Cloud Native Architecture and Design: A Handbook for Modern Day Architecture and Design with Enterprise-Grade Examples

Table of Contents
About the Author
About the Technical Reviewer
Acknowledgments
Introduction
Part I: The Cloud Native Journey, Principles, and Patterns
	Chapter 1: Introduction to Cloud Native Architecture
		Introduction to Cloud Native
		Cloud Adoption Across Industries
		Reducing Costs
		Adopting the Cloud Native Mindset
		What Is Cloud Native?
		Cloud Native Maturity Model
			Cloud Enablement Wave
			Cloud Native Transformation Wave
			Scalability and Flexibility Advantage
			Cloud Native Culture and Innovation Wave
				Blockchain as a Service
				Digital Twin
				Zero Trust Architecture
				5G
				Quantum Computing
		Elements of Cloud Native Computing
			Microservices Architecture
			Serverless Architecture
			Event-Driven Architecture
			Cloud Computing
			Containers
			Agile Development
			DevSecOps
		How Is Cloud Native Different Than Cloud-Enabled?
		Cloud Native Journey
			Start with Lift and Shift
			Re-engineer Migration
		Benefits of Cloud Native
		Cloud Native Organization and Culture
		How Is Cloud Native Architecture Embraced Across Industries?
			Migrate
			Accelerate
			Scale and Innovate
		What Is a Software Architect’s Role in Cloud Native?
		Summary
	Chapter 2: Cloud Native Services
		Evolution of Infrastructure Services
			Mainframe Services
			Minicomputer Services
			Personal Computing Service
			Client-Server Service
			Enterprise Computing Service
			Cloud and Mobile Computing Services
		IT Infrastructure Laws and Prediction
			Moore’s Law
			The Laws of Mass Digital Storage
			Metcalfe’s Law
			Communication Cost and Internet
		Evolution of Servers
			Bare-Metal Servers
			Virtual Machine Revolution
				Adoption of Virtual Machines
				Virtual Machines in the Cloud
			Container Revolution
		Understanding Cloud Services
			Infrastructure as a Service
			Platform as a Service
				PaaS Taxonomy
				PaaS Architecture Styles
				PaaS Deployment Model
			Software as a Service
				SaaS Limitations
				Architectural Considerations: How to Decide on a Custom vs. SaaS Platform
		Cloud Computing Deployment Models
			Public Cloud
			Private Cloud or On-Premises Cloud
			Community Cloud
			Hybrid
		Cloud Services
		Summary
	Chapter 3: Cloud Native Architecture Principles
		What Are Architecture Principles?
		Cloud Native Design Principles
			API First Principle
			Monolithic Architecture Principle
			Polylithic Architecture Principle
				Applying the Polylithic Principle in Architecture
				Properties of Polylithic Principles
			Polyglot Persistence Principle
				Applying the Polyglot Persistence Principle in Architecture
			Modeled with Business Domain Principle
			Consumer First Principle
			Decentralize Everything Principle
			Culture of Automation Principle
			Always Be Architecting Principle
			Interoperability Principle
			Digital Decoupling Principle
			Single Source of Truth Principle
			Evolutionary Design Principle
		Cloud Native Runtime Principles
			Isolate Failure Principle (IFP)
			Deploy Independently Principle
			Be Smart with State Principle
			Location-Independent Principle
			Design for Failure Principle
		Security Principles
			Defense in Depth Principle
			Security by Design Principle
				SQL Injection
				Cross-Site Scripting (XSS)
		Software Engineering Principle
			Products Not Projects Principle
			Shift-Left Principle
				Shift-Left Security
				Shift-Left Performance
		Container Principles
			Single Concern Principle
			High Observability Principle
			Lifecycle Conformance Principle
			Image Immutability Principle
			Process Disposability Principle (PDP)
			Self-Containment Principle
			Runtime Confinement Principle
		Principles of Orthogonal
			Cohesion
				Types of Cohesion
				Function Cohesion
				Sequence Cohesion
				Communication Cohesion
				Procedural Cohesion
				Temporal Cohesion
				Logical Cohesion
				Coincidental Cohesion
				Applying High Cohesion to Software Design
			Coupling
				Types of Coupling
					No Coupling
					Message Coupling
					Data Coupling
					Stamp Coupling (Data-Structured Coupling)
					Control Coupling
					External Coupling
					Common Coupling (Global Coupling)
					Content Coupling (Pathological Coupling)
					Law of Demeter (LoD) or Principle of Least Knowledge
					Applying Loose Coupling to Software Design
		Software Quality Principles
			KISS Principle
				Applying KISS to Software Design
			Don’t Repeat Yourself
				Duplication Is Waste
				The DRY Principle in Polylithic and Polyglot Architecture
				How does the DRY principle reduce maintenance costs?
