Event-Driven Backends for Resilient AI Workflows

Event-driven designs absorb spiky workloads and isolate failures. Each AI step—ingestion, enrichment, inference—emits events with durable state, enabling retries and idempotent consumers. Sagas coordinate multi-step operations with compensations, preventing partial writes from corrupting domains.
Observability moves from call stacks to streams. With proper correlation IDs and dead-letter handling, teams keep SLAs even when an external model times out or a provider throttles. This architecture transforms uncertainty into manageable work.