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Solutions Architect's Handbook

Solutions Architect's Handbook - Third Edition

By : Saurabh Shrivastava, Neelanjali Srivastav
4.6 (57)
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Solutions Architect's Handbook

Solutions Architect's Handbook

4.6 (57)
By: Saurabh Shrivastava, Neelanjali Srivastav

Overview of this book

Build a strong foundation in solution architecture and excel in your career with the Solutions Architect’s Handbook. Authored by seasoned AWS technology leaders Saurabh Shrivastav and Neelanjali Srivastav, this book goes beyond traditional certification guides, offering in-depth insights and advanced techniques to meet the specific needs and challenges of solutions architects today. This edition introduces exciting new features that keep you at the forefront of this evolving field. From large language models and generative AI to deep learning innovations, these cutting-edge advancements are shaping the future of technology. Key topics such as cloud-native architecture, data engineering architecture, cloud optimization, mainframe modernization, and building cost-efficient, secure architectures remain essential today. This book covers both emerging and foundational technologies, guiding you through solution architecture design with key principles and providing the knowledge you need to succeed as a Solutions Architect. It also sharpens your soft skills, providing career-accelerating techniques to stay ahead. By the end of this book, you will be able to harness cutting-edge technologies, apply practical insights from real-world scenarios, and enhance your solution architecture skills with the Solutions Architect's Handbook.
Table of Contents (20 chapters)
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18
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Index

What this book covers

This book contains the following chapters:

Chapter 1: Solutions Architects in Organizations, explores the varied roles of solutions architects within an organization, detailing their responsibilities and illustrating how they align with different organizational structures.

Chapter 2: Principles of Solution Architecture Design, discusses the foundational principles that guide the creation of scalable, secure, and efficient solution architectures, emphasizing best practices in design methodology.

Chapter 3: Cloud Migration and Cloud Architecture Design, offers a roadmap for transitioning to the cloud, including strategies for migration, the benefits of cloud adoption, and the principles of cloud architecture design.

Chapter 4: Solution Architecture Design Patterns, reviews common architectural patterns, providing insights on when and how to apply them effectively to solve different architectural challenges.

Chapter 5: Cloud-Native Architecture Design Patterns, delves into design patterns specifically tailored for cloud-native environments, emphasizing scalability, resilience, and maintainability.

Chapter 6: Performance Considerations, focuses on optimizing the performance of IT systems, discussing key metrics, and strategies to enhance speed and efficiency in architectural designs.

Chapter 7: Security Considerations, addresses the critical aspect of security in solution architecture, covering best practices, patterns, and strategies to safeguard systems.

Chapter 8: Architectural Reliability Considerations, examines the principles and practices essential for building reliable systems, including disaster recovery planning and high availability design.

Chapter 9: Operational Excellence Considerations, highlights strategies and practices to achieve operational excellence, ensuring that systems are efficient, reliable, and maintainable.

Chapter 10: Cost Considerations, provides guidance on managing and optimizing costs associated with architectural solutions, focusing on maximizing value while minimizing expenses.

Chapter 11: DevOps and Solution Architecture Framework, integrates DevOps practices with solution architecture, illustrating how this synergy enhances deployment, monitoring, and maintenance.

Chapter 12: Data Engineering for Solution Architecture, introduces the fundamentals of data engineering within the context of solution architecture, emphasizing the design of data systems and workflows.

Chapter 13: Machine Learning Architecture, covers the architectural considerations for integrating machine learning into solutions, from data preparation to model deployment.

Chapter 14: Generative AI Architecture, explores the architecture behind generative AI systems, discussing the components and processes that enable AI to create novel content.

Chapter 15: Rearchitecting Legacy Systems, provides strategies and insights for modernizing legacy systems, focusing on how to transition them to contemporary, cloud-based environments.

Chapter 16: Solution Architecture Document, outlines the importance and structure of a comprehensive solution architecture document, guiding architects on how to effectively communicate their designs.

Chapter 17: Learning Soft Skills to Become a Better Solutions Architect, emphasizes the essential soft skills needed for solutions architects to succeed, including communication, problem-solving, and leadership.

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