Send Node.js logs and traces to Bronto via OpenTelemetry

This page covers instrumenting a Node.js application with the OpenTelemetry SDK to send logs and traces to Bronto over OTLP/HTTP via a local OTel Collector. Both signals are co-equal: logs are bridged via a Winston or Pino transport — no log statement changes needed — and traces are emitted via a tracer provider.

If you don’t have a Collector and want to export directly from your application to Bronto, see Direct export to Bronto at the bottom of this page.

Prerequisites

Node.js 14 or later
npm or yarn
A running OTel Collector configured to forward logs and traces to Bronto — see Connect Open Telemetry to Bronto
OpenTelemetry JavaScript SDK documentation

Install dependencies

npm install \
  @opentelemetry/api \
  @opentelemetry/sdk-logs \
  @opentelemetry/exporter-logs-otlp-http \
  @opentelemetry/resources \
  @opentelemetry/semantic-conventions \
  @opentelemetry/winston-transport \
  winston

npm install \
  @opentelemetry/api \
  @opentelemetry/sdk-logs \
  @opentelemetry/exporter-logs-otlp-http \
  @opentelemetry/resources \
  @opentelemetry/semantic-conventions \
  pino

Package	Purpose
`@opentelemetry/sdk-logs`	SDK — `LoggerProvider`, processors
`@opentelemetry/exporter-logs-otlp-http`	OTLP/HTTP exporter
`@opentelemetry/resources`	Resource builder
`@opentelemetry/semantic-conventions`	Standard attribute key constants
`@opentelemetry/winston-transport`	Bridges Winston into OTel

Configure the OTel logger provider

Set up a LoggerProvider with an OTLP exporter. This is the same regardless of which logger you use.

otel-logging.js

const { LoggerProvider, BatchLogRecordProcessor } = require('@opentelemetry/sdk-logs');
const { OTLPLogExporter } = require('@opentelemetry/exporter-logs-otlp-http');
const { Resource } = require('@opentelemetry/resources');
const { SEMRESATTRS_SERVICE_NAME, SEMRESATTRS_SERVICE_NAMESPACE } = require('@opentelemetry/semantic-conventions');

const resource = new Resource({
  [SEMRESATTRS_SERVICE_NAME]: 'my-service',
  [SEMRESATTRS_SERVICE_NAMESPACE]: 'my-team',
  'deployment.environment': 'production',
});

const exporter = new OTLPLogExporter({
  url: 'http://localhost:4318/v1/logs',
});

const loggerProvider = new LoggerProvider({ resource });
loggerProvider.addLogRecordProcessor(new BatchLogRecordProcessor(exporter));

module.exports = { loggerProvider };

Configure the log bridge

const winston = require('winston');
const { OpenTelemetryTransportV3 } = require('@opentelemetry/winston-transport');

const logger = winston.createLogger({
  level: 'info',
  transports: [
    new winston.transports.Console(),
    new OpenTelemetryTransportV3(), // forwards to the global LoggerProvider
  ],
});

module.exports = logger;

const pino = require('pino');
const { logs, SeverityNumber } = require('@opentelemetry/api-logs');

// Get a logger from the provider
const otelLogger = logs.getLogger('my-service');

// Write a Pino destination that forwards to OTel
const otelDest = pino.destination({
  write(msg) {
    const record = JSON.parse(msg);
    otelLogger.emit({
      severityNumber: pinoLevelToSeverity(record.level),
      severityText: record.level,
      body: record.msg,
      attributes: record,
    });
  },
});

function pinoLevelToSeverity(level) {
  if (level >= 50) return SeverityNumber.ERROR;
  if (level >= 40) return SeverityNumber.WARN;
  if (level >= 30) return SeverityNumber.INFO;
  return SeverityNumber.DEBUG;
}

const logger = pino({ level: 'info' }, otelDest);
module.exports = logger;

Set resource attributes

Resource attributes are attached to every log record exported from this process. Two attributes drive how Bronto organises incoming logs:

OTel attribute	Bronto concept	Description
`service.name`	Dataset	Groups logs from one service
`service.namespace`	Collection	Groups related services or a team’s services

These are set via the Resource constructor in the provider setup above.

Complete example

app.js

// Must be required before any logger usage
const { loggerProvider } = require('./otel-logging');
const winston = require('winston');
const { OpenTelemetryTransportV3 } = require('@opentelemetry/winston-transport');

const logger = winston.createLogger({
  level: 'info',
  format: winston.format.json(),
  transports: [
    new winston.transports.Console(),
    new OpenTelemetryTransportV3(),
  ],
});

logger.info('Application started');
logger.warn('Low disk space', { disk_free_gb: 2.1 });
logger.error('Database connection failed', { error: 'timeout' });

// Flush on shutdown
process.on('SIGTERM', async () => {
  await loggerProvider.shutdown();
  process.exit(0);
});

Verify delivery

After running your application, check both signals in Bronto:

Logs: open the Search page and filter by the dataset name you set in service.name — your log records should appear within a few seconds.
Traces: open the Explore Traces page and filter by the same service.name — your spans should appear within a few seconds.

If no logs appear, check:

The OTel Collector is running and reachable at the configured endpoint.
The Collector’s pipeline includes a logs pipeline with an otlp receiver and the Bronto exporter — see Connect Open Telemetry to Bronto.
otel-logging.js is required before any logger is created — the OpenTelemetryTransportV3 picks up the global LoggerProvider on instantiation.
BatchLogRecordProcessor exports on a background timer — for short-lived scripts, call loggerProvider.shutdown() before exit to flush pending records.

Traces

For Express, HTTP, gRPC, database drivers, and other popular libraries, use @opentelemetry/auto-instrumentations-node — it instruments all supported libraries automatically at startup with no code changes. Run node -r @opentelemetry/auto-instrumentations-node/register app.js or require it at the top of your entry point. See Node.js auto-instrumentation for setup details.

Install tracing dependencies

npm install \
  @opentelemetry/sdk-trace-node \
  @opentelemetry/exporter-trace-otlp-http

Package	Purpose
`@opentelemetry/sdk-trace-node`	`NodeTracerProvider` with automatic context propagation
`@opentelemetry/exporter-trace-otlp-http`	OTLP/HTTP span exporter

Configure the tracer provider

otel-tracing.js

const { NodeTracerProvider } = require('@opentelemetry/sdk-trace-node');
const { OTLPTraceExporter } = require('@opentelemetry/exporter-trace-otlp-http');
const { BatchSpanProcessor } = require('@opentelemetry/sdk-trace-base');

function configureOtelTracing(resource) {
  const exporter = new OTLPTraceExporter({
    url: 'http://localhost:4318/v1/traces',
  });

  const provider = new NodeTracerProvider({ resource });
  provider.addSpanProcessor(new BatchSpanProcessor(exporter));
  provider.register(); // sets global trace context propagation

  return provider;
}

module.exports = { configureOtelTracing };

Pass the same resource object used for logging so both signals share service.name and service.namespace.

Creating spans

const { trace } = require('@opentelemetry/api');

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

async function processPayment(amount, currency) {
  return tracer.startActiveSpan('process-payment', async (span) => {
    span.setAttributes({ 'payment.amount': amount, 'payment.currency': currency });
    logger.info('Processing payment');  // trace_id and span_id injected automatically
    // your code here
    span.end();
  });
}

Any log emitted inside an active span will automatically have trace_id and span_id attached via the OpenTelemetryTransportV3.

Complete example

app.js

const { resource, loggerProvider } = require('./otel-logging');
const { configureOtelTracing } = require('./otel-tracing');
const { trace } = require('@opentelemetry/api');
const winston = require('winston');
const { OpenTelemetryTransportV3 } = require('@opentelemetry/winston-transport');

// Tracing — pass the same resource used for logging
configureOtelTracing(resource);

const logger = winston.createLogger({
  transports: [new winston.transports.Console(), new OpenTelemetryTransportV3()],
});

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

tracer.startActiveSpan('handle-request', (span) => {
  span.setAttribute('http.method', 'GET');
  logger.info('Handling request');  // trace_id + span_id attached automatically
  span.end();
});

GenAI semantic conventions

If your application calls an LLM (OpenAI, Anthropic, Amazon Bedrock, etc.), OpenTelemetry defines a dedicated set of GenAI semantic conventions — gen_ai.* attributes for model, token usage, and prompt/response content.

This page was verified on July 17, 2026. GenAI libraries and semantic conventions are evolving rapidly, so package configuration and emitted attributes can change between releases. Keep your instrumentation current and verify the fields emitted by the version you deploy.