			Isolate
				What do we mean by isolation?
				Isolation in Cloud Native Applications
				Applying Isolation to Software Design
			Separation of Concern
				Applying SoC to Software Design
			Use Layering
				Layering in Traditional Application
				Layering in Cloud Native Application
				Applying Layering to Software Design
			Information Hiding
				Why Information Hiding?
				Applying Information Hiding to Software Design
			You Aren’t Gonna Need It
				Idea of YAGNI
				How to Decide What You Need
		SOLID Design Principles
			Single Responsibility Principle
				Applying Single Responsibility to Microservice Design
			Open-Closed Principle
				Applying Open-Closed to Microservices
			Liskov Substitution Principle
				Applying Liskov Substitution to Microservices Design
			Interface Segregation Principle
			Dependency Inversion Principle
			Summary
	Chapter 4: Cloud Native Architecture and Design Patterns
		Evolution of Design Patterns
		What Are Software Patterns?
		Architecture Style, Architecture Pattern, and Design Pattern
		Anti-pattern
		Cloud Native Data Management Pattern for Microservices
			Event Sourcing Pattern
				Stream
				Event Store
			Command and Query Responsibility Segregation Pattern
				Application Layer Command and Query
				Command and Query in the Database
			Data Partitioning Pattern
				Horizontal Partitioning or Sharding
				Range Based or Interval Partitioning/Sharding
				Hash Partitioning/Sharding
				List Partition
				Round-Robin Partitioning
				Vertical Partitioning
			Data Replication
				Leader-Based or Leader-Followers Replication
					How are the leaders selected?
				Quorum-Based Replication
		Cloud Native API Management Patterns for Microservices
			Idempotent Service Operation
			Optimistic Concurrency Control in API
			Circuit Breaker
			Service Discovery
				Client-Side Discovery Pattern
				Server-Side Discovery Pattern
			Service Versioning
				URI Versioning
				Header Versioning
		Cloud Native Event-Driven Patterns for Microservices
			Asynchronous Nonblocking I/O
				What is synchronous and asynchronous messaging?
			Stream Processing
		Cloud Native Design Pattern for Microservices
			Mediator
			Orchestration
			Strangler Pattern
			Bulkhead Pattern
				How does the bulkhead pattern work?
			Anti-corruption Pattern
		Cloud Native Runtime Pattern for Microservices
			Fail Fast
			Retry
			Sidecar
			Init Containers
			Saga Pattern
				Event Driven and Choreography
				Orchestrator-Based Saga Pattern
		Summary
Part II: Elements of Cloud Native Architecture and Design
	Chapter 5: Microservices Architecture and Design
		Evolution of Microservices
			What Is a Microservices Architecture?
		Characteristics of Microservices
			Organized Around Business Capabilities
			Autonomous
			Smart Endpoints and Dumb Pipes
				What Is a Service Mesh?
				Smart Endpoints and Dumb Pipes with Service Meshes
				What Is an Event Mesh?
			Resilience in Microservices
				Resilience Capabilities
				How to Build Resilient Microservices?
			Elasticity in Microservices
			Distributed State
				How to Handle Distributed State with Asynchronous microservices
			Independently Deployable
			Decentralization
				Decentralized Governance
				Decentralized Data
			Automation
			Containerization
			Design for Failure
				How Do You Design a Microservice for Failure and Stability?
			Living Continuous Design
			Self-Healing
		Hexagonal Architecture
		Enterprise Microservices Examples
			Case Study: Trade Finance
				What Is Trade Finance?
