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OpenTelemetry for Node.js

Honeycomb has an OpenTelemetry Distribution for Node.js to instrument your applications and send trace data to Honeycomb. In addition to simplified OpenTelemetry initialization, the Honeycomb Distribution makes it easier to add multi-span attributes and configure sampling, as well as link directly to your traces in Honeycomb with local visualizations.

The primary purpose of Honeycomb’s Distribution for Node.js is to streamline configuration and to instrument as quickly and easily as possible. Under the hood, the Honeycomb Distribution uses OpenTelemetry for JavaScript, which means OpenTelemetry can be used with or without this Distribution. It may be unnecessary for advanced users or those already instrumented with OpenTelemetry to use the Distribution. Refer to how to use OpenTelemetry without the Honeycomb Distribution.

Automatic instrumentation is enabled by adding instrumentation packages. Manual instrumentation can be added using the OpenTelemetry API.

Requirements 

These instructions will explain how to set up automatic and manual instrumentation for a Node.js service. In order to follow along, you will need:

• Node.js version 14 or newer.
• A Node.js application.
• A Honeycomb API Key. You can find your API key in your Environment Settings. If you do not have an API key yet, sign up for a free Honeycomb account.

Examples 

There are several examples that configure applications to send OpenTelemetry data to Honeycomb.

Automatic Instrumentation 

Install Modules 

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

yarn add \
    @honeycombio/opentelemetry-node \
    @opentelemetry/auto-instrumentations-node

yarn add --dev ts-node

Initialize 

// tracing.ts
import { NodeSDK } from '@opentelemetry/sdk-node';
import { HoneycombSDK } from '@honeycombio/opentelemetry-node';
import { getNodeAutoInstrumentations } from '@opentelemetry/auto-instrumentations-node';

// uses HONEYCOMB_API_KEY and OTEL_SERVICE_NAME environment variables
const sdk: NodeSDK = new HoneycombSDK({
  instrumentations: [    
    getNodeAutoInstrumentations({
      // we recommend disabling fs autoinstrumentation since it can be noisy
      // and expensive during startup
      '@opentelemetry/instrumentation-fs': {
        enabled: false,
      },
    }),
  ],
});

sdk.start();

// tracing.js
'use strict';

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

// uses HONEYCOMB_API_KEY and OTEL_SERVICE_NAME environment variables
const sdk = new HoneycombSDK({
  instrumentations: [getNodeAutoInstrumentations()]
});

sdk.start()

Configure and Run 

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

ts-node -r ./tracing.ts APPLICATION_MAIN_FILE.ts

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

node -r ./tracing.js APPLICATION_MAIN_FILE.js

export HONEYCOMB_DATASET="your-dataset"

To set configuration in code, instead of environment variables, add to the HoneycombSDK:

const sdk = new HoneycombSDK({
  apiKey: "your-api-key",
  serviceName: "your-service-name",
  instrumentations: [getNodeAutoInstrumentations()]
})

Advanced Configuration 

This is the complete list of configuration options for the Honeycomb Distribution.

Using gRPC instead of HTTP/protobuf 

By default, the Honeycomb OpenTelemetry SDK uses the HTTP protocol (http/protobuf) to send telemetry data. To use gRPC instead of HTTP/protobuf, update the protocol to grpc:

export OTEL_EXPORTER_OTLP_PROTOCOL=grpc

Alternatively, if you prefer to configure this protocol in code, you can configure it with the HoneycombSDK:

const sdk = new HoneycombSDK({
  apiKey: "your-api-key",
  serviceName: "your-service-name",
  instrumentations: [getNodeAutoInstrumentations()],
  protocol: OtlpProtocolKind.Grpc,
})

const sdk = new HoneycombSDK({
  apiKey: "your-api-key",
  serviceName: "your-service-name",
  instrumentations: [getNodeAutoInstrumentations()],
  protocol: "grpc",
})

Adding Manual Instrumentation 

Auto-instrumentation is the easiest way to get started with instrumenting your code, but in order to get the most insight into your system, you should add manual instrumentation where appropriate. To do this, use the OpenTelemetry API to access the currently executing span and add attributes to it, and/or to create new spans.

