Generative AI for Cloud Solutions: Architect Modern AI LLMs in Secure, Scalable, and Ethical Cloud Environments

Building with generative AI means more than choosing a language model. Teams also have to think about data, deployment, security, scale, and how a promising prototype becomes a dependable cloud application. Generative AI for Cloud Solutions brings those decisions together, moving from the foundations of LLMs to the practices and architectures involved in putting them to work.

Paul Singh and Anurag Karuparti take readers from conversational AI, generative models, and transformers into application-focused topics such as prompt engineering, fine-tuning, retrieval-augmented generation (RAG), and cloud deployment. The emphasis is on understanding how the pieces fit—not treating an LLM as a solution in isolation.

From language models to cloud applications

The opening material establishes the relationship between natural language processing, transformers, large language models, and cloud computing. From there, the book explores ways to tailor models and build applications, including chatbot foundations, RAG, and approaches for adapting models to particular needs.

Practical concerns beyond the prototype

Deployment brings its own set of questions. The book addresses scaling, security, cost considerations, and responsible AI, alongside LLMOps, autonomous agents, and Assistants APIs. These subjects help readers frame generative AI as an ongoing engineering and operational challenge—not just a prompt-and-response demonstration.

Who will find it useful?

Cloud developers and architects, data scientists, AI practitioners, and technical business leaders will find the cloud-and-LLM perspective especially relevant. The material ranges from introductory explanations to intermediate technical concepts, so readers with a basic familiarity with cloud environments will have a useful starting point.

For practitioners working out how generative AI fits into real cloud systems, Singh and Karuparti offer a grounded path through the terminology, techniques, and design considerations shaping that work.