The Definitive Guide to Modernizing Applications on Google Cloud: The what, why, and how of application modernization on Google Cloud

Cover
Title page
Copyright and Credits
Dedication
Contributors
Table of Contents
Preface
Section 1: Cloud-Native Application Development and App Modernization in Google Cloud
Chapter 1: Cloud-Native Application Fundamentals
	The cloud-native ecosystem
	Benefits of cloud-native applications
		Increased speed of delivery
		Increased scalability
		Increased resiliency
		Mixed technology stack and workforce
		Continuous integration and delivery
		Increased automation
	Principles of cloud-native architecture
		Principle 1 – lightweight microservices
		Principle 2 – leveraging automation
		Principle 3 – DevOps culture
		Principle 4 – better to go managed
		Principle 5 – innovate
		Limitations of microservices
	Applying the 12-factor app principles on Google Cloud
		Code base
		Dependencies
		Config
		Backing services
		Build, release, run
		Processes
		Port binding
		Concurrency
		Disposability
		Dev/prod parity
		Logs
		Admin processes
	Summary
Chapter 2: End-to-End Extensible Tooling for Cloud-Native Application Development
	Moving past third-party services – the beauty of end-to-end tooling
	Google Cloud Code
		Features and benefits of Cloud Code
		The role of Cloud Code in the cloud-native app development pipeline
	Google Cloud Build
		Features and benefits of Cloud Build
		The role of Cloud Build in the cloud-native app development pipeline
	Google Container Registry
		Features and benefits of GCR
		The next-gen container registry – Artifact Registry
		The role of GCR in the cloud-native app development pipeline
	Google Cloud Run
		Features and benefits of Cloud Run
		The role of Google Cloud Run in the cloud-native app development pipeline
	Google Kubernetes Engine
		Features and benefits of GKE
		The role of GKE in the cloud-native app development pipeline
	Operations suite
		Features of Google Cloud Monitoring
		Features of Google Cloud Logging
		The role of the Cloud operations suite in the cloud-native app development pipeline
	Summary
Chapter 3: Cloud-Native Architecture Patterns and System Architecture Tenets
	Cloud-native patterns
		The scope of cloud-native patterns
	Solving challenges with cloud-native patterns
		Be proactive, not reactive
		Scaling and performance
		Deployments
		Resiliency and availability
		Monitoring
		Security
	Cloud-native design patterns
		Microservices
		Strangler applications
		Decomposition patterns
		Event-driven patterns
		Command Query Responsibility Segregation
		The saga pattern
		Multiple service instances
		Canary deployments
		Stateless services
		Immutable infrastructure
		Anti-corruption layer
		API composition
		Event sourcing
		The Retry pattern
		Circuit breaker pattern
		The bulkhead pattern
		Using the cloud-native pattern judiciously
	Hybrid and multi-cloud architecture recommendations
		Distributed deployment patterns
		Redundant deployment patterns
	Summary
Section 2: Selecting the Right Google Cloud Services
Chapter 4: Choosing the Right Compute Option
	Five compute options… and Firebase
		Firebase
		Cloud Functions
		GAE
		Cloud Run
		GKE
		GCE
		Pricing
	How important is it to choose the right option?
		Changing compute options
		Making a decision
	Summary
Chapter 5: Choosing the Right Database and Storage
	Storage and database options on Google Cloud – the big three
		GCS – basics
		GCS
		Cloud SQL
		Cloud Firestore (previously Datastore)
		Cloud Spanner
		Cloud Bigtable
		Wrapping up the big five
	Additional storage and database options
		BigQuery
		Filestore
		Persistent disks/local solid-state drive (SSD) (block storage)
		MemoryStore
	Security and flexibility
	Summary
Chapter 6: Implementing a Messaging and Scheduling System
	Understanding the requirements of a messaging system
		Requirement #1: Scalability
		Requirement #2: Extensibility
		Requirement #3: Agility
		Requirement #4: Resiliency
	Introduction to asynchronous messaging
		Messaging products available (open source and cloud native) on the market
		Amazon SQS
		Kafka
		RabbitMQ
		NATS Streaming
		Advantages of asynchronous messaging
	Introduction to Pub/Sub
		What is Cloud Pub/Sub?
