Building Resilient AI Architectures using Amazon Bedrock and AWS Step Functions

Service disruptions and model throttling are an inevitable reality when building on top of any third-party API. A resilient architecture anticipates these disruptions and degrades gracefully, maintaining core functionality and a good user experience even when the underlying model isn't fully available.

In this lab, students will build a state machine in AWS Step Functions that wraps every Bedrock call in resilience logic. The gateway implements a circuit breaker pattern to detect when the primary model is degraded (e.g. due to throttling or transient errors) and automatically routes to a fallback model when necessary. By the end of the lab, students will have a reusable architecture they can drop into any Bedrock-backed application to protect against the two most common real-world failure modes:

• Regional throttling
• Transient model errors

Learning objectives

Upon completion of intermediate-level lab, you will be able to:

• Deploy an AI model state machine using AWS Step Functions and Amazon Bedrock
• Implement a circuit breaker pattern to detect and respond to model degradation
• Simulate model failures and observe the self-healing behavior of the architecture

Intended audience

• Candidates for the AWS Certified Generative AI Developer – Professional (AIP-C01) exam
• Cloud Architects
• AI Developers

Prerequisites

Familiarity with the following will be beneficial but is not required:

• AWS Step Functions
• Amazon Bedrock
• AWS Lambda
• AWS DynamoDB

The following content can be used to fulfill the prerequisites:

• Orchestrating Generative AI Applications With AWS Step Functions and Amazon Bedrock
• Building an Agentic AI Workflow with Amazon Bedrock and AWS Step Functions