Adding manual instrumentation requires the the OpenTelemetry API package. If not installed yet, use this command for installation:

npm install --save @opentelemetry/api

yarn add @opentelemetry/api

Adding Attributes to Spans 

It is often beneficial to add attributes to a currently executing span in a trace. For example, you may have an application or service that handles users, and you want to associate the user with the span when querying your service in Honeycomb. In order to do this, get the current span from the context and set an attribute with the user ID:

import opentelemetry from '@opentelemetry/api';

function handleUser(user: User) {
  let activeSpan = opentelemetry.trace.getActiveSpan();
  activeSpan.setAttribute("user.id", user.getId());
}

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

function handleUser(user) {
  let activeSpan = opentelemetry.trace.getActiveSpan();
  activeSpan.setAttribute("user.id", user.getId());
}

This will add a user.id field to the current span so that you can use the field in WHERE, GROUP BY or ORDER clauses in the Honeycomb query builder.

Initialize a Tracer 

To start manually tracing, you must initialize a tracer.

import opentelemetry from '@opentelemetry/api';

const tracer = opentelemetry.trace.getTracer("tracer.name.here");

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

const tracer = opentelemetry.trace.getTracer("tracer.name.here");

When you create a Tracer, OpenTelemetry requires you to give it a name as a string. This string is the only required parameter.

When traces are sent to Honeycomb, the name of the Tracer is turned into the library.name field, which can be used to show all spans created from a particular tracer.

In general, pick a name that matches the appropriate scope for your traces. 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 use the name that corresponds to that “layer”.

The library.name field is also used with traces created from instrumentation libraries.

You can then use this tracer to create custom spans.

Creating New Spans 

Auto-instrumentation can show the shape of requests to your system, but only you know the truly important parts. In order to get the full picture of what is happening, you will have to add manual instrumentation and create some custom spans. To do this, grab the tracer from the OpenTelemetry API:

import opentelemetry from '@opentelemetry/api';

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

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

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();
  });
}

Multi-Span Attributes 

Sometimes you want to add the same attribute to many spans within the same trace. These attributes may include variables calculated during your program, or other useful values for correlation or debugging purposes.

We will leverage the OpenTelemetry concept of baggage to add this attribute. Baggage allows you to add a key with a value as an attribute to every subsequent child span within the current application context.

import {
  Context,
  context,
  propagation,
} from '@opentelemetry/api';

tracer.startActiveSpan('main', (span) => {
  span.setAttribute('app.username', name); // add to current span

  // new context based on current, with key/values added to baggage
  const ctx: Context = propagation.setBaggage(
    context.active(),
    propagation.createBaggage({ 'app.username': { value: name } })
  );

  // within the new context, do some work and baggage will be
  // applied as attributes on child spans
  context.with(ctx, () => {
    tracer.startActiveSpan('childSpan', (childSpan) => {
      doTheWork();
      childSpan.end();
    });
  });

  span.end();
});

tracer.startActiveSpan('main', (span) => {
  span.setAttribute('app.username', name); // add to current span

  // new context based on current, with key/values added to baggage
  const ctx = propagation.setBaggage(
    context.active(),
    propagation.createBaggage({ 'app.username': { value: name } })
  );

  // within the new context, do some work and baggage will be
  // applied as attributes on child spans
  context.with(ctx, () => {
    tracer.startActiveSpan('childSpan', (childSpan) => {
      doTheWork();
      childSpan.end();
    });
  });

  span.end();
});

More on Manual Instrumentation 

The OpenTelemetry documentation for JavaScript has a comprehensive set of topics on manual instrumentation.

Sending Data to a Collector or Other Endpoint 

You can send data to an OpenTelemetry Collector instance or another endpoint by specifying a different endpoint:

export HONEYCOMB_API_ENDPOINT="http://<your-collector-endpoint>"

Alternatively, if you prefer to configure this in code, you can configure your endpoint with the HoneycombSDK:

const sdk = new HoneycombSDK({
  apiKey: "your-api-key",
  serviceName: "your-service-name",
  instrumentations: [getNodeAutoInstrumentations()],
  endpoint: "http://<your-collector-endpoint>",
})

The Honeycomb SDK will automatically append the endpoint with the appropriate traces-specific path of v1/traces.

