Solutions Architect's Handbook: Kick-start your solutions architect career by learning architecture design principles and strategies

Cover
Title Page
Copyright and Credits
Dedication
About Packt
Foreword
Contributors
Table of Contents
Preface
Chapter 1: The Meaning of Solution Architecture
	What is solution architecture?
	Evolution of solution architecture
	Why is solution architecture important?
	The benefits of solution architecture
		Addressing the business needs and quality of delivery
		Selecting the best technology platform
		Addressing solution constraints and issues
		Helping in resource and cost management
		Managing solution delivery and project life cycle
		Addressing non-functional requirements
	Solution architecture in the public cloud
		What is the public cloud?
		Public clouds, private clouds, and hybrid clouds
		The public cloud architecture
		Public cloud providers and cloud service offering
	Summary
Chapter 2: Solution Architects in an Organization
	Types of solution architect role
		Enterprise solution architect
		Solution architect
		Technical architect 
		Cloud architect 
		Architect evangelist
		Infrastructure architect
		Network architect
		Data architect
		Security architect
		DevOps architect
	Understanding a solution architect's responsibilities
		Analyzing user requirements
		Defining non-functional requirements
		Engaging and working with stakeholders
		Handling various architecture constraints
		Making technology selections
		Developing a proof of concept and a prototype
		Designing solutions and staying through delivery
		Ensuring post-launch operability and maintenance
		Working as a technology evangelist
	Solution architects in an agile organization
		Why the Agile methodology?
		Agile manifesto
			Agile process and terminology
			Sprint ceremonies
			Agile tools and terms
			Agile versus waterfall
			Agile architecture
	Summary
Chapter 3: Attributes of the Solution Architecture
	Scalability and elasticity
		The capacity dilemma in scaling
		Scaling your architecture
		Static content scaling
		Server fleet elasticity
		Database scaling
	High availability and resiliency
	Fault tolerance and redundancy
	Disaster recovery and business continuity
	Extensibility and reusability
	Usability and accessibility
	Portability and interoperability
	Operational excellence and maintainability
	Security and compliance
		Authentication and authorization
		Web security
		Network security
		Infrastructure security
		Data security
	Cost optimization and budget
	Summary
Chapter 4: Principles of Solution Architecture Design
	Scaling workload
		Predictive scaling
		Reactive scaling
	Building resilient architecture
	Design for performance
	Using replaceable resources
		Creating immutable infrastructure
			Canary testing
	Think loose coupling
	Think service not server
	Using the right storage for the right need
	Think data-driven design
	Overcoming constraints
	Adding security everywhere
	Automating everything
	Summary
Chapter 5: Cloud Migration and Hybrid Cloud Architecture Design
	Benefits of cloud-native architecture
	Creating a cloud migration strategy
		Lift and Shift migration 
			Rehost
			Replatform
			Relocate
		Cloud-native approach
			Refactor
			Repurchase
		Retain or retire
			Retain
			Retire
	Steps for cloud migration 
		Discovering your workload
		Analyzing the information
		Creating migration plan
		Designing the application
		Performing application migration to the cloud
			Data migration
			Server migration
		Integration, validation, and cutover
			Live migration cutover
		Operating cloud application
		Application optimization in the cloud
	Creating a hybrid cloud architecture
	Designing a cloud-native architecture
	Popular public cloud choices
	Summary
	Further reading
Chapter 6: Solution Architecture Design Patterns
	Building an n-tier layered architecture
		The web layer
		The application layer
		The database layer
	Creating multi-tenant SaaS-based architecture
	Building stateless and stateful architecture designs
	Understanding SOA
		SOAP web service architecture
		RESTful web service architecture
		Building an SOA-based e-commerce website architecture
	Building a serverless architecture
	Creating a microservice architecture
		Real-time voting application reference architecture
	Building queue-based architecture
		Queuing chain pattern
		Job observer pattern
	Creating event-driven architecture
		Publisher/subscriber model
		Event stream model
	Building cache-based architecture
		Cache distribution pattern in a three-tier web architecture
		Rename distribution pattern
		Cache proxy pattern
		Rewrite proxy pattern
		App caching pattern
			Memcached versus Redis
	Understanding the circuit breaker pattern
	Implementing the bulkheads pattern
	Creating a floating IP pattern
	Deploying an application with a container
		The benefit of containers
		Container deployment
	Database handling in application architecture
		High-availability database pattern
	Avoiding anti-patterns in solution architecture
	Summary
Chapter 7: Performance Considerations
	Design principles for architecture performance
		Reducing latency
		Improving throughput
		Handling concurrency
		Apply caching
	Technology selection for performance optimization
		Making a computational choice
			Selecting the server instance
			Working with containers
				Docker
				Kubernetes
			Going serverless
		Choosing storage
			Working with block storage and storage area network
			Working with file storage and network area storage (NAS)
			Working with object storage and the cloud data storage
		Choosing the database
			Online transactional processing (OLTP)
			Nonrelational databases (NoSQL)
			Online analytical processing (OLAP)
			Building a data search functionality
		Making the networking choice
			Defining a DNS routing strategy
			Implementing a load balancer
			Applying autoscaling
	Managing performance monitoring
	Summary
Chapter 8: Security Considerations
	Designing principles for architectural security
