فهرست مطالب

• Cover
• Copyright
• Forewords
• Contributors
• Table of Contents
• Preface
• Chapter 1: Solutions Architect in an Organization
• What is solution architecture?
• he 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
• Chapter 2: 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
• Chapter 3: 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
• Chapter 4: 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
• Chapter 5: 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
• Chapter 6: Performance Considerations
• Design principles for high-performance architecture
• Technology selection for performance optimization
• Performance considerations for mobile applications
• Performance testing
• Managing performance monitoring
• Summary
• Chapter 7: Security Considerations
• Chapter 8:Architectural Reliability Considerations
• Design principles for architectural reliability
• Technology selection for architectural reliability
• Improving reliability with the cloud
• Summary
• Chapter 9: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
• Chapter 10: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
• Chapter 11: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
• Chapter 12: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
• Chapter 13: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
• Chapter 14: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
• Chapter 15: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
• Chapter 16: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
• Chapter 17: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
• PacktPage
• Index