Sampling 

Deterministic head sampling can be used with the Honeycomb SDK, with or without manual instrumentation.

The SDK will read these variables and expect an integer that represents the sample rate you would like to apply. For example, a value of 5 means that one out of every five traces will be sent to Honeycomb.

To add sampling to the SDK, set the SAMPLE_RATE environment variable:

export SAMPLE_RATE=5

To set the sample rate in code instead of an environment variable, add sampleRate to the HoneycombSDK:

const sdk = new HoneycombSDK({
  apiKey: "your-api-key",
  serviceName: "your-service-name",
  instrumentations: [getNodeAutoInstrumentations()],
  sampleRate: 5,
})

The value of your sample rate must be a positive integer.

If you have multiple services that communicate with each other, it is important that they have the same sampling configuration. Otherwise, each service might make a different sampling decision, resulting in incomplete or broken traces. You can sample using a standalone proxy as an alternative, like Honeycomb Refinery, or when you have more robust sampling needs.

Distributed Trace Propagation 

When a service calls another service, you want to ensure that the relevant trace information is propagated from one service to the other. This allows Honeycomb to connect the two services in a trace.

Distributed tracing enables you to trace and visualize interactions between multiple instrumented services. For example, your users may interact with a front-end API service, which talks to two internal APIs to fulfill their request. In order to have traces connect spans for all these services, it is necessary to propagate trace context between these services, usually by using an HTTP header.

Both the sending and receiving service must use the same propagation format, and both services must be configured to send data to the same Honeycomb environment.

Note: Any Baggage attributes that you set in your application will be attached to outgoing network requests as a header. If your service communicates to a third party API, do NOT put sensitive information in the Baggage attributes.

Trace context propagation is done by sending and parsing headers that conform to the W3C Trace Context specification.

By default, the Honeycomb’s OpenTelemetry Distribution for Node.js uses the W3C trace context format.

If you opt to use a different trace context specification than W3C, ensure that both the sending and receiving service are using the same propagation format, and that both services are configured to send data to the same Honeycomb environment.

Visualize Traces Locally 

Honeycomb’s OpenTelemetry Distribution for Node.js can create a link to a trace visualization in the Honeycomb UI for local traces. Local visualizations enables a faster feedback cycle when adding, modifying, or verifying instrumentation.

To enable local visualizations, set the HONEYCOMB_ENABLE_LOCAL_VISUALIZATIONS environment variable to true:

export HONEYCOMB_ENABLE_LOCAL_VISUALIZATIONS=true

Then, run your application:

node -r ./tracing.js APPLICATION_MAIN_FILE.js

To set the local visualizations option in code instead of an environment variable, add localVisualizations to the HoneycombSDK:

const sdk = new HoneycombSDK({
  apiKey: "your-api-key",
  serviceName: "your-service-name",
  instrumentations: [getNodeAutoInstrumentations()],
  localVisualizations: true,
})

The output displays the name of the root span and a link to Honeycomb that shows its trace. For example:

Trace for root-span-name
Honeycomb link: <link to Honeycomb trace>

Select the link to view the trace in detail within the Honeycomb UI.

Using OpenTelemetry Without the Honeycomb Distribution 

The Honeycomb Distribution reads specific variables and translates them to variables understood by the upstream OpenTelemetry SDK. For example, the distribution automatically configures exporters to send telemetry data to Honeycomb’s API api.honeycomb.io. Therefore, to send data to Honeycomb using OpenTelemetry without the Distribution, a different configuration is necessary to match expected variables.

Follow the directions below to instrument with OpenTelemetry for JavaScript using the Node SDK.

Install Packages 

npm install --save \
    @opentelemetry/sdk-node \
    @opentelemetry/exporter-trace-otlp-proto \
    @opentelemetry/auto-instrumentations-node

Initialize 

Create an initialization file, commonly known as the tracing.js file, and import it as the first step in your application lifecycle. Alternatively, include this initialization file with the -r or --require Node.js CLI option.