		Implementing authentication and authorization control
		Applying security everywhere
		Reducing blast radius
		Monitoring and auditing everything all the time
		Automating everything
		Protecting data
		Preparing a response
	Selecting technology for architectural security
		User identity and access management
			FIM and SSO
			Kerberos
			AD
			Amazon Web Services (AWS) Directory Service
			Security Assertion Markup Language (SAML)
			OAuth and OpenID Connect (OIDC)
		Handling web security
			Web app security vulnerabilities
				Denial of Service (DoS) and Distributed Denial of Service (DDoS) attacks
				SQLi attacks
				XSS attacks
				Cross-Site Request Forgery (CSRF) attacks
				Buffer overflow and memory corruption attacks
			Web security mitigation
				Web Application Firewall (WAF)
				DDoS mitigation
		Securing an application and its infrastructure
			Application and operating system hardening
			Software vulnerabilities and secure code
			Network, firewall, and trusted boundary
			IDS/IPS
				Host-based IDS
				Network-based IDS
		Data security
			Data classification
			Data encryption
			Encryption key management
				Envelope encryption
				AWS Key Management Service (KMS)
				HSM
			Data encryption at rest and in transit
	Security and compliance certifications
	The cloud's shared security responsibility model
	Summary
Chapter 9: Architectural Reliability Considerations
	Design principles for architectural reliability
		Making systems self-healing
		Applying automation
		Creating a distributed system
		Monitoring capacity
		Performing recovery validation
	Technology selection for architecture reliability
		Planning the RTO and RPO
		Replicating data
			Synchronous versus asynchronous replication
			Replication methods
		Planning disaster recovery
			Backup and restore
			Pilot light
			Warm standby
			Multi-site
		Applying best practices for disaster recovery
	Improving reliability with the cloud
	Summary
Chapter 10: Operational Excellence Considerations
	Designing principles for operational excellence
		Automating the operation
		Making incremental and reversible changes
		Predicting failures and responding
		Learning from the mistake and refining
		Keeping operation's runbook updated
	Selecting technologies for operational excellence
		Planning for operational excellence
			IT Asset Management (ITAM)
			Configuration management
		The functioning of operational excellence
			Monitoring system health
				Infrastructure monitoring
				Application monitoring
				Platform monitoring
				Log monitoring
				Security monitoring
			Handling alerts and incident response
		Improving operational excellence
			ITOA
			RCA
			Auditing and reporting
	Achieving operational excellence in the public cloud
	Summary
Chapter 11: Cost Considerations
	Design principles for cost optimization
		Calculating the total cost of ownership
		Planning the budget and forecast
		Managing demand and service catalogs
		Keeping track of expenditure
		Continuous cost optimization
	Techniques for cost optimization
		Reducing architectural complexity
		Increasing IT efficiency
		Applying standardization and governance
		Monitoring cost usage and report
	Cost optimization in the public cloud
	Summary
Chapter 12: DevOps and Solution Architecture Framework
	Introducing DevOps
	Understanding the benefits of DevOps
	Understanding the components of DevOps
		CI/CD
		Continuous monitoring and improvement
		IaC
		Configuration management (CM)
	Introducing DevSecOps
	Combining DevSecOps and CI/CD
	Implementing a CD strategy
		In-place deployment
		Rolling deployment
		Blue-green deployment
		Red-black deployment
		Immutable deployment
	Implementing continuous testing in the CI/CD pipeline
		A/B testing
	Using DevOps tools for CI/CD
		Code editor
		Source code management
		CI server
		Code deployment
		Code pipeline
	Implementing DevOps best practices
	Summary
Chapter 13: Data Engineering and Machine Learning
	What is big data architecture?
	Designing big data processing pipelines
	Data ingestion
		Technology choices for data ingestion
		Ingesting data to the cloud
	Storing data
		Technology choices for data storage
			Structured data stores
				Relational databases
				Data warehousing
			NoSQL databases
				SQL versus NoSQL databases
			Types of NoSQL data store
			Search data stores
			Unstructured data stores
			Data lakes
	Processing data and performing analytics
		Technology choices for data processing and analysis
	Visualizing data
		Technology choices for data visualization
	Understanding IoT
	What is ML?
	Working with data science and ML
	Evaluating ML models – overfitting versus underfitting
	Understanding supervised and unsupervised ML
	Summary
Chapter 14: Architecting Legacy Systems
	Learning the challenges of legacy systems
		Difficulty in keeping up with user demand
		Higher cost of maintenance and update
		Shortage of skills and documentation
		Vulnerable to corporate security issues
		Incompatibility with other systems
	Defining a strategy for system modernization
		Benefits of system modernization
		Assessment of a legacy application
		Defining the modernization approach
		Documentation and support
	Looking at legacy system modernization techniques
		Encapsulation, rehosting, and re-platforming
		Refactoring and rearchitecting
		Redesigning and replacing
	Defining a cloud migration strategy for legacy systems
	Summary
Chapter 15: Solution Architecture Document
	Purpose of the SAD
	Views of the SAD
	Structure of the SAD
		Solution overview
		Business context
		Conceptual solution overview
		Solution architecture 
		Solution delivery
		Solution management
		Appendix section of SAD
	IT procurement documentation for a solution architecture 
	Summary
Chapter 16: Learning Soft Skills to Become a Better Solution Architect
	Acquiring pre-sales skills
	Presenting to C-level executives
	Taking ownership and accountability
	Defining strategy execution and OKRs
	Thinking big
	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
Other Books You May Enjoy
Index