-opentelemetry-javaagent-1.5.2.jar -jar /path/to/myapp.jar

For more configuration options, read Honeycomb OpenTelemetry Distribution for Java.

In Honeycomb’s UI, you should now see your application’s incoming requests and outgoing HTTP calls generate traces.

Note

This Quick Start uses ASP.NET Core. For other .NET configuration options, read our OpenTelemetry .NET documentation on programmatic and ASP.NET (.NET Framework) configuration.

Acquire Dependencies

Install the Honeycomb.OpenTelemetry NuGet package.

For example, with the .NET CLI, use:

dotnet add package Honeycomb.OpenTelemetry
dotnet add package OpenTelemetry.Extensions.Hosting
dotnet add package Honeycomb.OpenTelemetry.CommonInstrumentations --prerelease

Initialize

Initialize your ASP.NET Core app to use the Honeycomb OpenTelemetry Distribution for .NET:

In your appsettings.json file, add a Honeycomb section:

{
  "Honeycomb": {
    "ServiceName": "my-app",
    "ApiKey": "{apikey}"
  }
}

Get HoneycombOptions from configuration and use these options to configure the OpenTelemetry SDK in your application startup code:

using OpenTelemetry.Trace;

var builder = WebApplication.CreateBuilder(args);
builder.Services.AddControllers();

var honeycombOptions = builder.Configuration.GetHoneycombOptions();

// Set up OpenTelemetry Tracing
builder.Services.AddOpenTelemetry().WithTracing(otelBuilder =>
{
    otelBuilder
        .AddHoneycomb(honeycombOptions)
        .AddCommonInstrumentations();
});

// Register a Tracer, so it can be injected into other components (for example, Controllers)
builder.Services.AddSingleton(TracerProvider.Default.GetTracer(honeycombOptions.ServiceName));

var app = builder.Build();

app.MapGet("/", (Tracer tracer) =>
{
    using var span = tracer.StartActiveSpan("app.manual-span");
    span.SetAttribute("app.manual-span.message", "Adding custom spans is also super easy!");
});

await app.RunAsync();

Run

Run your application. You will see the incoming requests and outgoing HTTP calls generate traces.

dotnet run

To see all configuration options and ways to run your application, read Honeycomb OpenTelemetry Distribution for .NET.

In Honeycomb’s UI, you should now see your application’s incoming requests and outgoing HTTP calls generate traces.

Acquire Dependencies

Install the Honeycomb OpenTelemetry Go Distribution package:

go get github.com/honeycombio/honeycomb-opentelemetry-go \
  go.opentelemetry.io/contrib/instrumentation/net/http/otelhttp

Initialize

Prepare your application to send spans to Honeycomb.

Open or create a file called main.go:

package main

import (
    "fmt"
    "log"
    "net/http"

    "github.com/honeycombio/honeycomb-opentelemetry-go"
    "github.com/honeycombio/otel-config-go/otelconfig"

    "go.opentelemetry.io/contrib/instrumentation/net/http/otelhttp"
)

// Implement an HTTP Handler function to be instrumented
func httpHandler(w http.ResponseWriter, r *http.Request) {
    fmt.Fprintf(w, "Hello, World")
}

// Wrap the HTTP handler function with OTel HTTP instrumentation
func wrapHandler() {
    handler := http.HandlerFunc(httpHandler)
    wrappedHandler := otelhttp.NewHandler(handler, "hello")
    http.Handle("/hello", wrappedHandler)
}

func main() {
    // Enable multi-span attributes
    bsp := honeycomb.NewBaggageSpanProcessor()

    // Use the Honeycomb distro to set up the OpenTelemetry SDK
    otelShutdown, err := otelconfig.ConfigureOpenTelemetry(
        otelconfig.WithSpanProcessor(bsp),
    )
    if err != nil {
        log.Fatalf("error setting up OTel SDK - %e", err)
    }
    defer otelShutdown()

    // Initialize HTTP handler instrumentation
    wrapHandler()
    log.Fatal(http.ListenAndServe(":3030", nil))
}

Configure the Honeycomb Distro

Use environment variables to configure the Honeycomb OpenTelemetry Go distribution package:

export OTEL_SERVICE_NAME="your-service-name"
export HONEYCOMB_API_KEY="your-api-key"

Variable	Description
`OTEL_SERVICE_NAME`	Service name. When you send data, Honeycomb creates a dataset in which to store your data and uses this as the name. Can be any string.
`HONEYCOMB_API_KEY`	Your API Key generated in Honeycomb. Learn how to find your Honeycomb API Key.

