Outbox Pattern Survival Guide

The outbox pattern is a store-and-forward mechanism, not a place to embed business logic. When the dispatcher that moves rows from the outbox to a broker starts to make decisions, it becomes a source of bugs and operational headaches. Keep the dispatcher thin and let it focus on reliably moving data.

Database contention is a common failure mode. Spinning up many dispatchers or tying one to every API pod can flood the outbox table with concurrent readers, causing locks that throttle throughput. Often a smaller number of well-tuned dispatchers yields higher overall performance.

Treat the database as a short-term buffer, not a queue. The outbox table should hold records only briefly before they are handed off to a purpose-built message broker like RabbitMQ or Kafka, which are designed to absorb spikes and handle consumer unavailability.

Maintenance should be batched and partitioned. Deleting rows one by one incurs heavy locking and bloats transaction logs. Using batch deletes or, better yet, partitioning the table and truncating whole partitions reduces lock time and keeps the database healthy.

Finally, instrument everything. Track message volumes, latencies, and failure rates, and use that data to plan capacity. Decouple the source outbox from consumer processing to avoid tight coupling that makes future changes painful.