// tracing.js
'use strict';

const { NodeSDK } = require('@opentelemetry/sdk-node');
const { getNodeAutoInstrumentations } = require('@opentelemetry/auto-instrumentations-node');
const { OTLPTraceExporter } = require("@opentelemetry/exporter-trace-otlp-proto");

// The Trace Exporter exports the data to Honeycomb and uses
// environment variables for endpoint, service name, and API Key.
const traceExporter = new OTLPTraceExporter();

const sdk = new NodeSDK({
  traceExporter,
  instrumentations: [getNodeAutoInstrumentations()]
});

sdk.start()

Configure and Run 

Configure OpenTelemetry to send events to Honeycomb using environment variables.

The header x-honeycomb-team is your API key. Your service name will be used as the Service Dataset in Honeycomb, which is where data is stored. The service name is specified by OTEL_SERVICE_NAME.

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"

Run the Node.js app with the OpenTelemetry initialization file to generate data:

node -r ./tracing.js APPLICATION_MAIN_FILE.js

export OTEL_EXPORTER_OTLP_HEADERS="x-honeycomb-team=your-api-key,x-honeycomb-dataset=your-dataset"

Sampling Without the Honeycomb SDK 

Install the core OpenTelemetry package.

npm install --save @opentelemetry/core

Import the TraceIdRatioBasedSampler and add to the NodeSDK:

// tracing.js
const { TraceIdRatioBasedSampler } = require("@opentelemetry/core");

const sdk = new NodeSDK({
  resource: new Resource({
    [SemanticResourceAttributes.SERVICE_NAME]: "<YOUR_SERVICE_NAME>",
    SampleRate: 2,
  }),
  traceExporter,
  instrumentations: [getNodeAutoInstrumentations()],
  sampler: new TraceIdRatioBasedSampler(0.5),
});

You can configure the OpenTelemetry SDK to sample the data it generates. Honeycomb re-weights sampled data, so it is recommended that you set a resource attribute containing the sample rate.

In the example above, our goal is to keep approximately half (1/2) of the data volume. The resource attribute contains the denominator (2), while the OpenTelemetry sampler argument contains the decimal value (0.5).

Endpoint URLs for OTLP/HTTP 

When using the OTEL_EXPORTER_OTLP_ENDPOINT environment variable with an SDK and an HTTP exporter, the final path of the endpoint is actually modified by the SDK to represent the specific signal being sent.

For example, when exporting trace data, the endpoint is updated to append v1/traces. When exporting metrics data, the endpoint is updated to append v1/metrics. The same modification is not necessary for gRPC.

By setting OTEL_EXPORTER_OTLP_ENDPOINT to https://api.honeycomb.io, traces are sent to https://api.honeycomb.io/v1/traces and metrics to https://api.honeycomb.io/v1/metrics.

export OTEL_EXPORTER_OTLP_ENDPOINT=https://api.honeycomb.io

If the desired outcome is to send data to a different endpoint depending on the signal, use OTEL_EXPORTER_OTLP_<SIGNAL>_ENDPOINT instead of the more generic OTEL_EXPORTER_OTLP_ENDPOINT.

When using a signal-specific environment variable, these paths must be appended manually. Set OTEL_EXPORTER_OTLP_TRACES_ENDPOINT for traces, appending the endpoint with v1/traces, and OTEL_EXPORTER_OTLP_METRICS_ENDPOINT for metrics, appending the endpoint with v1/metrics.

Send both traces and metrics to Honeycomb using this method by setting the following variables:

export OTEL_EXPORTER_OTLP_TRACES_ENDPOINT=https://api.honeycomb.io/v1/traces
export OTEL_EXPORTER_OTLP_METRICS_ENDPOINT=https://api.honeycomb.io/v1/metrics

More details about endpoints and signals can be found in the OpenTelemetry Specification.