Run Your Application

Run your application:

go run YOUR_APPLICATION_NAME.go

Be sure to replace YOUR_APPLICATION_NAME with the name of your application’s main file.

In Honeycomb’s UI, you should now see your application’s incoming requests and outgoing HTTP calls generate traces.

Acquire Dependencies

Add these gems to your Gemfile:

gem 'opentelemetry-sdk'
gem 'opentelemetry-exporter-otlp'
gem 'opentelemetry-instrumentation-all'

Including opentelemetry-instrumentation-all provides instrumentation for Rails, Sinatra, several HTTP libraries, and more.

Initialize

Initialize OpenTelemetry early in your application lifecycle. For Rails applications, we recommend that you use a Rails initializer. For other Ruby services, initialize as early as possible in the startup process.

# config/initializers/opentelemetry.rb
require 'opentelemetry/sdk'
require 'opentelemetry/exporter/otlp'
require 'opentelemetry/instrumentation/all'

OpenTelemetry::SDK.configure do |c|
    c.use_all() # enables all instrumentation!
end

Configure the Honeycomb Distro

Use environment variables to configure OpenTelemetry to send events to Honeycomb:

export OTEL_EXPORTER_OTLP_ENDPOINT="https://api.honeycomb.io"
export OTEL_EXPORTER_OTLP_HEADERS="x-honeycomb-team=your-api-key"
export OTEL_SERVICE_NAME="your-service-name"

Variable	Description
`OTEL_EXPORTER_OTLP_ENDPOINT`	Base endpoint to which you want to send your telemetry data.
`OTEL_EXPORTER_OTLP_HEADERS`	List of headers to apply to all outgoing telemetry data. Place your API Key generated in Honeycomb in the `x-honeycomb-team` header. Learn how to find your Honeycomb API Key.
`OTEL_SERVICE_NAME`	Service name. When you send data, Honeycomb creates a dataset in which to store your data and uses this as the name. Can be any string.

Run Your Application

Run your Ruby application.

In Honeycomb’s UI, you should now see your application’s incoming requests and outgoing HTTP calls generate traces.

If your preferred language is not covered here, you can find relevant instrumentation information in the OpenTelemetry community documentation.

Tip

For Rust, we recommend you use the opentelemetry and opentelemetry-otlp crates to send data to Honeycomb over OTLP.

For any required configuration values, see Using the Honeycomb OpenTelemetry Endpoint.

Generate Automated Data

Now that you have added automatic instrumentation to your application and have it running in your development environment, interact with your application by making a few requests. Making requests to your service will generate telemetry data and send it to Honeycomb where it will appear in the Honeycomb UI within seconds.

Tip

If you have made several service requests in your development environment and after several minutes, you still do not see any data, reach out for help in our Pollinators Community Slack.

View an Example Trace

Before you move on, take a look at the data that you have generated using automatic instrumentation by viewing an example trace, which is a visual diagram that represents the complete journey of a request or transaction as it traverses a distributed system.

Traces provide a way to visualize and understand the flow of execution and the interactions between various components involved in serving a request. They can help you find the source of errors in a system, identify the slowest processes, and break down the user experience in great detail.

While Honeycomb helps you analyze all of your outputs, where we particularly shine is when working with traces to give you a visual representation of where requests spend time in your system. In this example, we want to see a count of events, an average latency for those events, and a heatmap of latency.

To see your trace:

Log in to Honeycomb using your Honeycomb account.
From the left sidebar, navigate to Query.
In the VISUALIZE clause, add HEATMAP(duration_ms)
Select Run Query.
In the heatmap results, click on a dot to get a trace.

