Visualizing Google Cloud

Visualizing Google Cloud

by Priyanka Vergadia
Released April 2022
Publisher(s): Wiley
ISBN: 9781119816324

Read it now on the O’Reilly learning platform with a 10-day free trial.

O’Reilly members get unlimited access to books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.

Start your free trial

Book description

Easy-to-follow visual walkthrough of every important part of the Google Cloud Platform

The Google Cloud Platform incorporates dozens of specialized services that enable organizations to offload technological needs onto the cloud. From routine IT operations like storage to sophisticated new capabilities including artificial intelligence and machine learning, the Google Cloud Platform offers enterprises the opportunity to scale and grow efficiently.

In Visualizing Google Cloud: Illustrated References for Cloud Engineers & Architects, Google Cloud expert Priyanka Vergadia delivers a fully illustrated, visual guide to matching the best Google Cloud Platform services to your own unique use cases. After a brief introduction to the major categories of cloud services offered by Google, the author offers approximately 100 solutions divided into eight categories of services included in Google Cloud Platform:

  • Compute
  • Storage
  • Databases
  • Data Analytics
  • