RabbitMQ queue telemetry

Test the integration

Send and verify events with RabbitMQ queue telemetry

Use RabbitMQ queue telemetry where your app knows the final result. Collect only the fields you need, then verify a test event before building charts.

1
Choose the outcome
Queue reliability
2
Define the contract
message_id, message_type, exchange, routing_key, queue_name, and release
3
Log the final result
Treat publisher confirmation and consumer acknowledgement as different boundaries; neither proves the downstream business action completed.
4
Check the stored event
Exercise a known fixture, then inspect rabbitmq_message_completed for one correctly typed terminal row.

Before you start

amqplib and telemetry-sh initialized in the trusted producer or consumer process
A stable message ID, an allowed set of queue names, and a definition of when processing ends
Publisher confirms and manual consumer acknowledgements where the workflow requires delivery evidence

Delivery setup

Install and initialize server-side

Import telemetry-sh in server-only code and initialize it once with process.env.TELEMETRY_API_KEY. Keep ingestion credentials out of browser bundles, client-visible environment variables, source control, logs, and exception messages.

rabbitmq-install

npm installation

bash

npm install telemetry-sh

1Create one reusable server-side client. Set its timeout and retry limit.
2Log an event when the operation succeeds, fails, retries, or times out.
3Send test events with known results and inspect the stored rows before enabling an alert.

Snippet

Start with one structured event

Add this shape where the workflow completes, fails, or retries. Then build the dashboard from real fields.

rabbitmq

RabbitMQ queue telemetry event

javascript

await telemetry.log("rabbitmq_message_completed", {
  message_id: message.properties.messageId,
  message_type: "invoice_recalculation",
  exchange: "billing",
  routing_key: message.fields.routingKey,
  queue_name: "billing.recalculate",
  status: "success",
  attempt: Number(message.properties.headers?.attempt ?? 1),
  redelivered: message.fields.redelivered,
  wait_ms: Date.now() - Number(message.properties.timestamp) * 1000,
  duration_ms: Math.round(performance.now() - startedAt),
  dead_lettered: false,
  consumer_name: "billing-worker",
  release: process.env.APP_RELEASE,
});

Event schema

message_id, message_type, exchange, routing_key, queue_name, and release

status, attempt, redelivered, wait_ms, duration_ms, and error_type

published_at, acknowledged_at, dead_lettered, and consumer_name

Check your setup

Checkpoint 1

Treat publisher confirmation and consumer acknowledgement as different boundaries; neither proves the downstream business action completed.

Checkpoint 2

Use a stable message_id across redeliveries and a separate attempt value so retries remain visible without inflating final outcomes.

Checkpoint 3

Measure queue wait from an approved published timestamp, and never copy message bodies or unrestricted broker errors into the event.

Verification

Prove the event arrived

Run this after exercising known success and failure cases. Replace the fallback table name if your final event contract differs from the snippet.

rabbitmq-verification

RabbitMQ queue telemetry verification query

sql

SELECT *
FROM rabbitmq_message_completed
ORDER BY timestamp_utc DESC
LIMIT 20;

Confirm one terminal row per logical outcome, with the expected status, identifiers, units, and UTC time.

Inspect the inferred schema and verify that retries do not change field types or generate a new logical event ID.

Search the stored fields for credentials, raw payloads, prompts, private content, and unbounded error messages.

Exercise a provider timeout, ingestion rejection, and process shutdown before treating the dashboard as complete.

Implementation references

Review the event contract, data-safety guidance, and upstream primary documentation before enabling a new production path.

Background job monitoring Queue wait SQL Delivery and idempotency RabbitMQ reliability guide RabbitMQ consumer acknowledgements and publisher confirms

Where to log

Keep the outcome event small and recoverable

This pattern provides

Record the outcome as an event you can query with SQL.
Stable fields for dashboards, alerts, and cross-event correlation.
Test events for checking success, failure, retries, and timeouts.

This pattern does not provide

An OTLP exporter, automatic collection pipeline, or replacement for detailed traces and diagnostic logs.
Exactly-once delivery merely because the payload contains an event ID.
Permission to collect raw provider payloads, user content, credentials, or regulated data.

Delivery and idempotency Batching and shutdown Troubleshoot ingestion

Example event schemas

Check what each event records, when to send it, and which field types it needs. Review the example payload and privacy checklist before using it in production.

Async reliability11 fields