Message Queue

Overview

Message Queue is an infrastructure component that stores messages between producers and consumers so work can be processed asynchronously and temporary speed or availability differences can be absorbed. Evidence for Message Queue should preserve the input, configuration version, actor or service, decision, downstream reference, and final outcome.

The principal risks include backlog growth, poison messages, duplicate processing, lost acknowledgements, hidden latency, ordering assumptions, unbounded retention, and a queue outage blocking critical payment workflows. Operational metrics for Message Queue should use stable denominators and separate technical activity from successful business completion.

A production implementation should define durability, acknowledgement, retention, ordering scope, retry and dead-letter behavior, access control, encryption, capacity limits, and consumer idempotency. A queue decouples delivery and processing but does not by itself guarantee exactly-once business effects, ordering across all messages, or permanent event history.

Useful measures include queue depth, oldest-message age, publish and consume rate, redelivery rate, dead-letter count, processing latency, and consumer lag. Message Queue is closely connected to At-Least-Once Delivery, Backpressure, and Idempotent Consumer. Changes to Message Queue should be tested against normal, failed, delayed, duplicate, and recovery paths that apply to the operation.

Testing Message Queue should cover boundary values, dependency failure, restart recovery, and incompatible versions where they affect the workflow. The production boundary for Message Queue should identify the authoritative system, responsible owner, accepted states, and recovery path.

For Message Queue, identifiers and timestamps should remain stable enough to trace the technical action to its final business outcome. Monitoring for Message Queue should distinguish transport success, processing success, and the final external or financial result.