We generated the following examples after adding automatic instrumentation to a simple greeting service application written in Node.js. You can see the code in our GitHub repository.

Here’s our example heatmap:

Heatmap for our automatically-instrumented example application, showing three dots, each of which represents a trace

And here is our example trace:

First trace for our automatically-instrumented example application

In this trace, you can see:

the spans within the trace
how long each span took
which spans contain errors (none, in this example)

All of this is useful information, but more information will allow us to dig even more deeply. To do this, we need to enhance our automatic instrumentation by customizing it.

Customize Your Instrumentation

To get the most insight into your system, you should customize your instrumentation. For example, if you have an application or service that handles users, you probably want to associate the user with the span created by automatic instrumentation. Additionally, because automatic instrumentation doesn’t know your business logic–it only knows about frameworks and languages–you’ll want to explicitly add instrumentation code surrounding your business logic.

Tip

When deciding what to instrument, we recommend thinking of this as an exploratory process and part of the core analysis loop. You don’t need to add your custom instrumentation to everything all at once. Consider your top interests and instrument them, then analyze your results and add additional code as necessary.

Install Dependencies

Before you can customize your instrumentation, you must install any required dependencies. These will vary depending on your chosen programming language.

JavaScript

To continue, you must install OpenTelemetry’s API package. Once you have installed the API package, you can use it to add instrumentation for everything you care about in your application.

Note

This Quick Start uses the npm dependency manager. For instructions with yarn or if using TypeScript, read our OpenTelemetry Node.js documentation.

npm install --save @opentelemetry/api

To continue, you must install OpenTelemetry’s API package. Once you have installed the API package, you can use it to add instrumentation for everything you care about in your application.

Note

This Quick Start uses the pip package manager. For instructions with poetry, read our OpenTelemetry Python documentation.

python -m pip install opentelemetry-api

To continue, you must install Honeycomb’s OpenTelemetry SDK, which provides access to the OpenTelemetry APIs. Once you have installed the SDK, you can use it to add instrumentation for everything you care about in your application.

Note

This Quick Start uses the Gradle build tool. For instructions with Maven, read our OpenTelemetry Java documentation.

dependencies {
  implementation('io.honeycomb:honeycomb-opentelemetry-sdk:1.5.2')
}

Note

This Quick Start uses ASP.NET Core. For other .NET configuration options, read our OpenTelemetry .NET documentation on programmatic and ASP.NET (.NET Framework) configuration.

Because you already installed all necessary dependencies when implementing automatic instrumentation, you can skip this step.

If your preferred language is not covered here, you can find relevant instrumentation information in the OpenTelemetry community documentation.

Add Contextual Information to Existing Spans

To enhance the understanding of your telemetry data, you can attach contextual information to the spans generated by automatic instrumentation. Contextual information includes attributes, which are arbitrary key-value pairs that you can add to provide additional data about the span, such as a specific database query being executed or an HTTP request being made.

In this example, you will enhance your automatic instrumentation by associating a span created automatically when a user queries your service with the user’s ID, which will be saved in an attribute called user.id. Once this attribute is added, you will be able to use it to query your data in Honeycomb.

JavaScript

const opentelemetry = require("@opentelemetry/api");

//...

function handleUser(user) {
  // Gets the active span from the context
  let activeSpan = opentelemetry.trace.getActiveSpan();
  // Sets an attribute that contains the user ID
  activeSpan.setAttribute("user.id", user.getId());
}

from opentelemetry import trace

#...

# Gets the active span from the context
span = trace.get_current_span()
# Sets an attribute that contains the user ID
span.set_attribute("user.id", user.id())

import io.opentelemetry.api.trace.Span;

//...

// Gets the active span from the context
Span span = Span.current();
// Sets an attribute that contains the user ID
span.setAttribute("user.id", user.getId());

using OpenTelemetry.Trace;

//...

