Event-Driven Architecture Bottlenecking Under Load

Your application's event-driven architecture works fine in development but collapses under production load. Events pile up in queues, consumers can't keep pace with producers, and end users experience increasing delays in seeing updates, receiving notifications, or having their actions processed.

Event-driven architectures are powerful but introduce complexity that AI-generated code often doesn't handle correctly. The initial implementation works for single-digit users but fails at scale because it lacks consumer scaling, proper partitioning, dead letter queues, and backpressure mechanisms.

Symptoms include growing queue depths, increasing latency on event processing, out-of-memory errors on consumer processes, and eventually dropped events when queues hit their size limits.