				Trade Finance Ecosystem
				Trade Finance Functional Architecture
			Case Study: Collateral Management
				Collateral Management Functional Architecture
				Collateral Management Architecture
		Microservices and User Interface: Micro Front End
			Routing
			Composition
			Communication
			Pros and Cons of Micro Front Ends
		Microservice Architecture in Artificial Intelligence
			AI Subcategories
			Microservices Vertical Components: Speech AI
		Summary
	Chapter 6: Event-Driven Architecture
		Evolution of Event-Driven Architecture
			Tightly Coupled World to Loosely Coupled World
			Message Broker World to Event World
		Event
			Business Events
			Technical Events
			Processing an Event
			Event Handling in Domain Context
			Event Governance
		What Is Event-Driven Architecture?
			How Does Event-Driven Architecture Work?
		Event-Driven Topologies
			Mediator Topology
			Broker Topology
				Choice of Topology
		Characteristics of Event-Driven Architecture
		Event-Driven Messaging Models
			Event Messaging
			Event Streaming
		Event Processing Styles
			Simple Event Processing
			Event Stream Processing
			Complex Event Processing
		Event-Driven Architecture Maturity Model
		Decoupling Use Case by Using Event-Driven Architecture
			Make Data Accessible
				How to Get Events and Make Data Accessible?
				Where to Store Events?
				How to Get Data?
				CDC
		Real-Time Interactivity
		How to Use Existing Message Queues with Event Streams?
		Transaction Management in Event-Driven Microservices
			Two-Phase Commit in Cloud Native Services
			Transactions with Events
		Event-Driven Microservices Interaction
		Interaction Between Microservices
			Service Mesh
				Service Mesh Implementation
				Advantages and Disadvantages of Service Meshes
			Event Mesh
				Characteristics of Event Mesh
				Event Mesh Capabilities
				How Do Event Meshes Work?
				Event Mesh in a Cluster of Brokers
				Event Mesh’s Control Plane
		Box- and Port-Style Event-Driven Architecture
			Characteristics of Box- and Port-Style Architecture
		DevOps for Events
		Event Security
			Field-Level Encryption Consideration
		Cloud Events
		Summary
	Chapter 7: Serverless Architecture
		Evolution of Serverless
		What Is Serverless Computing?
		Essential Components of Serverless
		Serverless and Event-Driven Computing
		Serverless Design Principles
			Stateless Functions
			Push-Based and Event-Driven Pipelines
			Config: Store Config in the Environment
			Backing Services: Treat Backing Services as Attached Resources
			Concurrency: Scaling Out via the Process Model
			Disposability: Maximize Robustness with Quick Startup and Shutdown
		Key Considerations for Serverless Computing
		Why Use Serverless Architecture?
		Best Practices of Serverless Architecture
		Types of Serverless Architecture
			Function as a Service
				AWS Lambda
					Reference Architecture
					Ecommerce Reference Architecture
					Best Practices of Lambda
				Azure Functions
					Reference Architecture
					Best Practices of Azure Functions
				Google Cloud Functions
					Reference Architecture
					Best Practices of Google Function
				FaaS Platform Evaluation Criteria
			Backend as a Service or Mobile Backend as a Service
				Pros and Cons of BaaS
		Function Deployment
		When to Use Serverless
		Advantages of Serverless Architecture
			Reduced Operational Cost
			Optimized Resource Utilization
			Faster Time to Market
			Ability to Focus on User Experience
			Fits with Microservices
		The Drawbacks of Serverless Architecture
			Standardization
			Operations Management
			Tooling Support
			Security
			Long-Term Tasks
		Future of Serverless
		Summary
	Chapter 8: Cloud Native Data Architecture
		Rethinking Data in a Cloud Native World
		Cloud Native Data Persistence Layer
			Cloud Native Data Characteristics
		How to Select a Data Store
			Objects, Files, and Blocks
			Databases
				Relational Database
				Key-Value
				Document Database
				Wide-Column Database
				Time-Series Database
				Graph Database
				Event Store Database
				Search Engine Database
		Data Replication
			Physical Database Replication
			Logical Database Replication
				Full Data Refresh
				Partial Data Refresh
				Change Data Capture
					Log-Based CDC
			Extract, Transfer, and Load
				Extraction
				Transform
				Load
		Decoupling Big Data Management from Distributed Data Meshes
			Step 1: Self-Service Data Infrastructure as a Platform
			Step 2: Data as a Product
			Step 3: Data Infrastructure as a Platform
			Step 4: Domain-Oriented Decentralized Data Ownership and Architecture
			Step 5: Data Governance
		Data Processing with Real-Time Streaming for Analytics
			Lambda Architecture
				How Does the Lambda Architecture Work?