Auto-instrumentation

Contrib packages instrument popular provider SDKs automatically. For OpenAI:

npm install @opentelemetry/instrumentation-openai

const { OpenAIInstrumentation } = require('@opentelemetry/instrumentation-openai');
const { registerInstrumentations } = require('@opentelemetry/instrumentation');

registerInstrumentations({
  instrumentations: [new OpenAIInstrumentation()],
});

For Amazon Bedrock, no extra package is needed beyond the AWS SDK instrumentation you likely already have: @opentelemetry/instrumentation-aws-sdk implements the GenAI semantic conventions for Bedrock Runtime calls (Converse, InvokeModel), and is bundled in @opentelemetry/auto-instrumentations-node.

Need broader provider or framework coverage? See OpenLLMetry for supported packages, setup, schema guidance, and content-capture controls.

Experimental: capturing prompt and response content

For the contrib instrumentations, content capture is off by default and controlled by:

export OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT=true

(The OTEL_SEMCONV_STABILITY_OPT_IN=gen_ai_latest_experimental opt-in used by the Python instrumentations is not read by the JS contrib packages.)

With content capture enabled, prompt/response content is emitted as log records (OTel log events) — it flows through the logs pipeline, correlated to the span by trace_id, rather than landing on the span itself, so it is not queryable in Bronto’s traces dataset.To shape it for search, emit the content as a structured log record with explicit attributes, using the log bridge configured above. See LLM Observability for the recommended attribute names, a worked logging example, and Bronto search queries.

Manual spans

Where no auto-instrumentation package exists for your provider, set the gen_ai.* attributes yourself:

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

tracer.startActiveSpan('chat gpt-4o-mini', (span) => {
  span.setAttributes({
    'gen_ai.provider.name': 'openai',
    'gen_ai.request.model': 'gpt-4o-mini',
    'gen_ai.usage.input_tokens': 33,
    'gen_ai.usage.output_tokens': 74,
    // An array attribute — Bronto displays it flattened as finish_reasons.0
    'gen_ai.response.finish_reasons': ['stop'],
  });
  span.end();
});

See LLM Observability for the full recommended attribute set, including gen_ai.input.messages / gen_ai.output.messages, and how to search and aggregate GenAI fields in Bronto.

Direct export to Bronto

If you are not using an OTel Collector, export directly to Bronto by replacing the exporter configurations with the Bronto OTLP endpoints and your API key:

const logExporter = new OTLPLogExporter({
  url: 'https://ingestion.eu.bronto.io/v1/logs', // or ingestion.us.bronto.io
  headers: { 'x-bronto-api-key': '<YOUR_API_KEY>' },
});

const traceExporter = new OTLPTraceExporter({
  url: 'https://ingestion.eu.bronto.io/v1/traces', // or ingestion.us.bronto.io
  headers: { 'x-bronto-api-key': '<YOUR_API_KEY>' },
});

Region	Logs endpoint	Traces endpoint
EU	`https://ingestion.eu.bronto.io/v1/logs`	`https://ingestion.eu.bronto.io/v1/traces`
US	`https://ingestion.us.bronto.io/v1/logs`	`https://ingestion.us.bronto.io/v1/traces`

See API Keys for how to create a key with ingestion permissions. No other changes to the rest of the setup are required.

Overview

Ingest with agents

Ingest from AWS

Ingest from Azure

Ingest from CDN and edge

Ingest from apps and platforms

Ingest from infrastructure and databases

Ingest OpenTelemetry data

Send Node.js logs and traces to Bronto via OpenTelemetry

Prerequisites

Install dependencies

Configure the OTel logger provider

Configure the log bridge

Set resource attributes

Complete example

Verify delivery

Traces

Install tracing dependencies

Configure the tracer provider

Creating spans

Complete example

GenAI semantic conventions

Auto-instrumentation

Experimental: capturing prompt and response content

Manual spans

Direct export to Bronto

​Prerequisites

​Install dependencies

​Configure the OTel logger provider

​Configure the log bridge

​Set resource attributes

​Complete example

​Verify delivery

​Traces

​Install tracing dependencies

​Configure the tracer provider

​Creating spans

​Complete example

​GenAI semantic conventions

​Auto-instrumentation

​Experimental: capturing prompt and response content

​Manual spans

​Direct export to Bronto

Prerequisites

Install dependencies

Configure the OTel logger provider

Configure the log bridge

Set resource attributes

Complete example

Verify delivery

Traces

Install tracing dependencies

Configure the tracer provider

Creating spans

Complete example

GenAI semantic conventions

Auto-instrumentation

Experimental: capturing prompt and response content

Manual spans

Direct export to Bronto