// Gets the active span from the context
var currentSpan = Tracer.CurrentSpan;
// Sets an attribute that contains the user ID
currentSpan.SetAttribute("user.id", User.GetUserId())

This example assumes you are writing a web application with the net/http package.

import (
  // ...
  "go.opentelemetry.io/otel/attribute"
  "go.opentelemetry.io/otel/trace"
  // ...
)

// ...
handler := func(w http.ResponseWriter, r *http.Request) {
  // Gets the currently logged in user
  user := someServiceCall()
  ctx := r.Context()
  // Gets the active span from the context
  span := trace.SpanFromContext(ctx)
  // Sets an attribute that contains the user ID
  span.SetAttributes(attribute.Int("user.id", user.getID()))
}
// ...

# Somewhere within the service, the SDK has been required and configured
require 'opentelemetry/sdk'
OpenTelemetry::SDK.configure do ... end

# ...

def handle_user(user)
  # Gets the active span from the context
  current_span = OpenTelemetry::Trace.current_span
  # Sets an attribute that contains the user ID
  current_span.set_attribute("user.id", user.id)
end

If your preferred language is not covered here, you can find relevant instrumentation information in the OpenTelemetry community documentation.

Create Custom Spans

To further enhance the understanding of your telemetry data, you’ll want to generate custom spans. Automatic instrumentation can show the shape of requests to your system, but only you know the truly important parts. To get the full picture, you should manually add spans to areas of interest. In OpenTelemetry, this is called manual instrumentation.

Initialize a Tracer

Before you can create a custom span, you must initialize a tracer. In OpenTelemetry, a tracer is used to instrument your code and generate telemetry data. The tracer provides the interface for capturing spans, which represent individual units of work in your code.

JavaScript

const opentelemetry = require("@opentelemetry/api");

// Creates the tracer and names it.
// Choose a name that matches the appropriate scope for your trace. 
// For example, if you have one tracer for each service, then use 
// the service name. If you have multiple tracers that live in 
// different "layers" of your application, then user the name that 
// corresponds to the appropriate "layer".
const tracer = opentelemetry.trace.getTracer("your.tracer.name");

from opentelemetry import trace

#...

# Creates the tracer and names it.
# Choose a name that matches the appropriate scope for your trace. 
# For example, if you have one tracer for each service, then use 
# the service name. If you have multiple tracers that live in 
# different "layers" of your application, then user the name that 
# corresponds to the appropriate "layer".
tracer = trace.get_tracer("tracer.name.here")

import io.opentelemetry.api;

//...

// Creates the tracer and names it.
// Choose a name that matches the appropriate scope for your trace. 
// For example, if you have one tracer for each service, then use 
// the service name. If you have multiple tracers that live in 
// different "layers" of your application, then user the name that 
// corresponds to the appropriate "layer".
Tracer tracer = openTelemetry.getTracer("tracer.name.here");

using OpenTelemetry.Trace;

//...

// Creates the tracer and names it.
// Choose a name that matches the appropriate scope for your trace. 
// For example, if you have one tracer for each service, then use 
// the service name. If you have multiple tracers that live in 
// different "layers" of your application, then user the name that 
// corresponds to the appropriate "layer".
var tracer = TracerProvider.Default.GetTracer("tracer.name.here");

Then, inject the Tracer instance with ASP.NET Core dependency injection or manage its lifecycle manually.

import (
  // ...
  "go.opentelemetry.io/otel"
  // ...
)

//...

// Creates the tracer and names it.
// Choose a name that matches the appropriate scope for your trace. 
// For example, if you have one tracer for each service, then use 
// the service name. If you have multiple tracers that live in 
// different "layers" of your application, then user the name that 
// corresponds to the appropriate "layer".
tracer := otel.Tracer("tracer.name.here")

require "opentelemetry/sdk"

#...

# Creates the tracer and names it.
# Choose a name that matches the appropriate scope for your trace. 
# For example, if you have one tracer for each service, then use 
# the service name. If you have multiple tracers that live in 
# different "layers" of your application, then user the name that 
# corresponds to the appropriate "layer".
tracer = OpenTelemetry.tracer_provider.tracer("tracer.name.here")

If your preferred language is not covered here, you can find relevant instrumentation information in the OpenTelemetry community documentation.