			Kappa Architecture
			Microservices in Data Processing with Real-Time Streaming for Analytics
		Mobile Platform Database
		Intelligent Data Governance and Compliance in the Cloud Native World
			Why Data Governance?
			What Is Data Governance?
			Governance Framework
				Change Management
				Intelligent Tooling
				Operating Model
				Decentralization
				Secure
		Summary
	Chapter 9: Designing for “-ilities”
		Why Do You Need “-ilities”?
			Partial List of “-ilities”
		Designing for Security
			Defense in Depth
			The CIA Triad
			Policy as Code
			Zero-Trust Security
			Decentralized Identity
			Validating Input
			Design for Threats
			Naive Password Complexity Requirements
			Compliance as Code
			Shift-Left Security
			Single Pane of Glass for Audit
			Homomorphic Encryption
			Fail Securely
			Secure APIs
		Designing for Elasticity
		Designing for Resilience
		Designing for Sustainability
			The JEVONS Paradox in Cloud Native
			Sustainability Approaches
			Deployment Environment
			Software Engineering
				UI Architecture
			Sustainability Assessment
		Designing for Failure
			Infrastructure
			Communication
			Dependencies
			Internal
		Designing for Reliability
			Pareto Chart
		Designing for High Availability
			Active-Active Deployments
			Active-Passive Deployments
		Designing for the Customer
		Designing for Interoperability
		Designing for Events
		Designing for Observability
		Designing for Portability
		Designing for Ethics
		Designing for Accessibility
			Accessibility Guidelines and Standards
		Designing for Automation
		Designing for Maintainability
		Designing for Usability
		Summary
Part III: Modernizing Enterprise IT Systems
	Chapter 10: Modernize Monolithic Applications to Cloud ­Native
		What Is Decoupling?
		Technical Debt
			How Are Technical Debts Accumulated?
			How Is Technical Debt Impacting Your Enterprise?
			How to Decide on Decoupling?
				Decoupling Model
		Decoupling
			Decoupling Approach
			Decoupling Plan
			Decoupling Principles
			Decoupling Business Case
			Decoupling Strategies
		Domain-Driven Design
			How Does Domain-Driven Design Manage Complexity?
			What Is a Domain?
			Goals of Domain-Driven Design
			Domain-Driven Design Model
				Strategic DDD
				Tactical DDD
			Guiding Principles of DDD
		Event Storming
			Key Roles in an Event Storming Workshop
			Event Storming Exercise
				Step 1: Identify the Objectives
				Step 2: Event Map: Capture Domain Events
				Step 3: Event Map: Identify Commands, Triggers, and Read Models
				Step 4: Event Map: Identify Aggregators
				Step 5: Context Map: Identify the Bounded Context
					How Does a Bounded Context Communicate?
					Ubiquitous Language
					Tactical Implementation of DDD
				Step 6: Microservices Identification
					Entity
					Value Objects
					Aggregates
					Domain Model to Microservices
					API Model
			Value of Domain-Driven Design
				The Business Value of DDD
				Drawbacks of DDD
				Where DDD Is Not Useful
		Summary
	Chapter 11: Enterprise IT Assessment for a Cloud Native Journey
		Introduction
		Assessment
			What Is an Assessment Used For?
