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Mastering AWS Cloud: Cloud adoption using the AWS cloud computing ecosystem
Cloud computing has redefined how modern businesses scale, secure, and innovate. Amazon Web Services (AWS) is the world’s leading cloud platform, providing the essential compute, storage, networking, and database power that runs modern applications. It stands as the global leader in cloud platforms, empowering millions of organizations with robust infrastructure, automation, and AI-driven services.
This book provides a comprehensive, expert-guided journey through the AWS ecosystem. You will explore core services, advanced networking, infrastructure as code, serverless design, edge computing, and real-world deployment architectures. Each chapter demystifies one vital aspect of AWS mastery, including governance, observability, media streaming, IoT, AI, and global infrastructure best practices.
By the end, readers will confidently architect, secure, and optimize scalable cloud solutions using AWS. The readers will possess a vast, practical knowledge of over 200 AWS services and be able to confidently apply the AWS Well-Architected Framework's six strategic pillars to design, optimize, and manage any cloud solution.
What you will learn
● Design enterprise-grade AWS architectures.
● Master Spark execution model RDDs, DAGs, Catalyst, and Adaptive Query Execution.
● Automate infrastructure with IaC tools.
● Apply secure networking and Zero Trust models.
● Build resilient serverless and edge solutions.
● Deploy AI/ML workloads with AWS services.
● Optimize media, IoT, and hybrid environments.
● Architect for observability and cost-efficiency.
● Scale infrastructure across global zones.
Who this book is for
This book is for cloud architects, DevOps engineers, solution designers, IT managers, and technical leads aiming to gain practical mastery of AWS. It also benefits advanced learners, certification candidates, and professionals building real-world, production-ready cloud systems.
Table of Contents
Prologue
1. AWS Architecture
2. Compute
3. Storage
4. Content Delivery Network
5. Security, Identity, and Compliance
6. Database
7. Developer Tools and Part 1
8. Developer Tools and Part 2
9. End-user, Front-end, and Mobile
10. Applications for Business
11. Analytics and Machine Learning
12. Management and Governance
13. Migration and Transfer
14. AWS Well-Architected Framework
Appendix 1: Smart City Architecture with AWS and the Well-Architected Framework
Appendix 2: Bibliography
This book provides a comprehensive, expert-guided journey through the AWS ecosystem. You will explore core services, advanced networking, infrastructure as code, serverless design, edge computing, and real-world deployment architectures. Each chapter demystifies one vital aspect of AWS mastery, including governance, observability, media streaming, IoT, AI, and global infrastructure best practices.
By the end, readers will confidently architect, secure, and optimize scalable cloud solutions using AWS. The readers will possess a vast, practical knowledge of over 200 AWS services and be able to confidently apply the AWS Well-Architected Framework's six strategic pillars to design, optimize, and manage any cloud solution.
What you will learn
● Design enterprise-grade AWS architectures.
● Master Spark execution model RDDs, DAGs, Catalyst, and Adaptive Query Execution.
● Automate infrastructure with IaC tools.
● Apply secure networking and Zero Trust models.
● Build resilient serverless and edge solutions.
● Deploy AI/ML workloads with AWS services.
● Optimize media, IoT, and hybrid environments.
● Architect for observability and cost-efficiency.
● Scale infrastructure across global zones.
Who this book is for
This book is for cloud architects, DevOps engineers, solution designers, IT managers, and technical leads aiming to gain practical mastery of AWS. It also benefits advanced learners, certification candidates, and professionals building real-world, production-ready cloud systems.
Table of Contents
Prologue
1. AWS Architecture
2. Compute
3. Storage
4. Content Delivery Network
5. Security, Identity, and Compliance
6. Database
7. Developer Tools and Part 1
8. Developer Tools and Part 2
9. End-user, Front-end, and Mobile
10. Applications for Business
11. Analytics and Machine Learning
12. Management and Governance
13. Migration and Transfer
14. AWS Well-Architected Framework
Appendix 1: Smart City Architecture with AWS and the Well-Architected Framework
Appendix 2: Bibliography
499 pages, Kindle Edition
About the author
Paulo H. Leocadio
4 books2 followersPaulo H. Leocadio is an engineer, technology architect, researcher, and author whose work spans artificial intelligence, autonomous systems, cloud computing, and applied cognitive architectures.
His research and writing examine a recurring question: how do we move from systems that execute increasingly sophisticated instructions toward architectures capable of maintaining, retrieving, and acting upon internal representations with greater autonomy?
His work combines engineering practice with theoretical investigation, drawing on experience in enterprise architecture, software engineering, artificial intelligence, and large-scale technology programs. Rather than treating AI primarily as a collection of models and tools, his recent work approaches it as an architectural problem involving memory, representation, cognition, governance, and autonomous decision-making.
Leocadio is the author and co-author of technical books and research publications covering cloud architecture, natural language processing, generative AI, cybersecurity, and autonomous cognitive systems.
He particularly welcomes difficult questions, competing interpretations, and challenges to the assumptions underlying his work. For him, disagreement is most useful when it creates an opportunity to examine the evidence.