		Pub/Sub key features
		Additional benefits
		Pub/Sub Concepts – topics and subscriptions
		Pub/Sub model – fan-in and fan-out
		Pull versus push types – differences and when to use each type
		Getting started with Cloud Pub/Sub
	Introduction to Cloud Tasks
	Introduction to Cloud Scheduler
	Summary
Chapter 7: Implementing Cloud-Native Security
	The principles and concepts of cloud security
		Economy of Mechanism
		Defense in Depth
		Principle of Least Privilege
		Adding infrastructure security layers (revision)
	Cloud IAM
		Traditional access control versus Cloud IAM
	Concepts of IAM
		Entity
		Identity
		Permissions
		Policy
		Authentication and authorization
	Cloud IAM on Google Cloud Platform
		Features of Cloud IAM
	Components of Cloud IAM
		Members
		All authenticated users
		All users
		Resources
		Permissions
		Roles
		IAM policy bindings
	Limitations of Cloud IAM
	Cloud Identity
		Features of Cloud Identity
		Setting up Cloud Identity
	Cloud Identity Platform
		Features of Cloud Identity Platform
	BeyondCorp (a new approach to enterprise security)
	Cloud Identity-Aware Proxy (IAP)
	Summary
Section 3: Rehosting and Replatforming the Application
Chapter 8: Introducing the Legacy Application
	Technical requirements
	The infrastructure architecture
	The software architecture
		Spring Boot
		Thymeleaf
		Bootstrap
		jQuery
	Explaining the software architecture
	Implementing the software
		Spring Boot configuration
	Understanding the layers of the application
		The presentation layer
		The controller layer
		The domain layer
	Validation and defensive programming
	Summary
Chapter 9: The Initial Architecture on Google Compute Engine
	Technical requirements
	The initial infrastructure design
		Designing our network
		Designing our network security
	Creating the modernization project
	Implementing the network
	Implementing the VMs
	Importing the data
	Summary
Chapter 10: Addressing Scalability and Availability
	Technical Requirements
	Designing for scalability and availability
	Using instance templates
	Using managed instance groups
	Using an HTTP(S) load balancer
	Summary
Chapter 11: Re-Platforming the Data Layer
	Designing for scalability and availability
	Using Cloud Memorystore
		Provisioning a Cloud Memorystore instance
		Updating the Regional Managed Instance Group
	Using Cloud SQL
	Using Cloud SQL Proxy
	Using Cloud Spanner
		Provisioning Cloud Spanner
		Updating the build
		Updating the application settings
	Importing data into Cloud SQL
		Exporting data from our MySQL virtual machine
		Importing to Cloud SQL
		Cloud SQL versus Cloud Spanner
	Summary
Chapter 12: Designing the Interim Architecture
	The infrastructure architecture
		Google Identity Platform
		Cloud Pub/Sub
	The software architecture
		Refactoring the frontend and exposing REST services
		Adding Google Identity Platform for identity and authentication
		Publishing events
		Consuming events
		Refactoring to microservices
		Microservice boundaries
	Summary
Chapter 13: Refactoring to Microservices
	Technical requirements
	Analyzing the structure of the application backend
	Refactoring into microservices
	Refactoring the database
	The web frontend
	The Strangler Pattern revisited
		Google HTTP(S) Load Balancer Routing
		Google App Engine Dispatcher
		Apigee API Manager
	Containerizing the deployment units with Docker
	Summary
Section 4: Refactoring the Application on Cloud-Native/PaaS and Serverless in Google Cloud
Chapter 14: Refactoring the Frontend and Exposing REST Services
	Technical requirements
	Creating REST controllers
	Creating an AngularJS web frontend
		Modules
		Components
		Routing
		Services
	Authenticating in the web frontend
		Setting up Firebase and Google Identity Platform
		Initializing Firebase Authentication
		Router updates
		The authentication cycle
		The signout controller
	Validating the authentication token in the REST controllers
		The authentication filter
	Summary
Chapter 15: Handling Eventual Consistency with the Compensation Pattern
	Technical requirements
	The distributed transaction problem
	The compensation pattern
	Creating topics and subscriptions with Google Cloud Pub/Sub
	Implementing eventual consistency and the compensation pattern
	Deploying and testing the application
	Summary
Chapter 16: Orchestrating Your Application with Google Kubernetes Engine
	Technical requirements
	Introducing GKE
		Modes of operation
		Creating a GKE cluster
	Configuring the environment
		Kubernetes ConfigMaps and Secrets
	Deploying and configuring the microservices
		Kubernetes Pods
		Kubernetes ReplicaSets
		Kubernetes Deployments
		Kubernetes Horizontal Pod Autoscalers
		Kubernetes Services
		Automating the deployment of our components
	Configuring public access to the application
		Kubernetes-managed certificates
		Kubernetes Ingress
	When to use GKE
	Summary
Chapter 17: Going Serverless with Google App Engine
	Technical requirements
	Introducing Google App Engine
		Google App Engine standard environment
		Google App Engine flexible environment
		Components of App Engine and the hierarchy of an application deployed on App Engine
	Deploying containers to the App Engine flexible environment
		Application configuration updates
		Deployment configuration
		Automating deployment
	When to use Google App Engine
	Summary
Chapter 18: Future Proofing Your App with Google Cloud Run
	Technical requirements
	Cloud Run
		The Knative stack
		Cloud Run environments
	Deploying containers to Google Cloud Run
		Frontend configuration
		Service manifest
		Google Cloud Build
		Domain name mapping
	When to use Cloud Run
	Summary
Appendix A: Choosing the Right Migration Strategy
	Step 1 – assess
		Cataloging existing applications
		Educating teams
		Choosing what to migrate first
		Capable and innovative teams
		The effort required for migration
		License restrictions and compliance
		Can afford downtime
	Step 2 – plan
		Migration paths versus migration strategies
		Choosing the right migration path
	Step 3 – migrate
		Transferring your data
		Deploying workloads
		Setting up automated and containerized deployments
	Step 4 – optimize
		Letting internal teams takeover
		Setting up monitoring
		Leveraging managed services and automation
		Cost and performance
Appendix B: Application Modernization Solutions
	Modernizing Java apps
		What is Google Anthos?
	Preparing to modernize Java apps
		Phase 1 – containerizing Java applications
		Phase 2 – Refactoring and re-platforming
	Modernization strategies (the 6 Rs of modernization)
		Retire, retain, and re-architect
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