			Assessment Objectives
			Assessment Execution Approach and Key Activities
		Cloud Native Assessment
			When to Consider a Cloud Native Assessment
			Cloud Native Maturity Assessment Model
		Detailed Architecture Assessment
			Assessment Usage
			Architecture Assessment Model
			Assessment Questions Template
		Automation Maturity Assessment
			Automation Maturity Assessment Model
			Automation Maturity Assessment Questionnaire Template
		Summary
	Chapter 12: “-ilities” Fitness Function
		What Is a Fitness Function?
		Categories of Fitness Functions
			Atomic vs. Holistic
			Triggered vs. Continuous
			Static vs. Dynamic
			Automated vs. Manual
			Temporal
			International vs. Emergent
			Domain-Specific
			Design-Time Fitness Function
			Runtime Fitness Function
		Execution of the Fitness Function
			Manual Execution
			Automated Execution
		Fitness Function Identification
			Fitness Function: Coupling and Cohesion
			Fitness Function: Security
			Fitness Function: Extensibility, Reusability, Adaptability, and Maintainability
			Fitness Function: Performance
			Fitness Function: Resiliency
			Fitness Function: Scalability
			Fitness Function: Observability
			Fitness Function: Compliance
		Fitness Function Metrics
		Review Function Metrics
		Summary
Part IV: Cloud Native Software Engineering
	Chapter 13: Enterprise Cloud Native Software Engineering
		Cloud Native and Traditional Application Engineering
		Intelligent Software Engineering
		From Project to Product
		Organization Transformation
		Agile Software Development Methodologies
			Hypothesis-Driven Development
				Why Do You Need a Hypothesis?
				Methodology Steps
				Hypothesis Example
				Framing Hypothesis
				Culture of Hypothesis
			Test-Driven Development
				Why TDD?
				TDD Cycle
				Steps of TDD
				Factors to Consider for TDD
				Drawbacks of TDD
			Behavior-Driven Development
				How BDD Helps You to Solve Problems
				BDD Principles and Practices
				BDD Process
				BDD Specification
				Transition to BDD
				Benefits of BDD
				Drawbacks of BDD
			Feature-Driven Development
				Why FDD?
				FDD Process
				Feature Specification
					Feature Set
					Subject Area
				Benefits of FDD
				Drawbacks of FDD
		Architecture in the Agile Methodology
		Waterfall to Agile Transformation
		Summary
	Chapter 14: Enterprise Cloud Native Automation
		Introduction
		DevOps Today and Tomorrow
		From DevOps to DevSecOps
			Driver for Shift-Left Security
		Automation Principles and Best Practices
		Site Reliability Engineering
		DevSecOps
			Continuous Integration
			Continuous Delivery
			Continuous Deployment
		DataOps
			DataOps Principles
			DataOps Pipeline
		DevNetOps
			Network Operation and Challenges
			Why You Need DevNetOps?
			Network Reliability Engineering
			DevNetOps Pipeline
		DevOps in the Cloud
			AWS Cloud
			Azure Cloud
			Google Cloud
		DevOps Transformation
		Summary
	Chapter 15: AI-Driven Development
		Introduction
		Unique AI Challenges
		Why AI-Driven Development?
		AI-Driven Principles at a Glance
		Approach to AI
		AI Governance
			AI Framework
			AI Governance Measurement
			Governance Process
			Governance Model
		How to Train AI-Enabled Frameworks?
		AI-Driven Methodology
			AI Use Cases
			Discovery and Piloting
			AI Project Execution
			Deploy and Industrialize
		AI and ML in DevOps
			AI and ML in Code Management
				Source Code Progress
					DeepCode.AI
					Codota
				Quality Checks
				Continuous Feedback
				Kubeflow
				Alert Monitoring
		Summary
Part V: Cloud Native Infrastructure
	Chapter 16: Containerization and Virtualization
		Introduction
			What Is Cloud Native Infrastructure?
			Cloud Native Environment Characteristics
		Cloud Virtualization
			How Does Virtualization Work?
			Types of Virtualization in the Cloud
			What Applications and Services Are Commonly Virtualized?
			Cloud Native and Virtual Machines
		Containerization
			What Is a Container Image?
