AWS has published guidance on implementing resilience patterns with Amazon Bedrock and an LLM gateway. The approach is aimed at making AI applications more reliable when models, providers or downstream services fail.
Resilience is becoming a core production requirement for AI systems. Teams need retries, fallbacks, routing, rate-limit handling and observability because model calls are now part of critical workflows.
For enterprises, the guidance reflects a shift from prompt experiments to operational AI architecture, where uptime and predictable behavior matter as much as output quality.