Why Developers Use Message Queues to Move Heavy Tasks Out of Request Paths

Async processing via message queues splits a request into two phases: the handler acknowledges the client immediately, while a separate worker handles the actual computation outside the request path. This approach is used to avoid high p99 latency caused by slow operations like payment calls, email delivery, or image resizing, which can collectively stall an app server's thread pool. Common brokers such as RabbitMQ, AWS SQS, Kafka, and Redis Streams hold messages with configurable persistence until a consumer processes and acknowledges them. If a worker crashes before acknowledging, the broker redelivers the message, resulting in at-least-once semantics that require idempotent consumer logic to prevent duplicate side effects. Key production details include marking messages as persistent, enabling publisher confirms so producers know the broker received the message, and setting prefetch limits to prevent slow consumers from holding up entire queues.