This book is a practical, hands-on guide created for developers, data scientists, and cloud architects who want to build and deploy generative AI applications efficiently on AWS--without the complexity of managing infrastructure or training models. This book offers a fast, structured, and applied path from simple prompts to scalable enterprise workflows.
The book starts with a practical approach, diving directly into real-world, executable patterns inspired by Amazon's open-source Bedrock samples rather than staying conceptual. Each recipe follows a clear format--problem, solution, and runnable code--so readers can quickly build summarizers, Q&A systems, classifiers, semantic search pipelines, RAG chatbots, and multimodal applications using text and images. Readers learn how to generate embeddings, integrate with OpenSearch, orchestrate multi-turn chat flows, build agent-based tool-using assistants, and deploy workloads through serverless AWS patterns like Lambda and API Gateway. The book also covers advanced enterprise practices, including custom model tuning, secure application design, responsible AI guardrails, cost optimization, and observability. Case studies and appendices provide guided examples for customer support automation, marketing content generation, and knowledge-base assistants, along with practical security and troubleshooting tips.
By the end of this book, readers will have a ready-to-use library of Bedrock recipes and deployment patterns--plus the architectural understanding to extend, combine, and scale them for real business needs. Whether you're prototyping or preparing for production, this book equips you with repeatable techniques to deliver secure, high-performance generative AI applications on AWS.
What you will learn:
Implement generative AI recipes using Amazon Bedrock foundation models
Build RAG-powered chatbots, summarizers, and Q&A assistants
Integrate Bedrock with AWS services like Lambda, API Gateway, and OpenSearch
Deploy multimodal AI workflows (text, image, embeddings)
Apply best practices for cost optimization, monitoring, and responsible AI
Who this book is for:
Cloud developers, data scientists, and ML engineers building generative AI solutions on AWS. AI learners and enthusiasts exploring large language models and real-world applications. Enterprise and startup teams integrating AI into products, workflows, and automation systems.
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