Implementing resilience patterns with Amazon Bedrock and LLM gateway

This article presents five practical patterns for building resilient generative AI applications on AWS using Amazon Bedrock and LLM gateways to ensure high availability, throughput, and cost-effectiveness.

• Amazon Bedrock cross-Region inference automatically distributes requests across regions to improve throughput and reduce throttling
• AWS account sharding creates fault isolation boundaries with independent quotas for multi-tenant architectures
• Model fallback enables automatic failover between primary and secondary models during rate limits or disruptions
• Load balancing distributes requests across multiple models to optimize resource utilization and prevent bottlenecks
• Multi-tenant quota isolation prevents noisy neighbor problems by enforcing independent rate limits per consumer
• LLM gateways provide unified abstraction layer with routing, failover, governance, and observability capabilities

These incremental patterns help organizations scale LLM inference from experimentation to production while maintaining availability, managing costs, and supporting multi-tenant isolation.