Create Your Span

Get the tracer from the OpenTelemetry API and use it to create your custom span.

JavaScript

const opentelemetry = require("@opentelemetry/api");

const tracer = opentelemetry.trace.getTracer("my-service-tracer");

function runQuery() {
  tracer.startActiveSpan("expensive-query", (span) => {
    // Do cool stuff
    span.end();
  });
}

from opentelemetry import trace

tracer = trace.get_tracer("tracer.name.here")
with tracer.start_as_current_span("some-long-running-handler"):
    # Prepare to auth

    with tracer.start_as_current_span("what-it-takes-to-authorize-handling"):
        # Perform auth

    # Do the authorized long-running handling of cool stuff

import io.opentelemetry.api.GlobalOpenTelemetry;
import io.opentelemetry.api.trace.Span;
import io.opentelemetry.api.trace.Tracer;

...

Tracer tracer = GlobalOpenTelemetry.getTracer("my-service");
Span span = tracer.spanBuilder("expensive-query").startSpan();

// ... Do cool stuff

span.end();

using OpenTelemetry.Trace;

//...

using var span = TracerProvider.Default.GetTracer("my-service").StartActiveSpan("expensive-query")
// ... Do cool stuff

import (
  // ...
  "go.opentelemetry.io/otel"
  // ...
)

// ...
tracer := otel.Tracer("my-app") // If not already in scope
ctx, span := tracer.Start(ctx, "expensive-operation")
defer span.End()
// ...

# Somewhere within the service, the SDK has been required and configured
require 'opentelemetry/sdk'
OpenTelemetry::SDK.configure do ... end

# ...

def run_query
  tracer = OpenTelemetry.tracer_provider.tracer('my-tracer')
  tracer.in_span("expensive-query") do |span|
    # ... Do cool stuff
    span.set_attribute('coolness', 100)
  end
end

If your preferred language is not covered here, you can find relevant instrumentation information in the OpenTelemetry community documentation.

Analyze Your Results

Now that you have customized your instrumentation, take a look at your trace again.

We generated the following examples after adding additional custom spans (a note to indicate where we are in the process, plus person name and message) to our simple greeting service application written in Node.js. You can see the code in our GitHub repository.

Here’s our example trace:

Trace showing custom spans implemented in our example application

In this trace, you can see the additional spans:

note indicating we are preparing the greeting
call name
call message

If you look in the Fields section of the UI, you would also see new attributes, such as the name of the person and the message that was sent.

What’s Next?

Excellent work! If you made it this far, you should now have telemetry data from your application flowing into Honeycomb. You can deploy to production and start gaining new insights on real traffic!

But there is so much more to explore! To learn more about what you can do with Honeycomb, check out:

Exploring Your Data: See a quick run-through of the different ways you can explore your data in Honeycomb.
Honeycomb’s Sandbox: Explore common scenarios with real data.
DevRel Office Hours: Join in on observability talk with world-class experts.
Integrations: Learn about other types of data you can explore with Honeycomb.

Honeycomb.io Documentation

Quick Start

Before You Begin

Create a Honeycomb Account

Create a Honeycomb Team

Get Your Honeycomb API Key

Send Telemetry Data to Honeycomb

Choose Your Application

Add Automatic Instrumentation to Your Code

Install Dependencies

Initialize

Configure the Honeycomb Distro

Run Your Application

Install Packages

Configure the Honeycomb Distro

Run Your Application

Acquire Dependencies

Configure the Honeycomb Distro

Run Your Application

Acquire Dependencies

Initialize

Run

Acquire Dependencies

Initialize

Configure the Honeycomb Distro

Run Your Application

Acquire Dependencies

Initialize

Configure the Honeycomb Distro

Run Your Application

Generate Automated Data

View an Example Trace

Customize Your Instrumentation

Install Dependencies

Add Contextual Information to Existing Spans

Create Custom Spans

Initialize a Tracer

Create Your Span

Analyze Your Results

What’s Next?