Build, Secure, and Ship Generative AI Applications on AWS—The Hands-On Way Generative AI is moving from hype to production—and Amazon Bedrock is the enterprise-grade platform making it possible. AWS Bedrock in Action is your practical, code-first guide to building real-world GenAI applications with Retrieval-Augmented Generation (RAG), multi-agent orchestration, and AI guardrails, all within AWS’s secure ecosystem. Written for working developers, cloud engineers, and architects , this book goes beyond theory. Every chapter maps to runnable code in Python and TypeScript , fully provisioned with AWS CDK, and tested in real AWS accounts. You’ll learn not only how to invoke Bedrock’s foundation models, but also how to operationalize them in production —with the same rigor you’d apply to any mission-critical system. Inside, you’ll master: Core Bedrock APIs (Converse, ConverseStream, Embeddings, Async Inference) with real-world usage patterns - Knowledge Bases for RAG , from ingestion pipelines to retrieval tuning and S3 Vectors - Guardrails for safe GenAI: input/output filtering, policies, and continuous evaluation - Agents and Flows , including OpenAPI action groups, tool delegation, and orchestration topologies - Enterprise Security with IAM boundaries, KMS encryption, VPC endpoints, and multi-tenant isolation - Production-readiness : observability with CloudWatch, structured logs, error budgets, CI/CD pipelines, and SLO-driven operations - Cost and performance strategies , from token budgets and caching to provisioned throughput and async batching By the end of this book, you’ll have deployed a production-grade Bedrock microservice , wired to RAG pipelines, secured with guardrails, and observable in CloudWatch. More importantly, you’ll have the muscle memory to build, scale, and ship GenAI features at enterprise standards—without guesswork. Whether you’re integrating generative AI into an existing system or building a brand-new application, AWS Bedrock in Action gives you the tools, patterns, and discipline to succeed. Perfect for developers, engineers, and architects who want to move beyond toy demos and deliver real GenAI value on AWS.