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Solutions Architect's Handbook

Solutions Architect's Handbook

By : Saurabh Shrivastava, Neelanjali Srivastav
4.7 (59)
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Solutions Architect's Handbook

Solutions Architect's Handbook

4.7 (59)
By: Saurabh Shrivastava, Neelanjali Srivastav

Overview of this book

Master the art of solution architecture and excel as a Solutions Architect 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. Large language models, generative AI, and innovations in deep learning are cutting-edge advancements shaping the future of technology. Topics such as cloud-native architecture, data engineering architecture, cloud optimization, mainframe modernization, and building cost-efficient and secure architectures remain important in today's landscape. This book provides coverage of these emerging and key technologies and walks you through solution architecture design from key principles, providing you with the knowledge you need to succeed as a Solutions Architect. It will also level up your soft skills, providing career-accelerating techniques to help you get ahead. Unlock the potential of cutting-edge technologies, gain 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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Preface
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Preface
Who this book is for
What this book covers
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1
Solutions Architects in Organizations
Solutions Architects in Organizations
What is solution architecture?
The solutions architect’s role
Understanding a solutions architect’s responsibilities
Solutions architect in an Agile organization
Common challenges in the solutions architect role
Career path and skill development for solutions architects
Summary
2
Principles of Solution Architecture Design
Principles of Solution Architecture Design
Building scalable architecture design
Building a highly available and resilient architecture
Making your architecture fault-tolerant
Designing for performance
Creating immutable architecture
Think loose coupling
Think service, not server
Think data-driven design
Adding security everywhere
Making applications usable and accessible
Building future-proof extendable and reusable architecture
Ensuring architectural interoperability and portability
Applying automation everywhere
Plan for business continuity
Design for operation
Overcoming architectural constraints
Summary
3
Cloud Migration and Cloud Architecture Design
Cloud Migration and Cloud Architecture Design
Public, private, and hybrid clouds
Solution architecture in the public cloud
Creating a cloud migration strategy
Choosing a cloud migration strategy
Steps for cloud migration
Creating a hybrid cloud architecture
Taking a multi-cloud approach
Implementing CloudOps
CloudOps pillars
Summary
Further reading
4
Solution Architecture Design Patterns
Solution Architecture Design Patterns
Building an n-tier layered architecture
Creating a multi-tenant SaaS-based architecture
Understanding service-oriented architecture
Building a cache-based architecture
Model-View-Controller (MVC) architecture
Building Domain-Driven Design (DDD)
Understanding the circuit breaker pattern
Implementing the bulkhead pattern
Creating a floating IP pattern
Deploying an application with a container
Database handling in application architecture
Clean Architecture
Avoiding anti-patterns in solution architecture
Summary
5
Cloud-Native Architecture Design Patterns
Cloud-Native Architecture Design Patterns
What is cloud-native architecture?
Building serverless architecture
Building stateless and stateful architectural designs
Creating a microservice architecture
Reactive architecture
Building queue-based architecture
Pipes-and-Filters Architecture
Creating Event-Driven Architecture
Backend for Frontend pattern
Cloud-native architecture anti-patterns
Summary
6
Performance Considerations
Performance Considerations
Design principles for high-performance architecture
Technology selection for performance optimization
Performance considerations for mobile applications
Performance testing
Managing performance monitoring
Summary
7
Security Considerations
Security Considerations
Design principles for architectural security
Selecting technology for architectural security
Security and compliance certifications
The cloud’s shared security responsibility model
Securing threat modeling
Summary
8
Architectural Reliability Considerations
Architectural Reliability Considerations
Design principles for architectural reliability
Technology selection for architectural reliability
Improving reliability with the cloud
Summary
9
Operational Excellence Considerations
Operational Excellence Considerations
Design principles for operational excellence
Selecting technologies for operational excellence
Achieving operational excellence in the public cloud
Driving efficiency with CloudOps
Summary
10
Cost Considerations
Cost Considerations
Design principles for cost optimization
Understanding techniques for cost optimization
Driving cost optimization in the public cloud
Green IT and its influence on cost considerations
Summary
11
DevOps and Solution Architecture Framework
DevOps and Solution Architecture Framework
Introducing DevOps
Understanding the components of DevOps
Introducing DevSecOps for Security
Combining DevSecOps and CI/CD
Implementing a CD strategy
Best practices for choosing the right deployment strategy
Implementing continuous testing in the CI/CD pipeline
Using DevOps tools for CI/CD
Implementing DevOps best practices
Building DevOps and DevSecOps in the cloud
Summary
12
Data Engineering for Solution Architecture
Data Engineering for Solution Architecture
What is big data architecture?
Designing big data processing pipelines
Data ingestion, storage, processing, and analytics
Data storage in the cloud
Visualizing data
Designing big data architectures
Big data architecture best practices
Summary
13
Machine Learning Architecture
Machine Learning Architecture
What is machine learning?
Working with data science and machine learning
Machine learning in the cloud
Building machine learning architecture
Design principles for machine learning architecture
MLOps
Deep learning
NLP
Summary
14
Generative AI Architecture
Generative AI Architecture
What is generative AI?
Generative AI use cases
The basic architecture of generative AI systems
Popular generative AI FMs
How to start with generative AI
Generative AI reference architecture for building a mortgage assistant app
Challenges in implementing generative AI
Summary
15
Rearchitecting Legacy Systems
Rearchitecting Legacy Systems
Learning the challenges of legacy systems
Defining a strategy for system modernization
Looking at legacy system modernization techniques
Defining a cloud migration strategy for legacy systems
Mainframe migration with the public cloud
Modernizing legacy code with generative AI
Summary
16
Solution Architecture Document
Solution Architecture Document
Purpose of the SAD
Views of the SAD
Structure of the SAD
Life cycle of the SAD
SAD best practices and common pitfalls
IT procurement documentation for a solution architecture
Summary
17
Learning Soft Skills to Become a Better Solutions Architect
Learning Soft Skills to Become a Better Solutions Architect
Importance of soft skills in solution architecture
Acquiring pre-sales skills
Taking ownership and accountability
Being flexible and adaptable
Design thinking
Being a builder by engaging in coding hands-on
Becoming better with continuous learning
Being a mentor to others
Becoming a technology evangelist and thought leader
Summary
18
Other Books You May Enjoy
Other Books You May Enjoy
19
Index
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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