His research and writing examine a recurring question: how do we move from systems that execute increasingly sophisticated instructions toward architectures capable of maintaining, retrieving, and acting upon internal representations with greater autonomy?
His work combines engineering practice with theoretical investigation, drawing on experience in enterprise architecture, software engineering, artificial intelligence, and large-scale technology programs. Rather than treating AI primarily as a collection of models and tools, his recent work approaches it as an architectural problem involving memory, representation, cognition, governance, and autonomous decision-making.
Leocadio is the author and co-author of technical books and research publications covering cloud architecture, natural language processing, generative AI, cybersecurity, and autonomous cognitive systems.
He particularly welcomes difficult questions, competing interpretations, and challenges to the assumptions underlying his work. For him, disagreement is most useful when it creates an opportunity to examine the evidence.
Ratings & Reviews
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Displaying 1 - 3 of 3 reviews
June 14, 2026
An Important Note on the Scope and Purpose of 'Mastering AWS Cloud'
I recently received some incredibly precise, critical feedback from a reader in India that I believe is vital to share with anyone considering this book. The reader noted that the book consists entirely of comprehensive textual descriptions rather than step-by-step code tutorials, and highlighted that a significant portion of its ~500 pages includes exhaustive indexing and a detailed table of contents.
This assessment is completely accurate regarding the book's structural format, and it highlights exactly what this book is—and what it is not.
What this book is:
This volume was intentionally designed to serve as a massive, unified reference manual and textbook. The goal was to build an all-in-one desktop companion for practitioners, enterprise architects, and students who need a single, reliable framework mapping out over 200+ AWS services and the Well-Architected Framework. It is built so you can immediately find definitions, architectural logic, and operational boundaries without having to cross-reference and browse dozens of open browser tabs. The extensive table of contents and index are intentional; they are the navigation system for a 500-page enterprise roadmap.
What this book is NOT:
This is not a "hands-on lab" workbook, a code-heavy cookbook, or a collection of command-line deployment scripts. If you are looking for ready-to-copy PyTorch implementations or step-by-step AWS SageMaker console walkthroughs, this book will not meet your immediate needs.
Technical books are massive investments of your time and money. I want to ensure this text lands exclusively in the hands of professionals who need an architectural, conceptual reference anchor. For those seeking highly technical, code-level deployment blueprints for autonomous LLM systems, those frameworks are being reserved for my upcoming technical development sequences.
I recently received some incredibly precise, critical feedback from a reader in India that I believe is vital to share with anyone considering this book. The reader noted that the book consists entirely of comprehensive textual descriptions rather than step-by-step code tutorials, and highlighted that a significant portion of its ~500 pages includes exhaustive indexing and a detailed table of contents.
This assessment is completely accurate regarding the book's structural format, and it highlights exactly what this book is—and what it is not.
What this book is:
This volume was intentionally designed to serve as a massive, unified reference manual and textbook. The goal was to build an all-in-one desktop companion for practitioners, enterprise architects, and students who need a single, reliable framework mapping out over 200+ AWS services and the Well-Architected Framework. It is built so you can immediately find definitions, architectural logic, and operational boundaries without having to cross-reference and browse dozens of open browser tabs. The extensive table of contents and index are intentional; they are the navigation system for a 500-page enterprise roadmap.
What this book is NOT:
This is not a "hands-on lab" workbook, a code-heavy cookbook, or a collection of command-line deployment scripts. If you are looking for ready-to-copy PyTorch implementations or step-by-step AWS SageMaker console walkthroughs, this book will not meet your immediate needs.
Technical books are massive investments of your time and money. I want to ensure this text lands exclusively in the hands of professionals who need an architectural, conceptual reference anchor. For those seeking highly technical, code-level deployment blueprints for autonomous LLM systems, those frameworks are being reserved for my upcoming technical development sequences.
March 11, 2026
The book is written by LLM or it is heavily redacted with LLM, and if reader wants the same content then they might copy and paste table of contents into LLM and get the same, shallow results.
No real world examples, the same mechanical rhythm of writing, recurring sentences, summaries that refer to wrong chapters, and strange announcements that we will uncover real-case scenarios in each chapter… that are not fulfilled!
This book is the perfect example of AI Slop where author gives you inflated nothing, and I will keep this book just to show during conference talks how to not write a technical, or any book.
No real world examples, the same mechanical rhythm of writing, recurring sentences, summaries that refer to wrong chapters, and strange announcements that we will uncover real-case scenarios in each chapter… that are not fulfilled!
This book is the perfect example of AI Slop where author gives you inflated nothing, and I will keep this book just to show during conference talks how to not write a technical, or any book.
September 27, 2026
I think this book makes more sense if approached as a field manual for practitioners rather than as a collection of case studies. I found it more useful to consult individual sections when needed than to expect every chapter to build toward a real-world narrative. That distinction matters: readers looking mainly for detailed case studies may come away disappointed, while someone looking for a technical reference and practical frameworks may find it much closer to what they need.
Displaying 1 - 3 of 3 reviews