RabbitMQ Queue Telemetry

Implementation evidence

RabbitMQ Queue Telemetry: from boundary to verified row

Use RabbitMQ Queue Telemetry at a controlled application boundary, keep the event contract small, and verify a known outcome before building aggregate views.

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

Before you start

Prerequisites and boundaries

amqplib and telemetry-sh initialized in the trusted producer or consumer process
A stable logical message ID, queue taxonomy, and terminal outcome definition
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

1Prepare one reusable server-side delivery client with bounded network behavior.
2Add the outcome event at the success, failure, retry, or timeout boundary.
3Send controlled fixtures 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 contract

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

Implementation checkpoints

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

Production boundary

Keep the outcome event small and recoverable

This pattern provides

A bounded, SQL-ready outcome beside the upstream workflow.
Stable fields for dashboards, alerts, and cross-event correlation.
A fixture-driven path for validating success, failure, retry, and timeout behavior.

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

Event schema starting points

Review the row grain, emit boundary, required types, privacy classes, example payload, and validation checklist before adapting a query or snippet to production.

Async reliability11 fields