While the Honeycomb distributions of the OpenTelemetry SDKs are not yet deprecated, they are in maintenance.
Honeycomb provides the Honeycomb OpenTelemetry Distribution for Node.js to help you instrument your applications and send telemetry data to Honeycomb as quickly and easily as possible. Under the hood, the Honeycomb Distribution uses OpenTelemetry for JavaScript, so advanced users or those who have already instrumented their applications with OpenTelemetry do not need to use this Distribution.
The Honeycomb Distribution reads variables you provide and translates them to variables understood by the upstream OpenTelemetry SDK.
For example, the Honeycomb Distribution automatically configures exporters to send telemetry data to Honeycomb’s API (if you are using our US instance, api.honeycomb.io
, or if you are using our EU instance, api.eu1.honeycomb.io
).
If you want to send data to Honeycomb using OpenTelemetry without the Honeycomb Distribution, you will need to configure your implementation to match variables expected by OpenTelemetry.
In this guide, we explain how to set up automatic and custom, or manual, instrumentation for a service written in Node.js. If you prefer learning by example, we provide several examples of applications configured to send OpenTelemetry data to Honeycomb using the Honeycomb OpenTelemetry Distribution for Node.js.
Before you can set up instrumentation for your Node.js application, you will need to do a few things.
To complete the required steps, you will need:
To send data to Honeycomb, you’ll need to sign up for a free Honeycomb account and create a Honeycomb Ingest API Key. To get started, you can create a key that you expect to swap out when you deploy to production. Name it something helpful, perhaps noting that it’s a getting started key. Make note of your API key; for security reasons, you will not be able to see the key again, and you will need it later!
If you want to use an API key you previously stored in a secure location, you can also look up details for Honeycomb API Keys any time in your Environment Settings, and use them to retrieve keys from your storage location.
Automatic instrumentation is enabled by adding instrumentation packages. Add custom, or manual, instrumentation using the OpenTelemetry API.
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.
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:
yarn add \
@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.
If using TypeScript, install ts-node
to run the code:
yarn add --dev ts-node
Create an initialization file, commonly known as the tracing.ts
file:
// Example filename: tracing.ts
import { NodeSDK } from '@opentelemetry/sdk-node';
import { HoneycombSDK } from '@honeycombio/opentelemetry-node';
import { getNodeAutoInstrumentations } from '@opentelemetry/auto-instrumentations-node';
// Uses environment variables named HONEYCOMB_API_KEY and OTEL_SERVICE_NAME
const sdk: NodeSDK = 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();
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()
Use environment variables to configure the Honeycomb OpenTelemetry Node.js distribution package:
export HONEYCOMB_API_ENDPOINT="https://api.honeycomb.io:443" # US instance
#export HONEYCOMB_API_ENDPOINT="https://api.eu1.honeycomb.io:443" # EU instance
export OTEL_SERVICE_NAME="your-service-name"
export HONEYCOMB_API_KEY="your-api-key"
Variable | Description |
---|---|
HONEYCOMB_API_ENDPOINT |
Honeycomb endpoint to which you want to send your data. |
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. |
If you use Honeycomb Classic, you must also specify the Dataset using the x-honeycomb-dataset
header.
export OTEL_EXPORTER_OTLP_HEADERS="x-honeycomb-team=your-api-key,x-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()]
})
Explore all configuration options for the Honeycomb Distribution:
Environment Variable | Default Value | Description |
---|---|---|
HONEYCOMB_API_KEY |
None | [required – see note below] Your Honeycomb API key |
OTEL_SERVICE_NAME |
unknown_service |
[required – see note below] service.name attribute, where all trace data is sent |
HONEYCOMB_TRACES_APIKEY |
Value of HONEYCOMB_API_KEY |
Your Honeycomb API key for sending traces |
HONEYCOMB_METRICS_APIKEY |
Value of HONEYCOMB_API_KEY |
Your Honeycomb API key for sending metrics |
HONEYCOMB_METRICS_DATASET |
None | Honeycomb dataset where metrics will be sent |
HONEYCOMB_API_ENDPOINT |
api.honeycomb.io:443 (US instance)api.eu1.honeycomb.io:443 (EU instance) |
Honeycomb ingest endpoint |
HONEYCOMB_TRACES_ENDPOINT |
Value of HONEYCOMB_API_ENDPOINT |
Honeycomb ingest endpoint for traces (defaults to the value of HONEYCOMB_API_ENDPOINT ) |
HONEYCOMB_METRICS_ENDPOINT |
Value of HONEYCOMB_API_ENDPOINT |
Honeycomb ingest endpoint for metrics (defaults to the value of HONEYCOMB_API_ENDPOINT ) |
SAMPLE_RATE |
1 (retain all data) |
Sample rate for the deterministic sampler. Must be a positive integer. |
OTEL_METRICS_ENABLED |
false |
Enable metrics export (metrics dataset must be configured as well) |
HONEYCOMB_ENABLE_LOCAL_VISUALIZATIONS |
false |
Enable local visualizations |
DEBUG |
false |
Enable debug mode |
Run the Node.js app and include the initialization file you created:
ts-node -r ./tracing.ts YOUR_APPLICATION_NAME.ts
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.
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.
Automatic instrumentation is the easiest way to get started with instrumenting your code. To get additional insight into your system, you should also add custom, or manual, instrumentation where appropriate.
To learn more about custom, or manual, instrumentation, visit the comprehensive set of topics covered by Manual Instrumentation for JavaScript in OpenTelemetry’s documentation.
To start adding custom instrumentation, ensure that the OpenTelemetry API package exists as a direct dependency in your project. This package provides access to the high-level instrumentation APIs, which gives the ability to retrieve the current span to enrich with additional attributes, to create new spans, and to generate metrics.
npm install --save @opentelemetry/api
yarn add @opentelemetry/api
Adding attributes to a currently executing span in a trace can be useful. 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. 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 you can use the field in WHERE
, GROUP BY
or ORDER
clauses in the Honeycomb query builder.
To create spans, you need to 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.
Automatic instrumentation can show the shape of requests to your system, but only you know the truly important parts. To get the full picture of what is happening, you must add custom, or 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();
});
}
Sometimes you want to add the same attribute to many spans within the same trace. This attribute may include variables calculated during your program, or other useful values for correlation or debugging purposes.
To add this attribute, leverage the OpenTelemetry concept of baggage.
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('key', 'value'); // add to current span
// new context based on current, with key/values added to baggage
const ctx: Context = propagation.setBaggage(
context.active(),
propagation.createBaggage({ 'key': { value: 'value' } })
);
// 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('key', 'value'); // add to current span
// new context based on current, with key/values added to baggage
const ctx = propagation.setBaggage(
context.active(),
propagation.createBaggage({ 'key': { value: 'value' } })
);
// 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();
});
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.
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
.
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.
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.
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
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.
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
OTEL_EXPORTER_OTLP_<SIGNAL>_ENDPOINT
environment variable, you must append the endpoint with the appropriate signal path.
For example, if sending traces, append the endpoint with v1/traces
.
If sending metrics, append the endpoint with v1/metrics
.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",
})
To explore common issues when sending data, visit Common Issues with Sending Data in Honeycomb.