This lab is currently in Beta — content may be updated as we refine the material
LABINTERMEDIATE

Bedrock Multi-Model Integration

Build a multi-model service using AWS Bedrock to access Claude, compare it with direct API calls, and implement intelligent provider fallback.

60 minutes
ai-infrastructure/aws-ai
Bedrock Multi-Model Integration - Platform Engineering Hands-On Lab Icon

Lab Overview

This hands-on lab teaches you to integrate AWS Bedrock into your LLM applications and understand when to use Bedrock versus direct provider APIs.

You'll learn to:

  • Configure AWS credentials for Bedrock access
  • Invoke Claude models through Bedrock with streaming responses
  • Compare latency and response quality between Bedrock and local Ollama
  • Build a provider abstraction that supports multiple backends
  • Implement automatic fallback between Bedrock and other providers

This lab builds practical skills for enterprise AI deployments where AWS integration and compliance are requirements.

What You'll Learn

Configure AWS credentials and verify Bedrock model access

Invoke Claude models through AWS Bedrock with streaming responses

Compare latency and response quality between Bedrock and local providers

Implement multi-provider fallback for resilient AI applications

Prerequisites

llm-provider-landscape

multi-provider-integration

aws-basics

Technologies Covered

awsbedrockclaudellmpythonboto3enterprise

Part of a Course

This lab is part of the LLM Integration and API Patterns course

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  • Managed AWS Account included
  • Pre-configured environments
  • Real-world cloud scenarios

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