			Container Architecture
			Container Principles
			Container Patterns
				Container Security
				Logging Mechanism
				Stateless
				Immutable
				Privileged Containers
				Monitoring
				Running Container as Root
				Image Version
				Container Networking
				Container Lifecycle Management
			Container Benefits
			Container Adoption Best Practices
			Containers in an Enterprise
		Container Orchestration
			Types of Orchestration Tools
				Docker Swarm
				Apache Mesos
				Kubernetes
					Orchestration Tool Comparison
			Kubernetes Features
			Kubernetes Principles and Patterns
				Predictable Demands
				Declarative Deployment
				Health Probe
				Automated Placement
				Singleton Service
				Init Container
				Sidecar
			Running a Cloud Native Application on the Container and Kubernetes Strategy
			Kubernetes Maturity Model
				Prepare
				Transform
				Deploy
				Build Confidence
				Improve Operations
				Measure and Control
				Optimize and Automate
			Service Meshes and Kubernetes
			Stateful Workloads on Kubernetes
			Kubernetes Multitenancy
			Kubernetes Secrets
			Kubernetes as a Service
				Google Kubernetes Engine
				Amazon Elastic Kubernetes Service
				Azure Kubernetes Services
				Red Hat OpenShift
				VMware Tanzu
		Summary
	Chapter 17: Infrastructure Automation
		What Is Infrastructure Automation?
		What Can You Automate?
		What Is Infrastructure as Code?
		IaC in Build Pipeline Automation
			Capture Requirements
			Prepare Automation Code
			Set Up Infrastructure
			Install OS
			Set Up Network and Storage
			Deploy Services
		Define Everything As Code
			How Do You Select an IaC Tool?
			What Coding Language Can You Use?
		IaC Example
		IaC Tools
			Terraform
			Ansible
			SaltStack
			Chef
			Puppet
			CFEngine
			AWS Cloud Formation
			IaC Tools Comparison
		Summary
Part VI: Cloud Native Operations
	Chapter 18: Intelligent Operations
		Introduction
		Why Do You Need Intelligent Operations?
		Elements of Intelligent Operation
			Data-Driven Approach
			Applied Intelligence
			Cloud Enablement
			Right Talent and Skill
			Smart Partnership
		AIOps
			Central Functions
				Artificial Intelligence
				Data
				Automation
					Anomaly Detection
					Event Correlation
					IT Service Management (ITSM)
			Example Use Case of AIOps
			Traditional Operations
			AIOps-Based Operation
			Capabilities of AIOps
			AIOps Transformation
				AIOps Strategy
				AIOps Transition
				AIOps Transformation
			Benefits of AIOps
		ChatOps
			ChatOps Benefits
			Types of ChatOps
				Group Chat
				Bots
			ChatOps in Service Support
			ChatOps (Bot) Architecture
			Industry Example Use Cases
				Group Chat Use Case: Microsoft Teams–Based Chatbot with AI Is Integrated with ServiceNow
				Chatbot Use Case: Payment Industry to Resolve Billing Queries and Create Case Management Requests
		Summary
	Chapter 19: Observability
		Introduction
			Difference Between Monitoring and Observability
		Full-Stack Observability
			Connected Across Capabilities
			One Source of Truth
			Visualization
		Observability and Cloud Native Services
		Observability in Kubernetes
		Observability and DevOps
			Common Use Cases for Observability with AIOps
		Guidance to Choose Observation Tools
		Benefits of Observability
		Observability, Monitoring, and Machine Learning Models
			Algorithms Help in Observability
			Workflow Steps for ML
		Summary
Part VII: Cloud Native Features
	Chapter 20: Cloud Native Trends
		Cloud Native Trends
			Designing for “-ilities”
			Cloud Native Architecture
			Open Application Model Specification
			Web Assembly
			Data Gateways
			HTTP/3
			RSocket and Reactive Streams
			Low Code/No Code
			Actor Model
			Kubernetes on the Edge
			GitOps
		General Trends Across Industry
			5G
				5G Technology
				5G Features
				Advantages of 5G
				Cloud Native and 5G: Network Slicing
			Digital Twin
				Why a Digital Twin?
				Digital Twin Implementation
			Quantum Computing
				Why Quantum Computing?
				Potential Use Cases
			Extended Reality
			Edge Computing
		Summary
Index