Premium
Title Page
1/7/2025
Copyright Page
1/7/2025
Dedication Page
1/7/2025
About the Author
1/7/2025
About the Reviewers
1/7/2025
Acknowledgement
1/7/2025
Preface
1/7/2025
Table of Contents
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Section 1: Cloud Services by Responsibility
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1. Responsibilities and Utility of a Cloud Platform
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Introduction
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Structure
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Objectives
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General infrastructure considerations
1/7/2025
Identity and authentication
1/7/2025
Scalability
1/7/2025
Asynchronous processing
1/7/2025
Data permanence
1/7/2025
Response delivery
1/7/2025
Analysis of infrastructure considerations
1/7/2025
Interdependence of platform responsibilities
1/7/2025
Assigning roles by platform
1/7/2025
Google Cloud Platform product overview
1/7/2025
Top level categories of Google Cloud services
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Computing power
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Databases
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Storage
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Networking
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Data analytics
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Security and identity
1/7/2025
Developer tools
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Artificial intelligence and machine learning
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Components outside of cloud services
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Conclusion
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2. Dividing up Features of a Cloud Backed Application
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Enumerating responsibilities and dependencies
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Different, valid points of view
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Grouping by topological locality
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Grouping by feature affinity
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Determining feature affinity and proximity
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Grouping by feature performance considerations
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Understanding feature requirements
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Defining application feature composition
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Pertinent qualities of an infrastructure service or component
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Describing infrastructure options
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3. Determining the Infrastructure to Build Features Upon
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Request funneling to scale to O(N)!
1/7/2025
Urgency versus importance
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Eventual consistency in distributed systems
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A case study in eventual consistency
1/7/2025
Guaranteeing user-visible responsiveness
1/7/2025
Horizontal scaling via Pub/Sub
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Transaction guarantees
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Beyond the base transaction model
1/7/2025
Security, privacy and permanence
1/7/2025
Cybersecurity
1/7/2025
Security in Google Cloud Platform
1/7/2025
Data privacy
1/7/2025
4. Choosing Between GCP Options
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Choosing a server-side runtime platform
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The impact of compute platform selection
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Google Application Engine
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Google Cloud Run
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Compute Engine
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Virtual machines
1/7/2025
Compute product comparison
1/7/2025
GCP Compute resource management
1/7/2025
Compute resources offered
1/7/2025
Determining where best to store your data
1/7/2025
Cloud Firestore
1/7/2025
Cloud Structured Query Language
1/7/2025
Bigtable
1/7/2025
Bigtable performance
1/7/2025
Spanner
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Cloud Storage
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Firebase Authentication
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Firebase authentication features
1/7/2025
Google Cloud IAM
1/7/2025
Roles versus users
1/7/2025
Identity Platform
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Identify Platform authentication features
1/7/2025
Asynchronous message handling
1/7/2025
Pub/Sub
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Scalability of a messaging architecture
1/7/2025
Cloud Tasks
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Section 2: Cloud Backed Application Architecture
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5. Client-side Technology Choices
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Native mobile applications
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Android development tools
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iOS development tools
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Cross-platform mobile frameworks
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Flutter
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React Native
1/7/2025
Kotlin Multiplatform
1/7/2025
Web applications
1/7/2025
Desktop client applications
1/7/2025
Native desktop development
1/7/2025
Cross-platform desktop development
1/7/2025
In-browser client applications
1/7/2025
Web application programming languages
1/7/2025
Angular
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React and ReactDOM
1/7/2025
Web application development tools
1/7/2025
GCP support for web application clients
1/7/2025
Chatbots and voice agents
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Chatbots and GCP
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Chatbot voice frontends
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6. Cloud Services at the Backend Border
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Maintaining backend agnostic clients
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General API design principles
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Special considerations for client or cloud interfaces
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Visibility levels to the client
1/7/2025
Planning migration to substitute or equivalent cloud services
1/7/2025
Vendor lock-in
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Product obsolescence
1/7/2025
Designing for migration
1/7/2025
Visibility between cloud services
1/7/2025
Dependencies between cloud service products
1/7/2025
Isolating cloud service products
1/7/2025
Identifying and packaging tightly coupled services
1/7/2025
7. Frontends at the Client Border
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Client-side logic
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Avoid multiple sources of truth
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Presentation of the user interface
1/7/2025
Capturing user input, selection and entry
1/7/2025
Hiding sensitive logic from observation
1/7/2025
Making frequently changed code easy to deploy
1/7/2025
Defining client requests to the backend
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Backends for frontends
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Blocking and non-blocking request responses
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Identifying asynchronous methods
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Client technologies for asynchronous processing
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Pushback and handling unexpected responses
1/7/2025
Defining and handling non-user-initiated actions
1/7/2025
Use cases for server-initiated actions
1/7/2025
Mechanisms for receiving server-generated traffic
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Section 3: End-to-End: A Global Voting System
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8. Making a Voting System Available and Reliable
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Digital voting system overview
1/7/2025
Overview of an online talent competition
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Voting process
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Scalability requirements
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Voting system performance requirements
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Usage models
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Google Cloud Platform regional boundaries
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Voting system demand by continent
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Data aggregation
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Aggregating distributed votes in a global system
1/7/2025
Accessibility
1/7/2025
Strategically relocating resources
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Optimizing the application to fit available resources
1/7/2025
Redesigning the application
1/7/2025
Creating the package and directory structure codelab
1/7/2025
Platform components and initial files
1/7/2025
Voting API
1/7/2025
9. Identifying the Stress Points of our Voting System
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Types of failures
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Scope of a failure
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Progression
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Causes of a failure
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Failure categorization
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Assessing impact
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Determining short-term cost of an outage
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The long-term cost of an outage
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Monitoring, detection and notification
1/7/2025
Observing first and then controlling
1/7/2025
Monitoring terminology
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Types of metrics
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Key reliability metrics
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Monitoring distributed systems
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Monitoring GCP applications
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Performance watchpoints in the voting application
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Incident response
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Matrix of failure modes and appropriate measures
1/7/2025
Implementation of the Vote Ingester API codelab
1/7/2025
Project considerations in setting up the repository
1/7/2025
Web client and common code
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Cloud-based code
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Google Cloud project configuration
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Firebase project configuration
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GCP Monitoring
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10. Securing All User Votes
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Demand modeling
1/7/2025
Independent cycles of demand
1/7/2025
Load balancing
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Types of load balancers
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Load balancing algorithms and considerations
1/7/2025
Load balancing in Google Cloud Platform
1/7/2025
Selecting voting system load balancers
1/7/2025
Employing message queues to pool requests
1/7/2025
Creating Pub/Sub resources for votes
1/7/2025
Publishing votes to Pub/Sub
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Asynchronous processing of requests
1/7/2025
Processing votes published to Pub/Sub
1/7/2025
Scaling backend processing
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Applying GCP scaling
1/7/2025
Vote Processor deployment
1/7/2025
Monitoring of backend performance
1/7/2025
Dispatching user requests asynchronously via Pub/Sub codelab
1/7/2025
Asynchronous vote processing components
1/7/2025