To configure the endpoint URL and API key in code instead of with environment variables, specify /v1/traces like so:

// Configure OTLPTraceExporter
const traceExporter =
  new OTLPTraceExporter({
    url: "https://api.honeycomb.io/v1/traces",
    headers: {
      "x-honeycomb-team": 'your-api-key',
    },
  })
);

Troubleshooting 

My Traces have Duplicate Spans 

If a This trace has multiple spans sharing the same non-null span ID error appears in Honeycomb, it is likely that your application is not instrumented correctly and is sending the same trace to Honeycomb more than once.

One possible misconfiguration is initializing OpenTelemetry more than once. Make sure to only initialize OpenTelemetry once when the application starts, and then use the Tracing API throughout the application runtime to add manual instrumentation.

Debug Mode 

To enable debugging when running the Honeycomb OpenTelemetry Node SDK, set the DEBUG environment variable to true:

export DEBUG=true

To set the debug option in code instead of an environment variable, add debug to the HoneycombSDK:

const sdk = new HoneycombSDK({
  apiKey: "your-api-key",
  serviceName: "your-service-name",
  instrumentations: [getNodeAutoInstrumentations()],
  sampleRate: 5,
  localVisualizations: true,
  debug: true,
})

When the debug setting is enabled, the Honeycomb SDK configures a DiagConsoleLogger that logs telemetry to the console with the log level of Debug.

The debug setting in the Honeycomb SDK will also output to the console the full options configuration, including but not limited to protocol, API Key, and endpoint.

If you are not using the Honeycomb SDK, or if you wish to change the logging level, you can still use the logger directly:

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

opentelemetry.diag.setLogger(
  new opentelemetry.DiagConsoleLogger(),
  opentelemetry.DiagLogLevel.WARN
);

If the logger still does not print enough, try increasing the log level by replacing WARN with DEBUG in opentelemetry.DiagLogLevel.WARN.

Keep in mind that printing to the console is not recommended for production and should only be used for debugging purposes.

OTLP Protobuf Definitions 

Honeycomb supports receiving telemetry data via OpenTelemetry’s native protocol, OTLP, over gRPC, HTTP/protobuf, and HTTP/JSON. The minimum supported versions of OTLP protobuf definitions are 0.7.0 for traces and metrics.

If the protobuf version in use by the SDK does not match a supported version by Honeycomb, a different version of the SDK may need to be used. If the SDK’s protobuf version is older than the minimum supported version, and telemetry is not appearing as expected in Honeycomb, upgrade the SDK to a version with the supported protobuf definitions. If using an added dependency on a proto library, ensure the version of protobuf definitions matches the supported version of the SDK.

Receiving 464 Errors 

You may receive a 464 error response from the Honeycomb API when sending telemetry using gRPC and HTTP1. The gRPC format depends on using HTTP2 and any request over HTTP1 will be rejected by the Honeycomb servers.

Missing .proto Files Error 

If your application builds using a bundler, like Webpack or ESBuild, or if your application uses TypeScript, you will see an error that says that a specific .proto file is not found:

opentelemetry/proto/collector/trace/v1/trace_service.proto not found in any of the include paths <directory>/protos

This error appears because the .proto files are not imported or required by the library that uses them, so bundlers do not know to include them in the final build. There are two ways to work around this error:

Copy the /protos Directory to the Correct Location 

Modify the bundler configuration to copy the /protos directory from the library to the same level as the build directory:

const CopyPlugin = require("copy-webpack-plugin");

module.exports = {
  ... other config ...
  plugins: [
    new CopyPlugin({
      patterns: [
        {
          from: "./node_modules/@opentelemetry/otlp-grpc-exporter-base/build/protos/**/*",
          to: "./protos"
        }
      ],
    }),
  ],
};

const { copy } = require('esbuild-plugin-copy')

require('esbuild').build({
  ... other config ...
  plugins: [
    copy({
      resolveFrom: 'cwd',
      assets: {
        from: ['./node_modules/@opentelemetry/otlp-grpc-exporter-base/build/protos/**/*'],
        to: ['./protos'],
        keepStructure: true
      },
    }),
  ],
}).catch(() => process.exit(1));

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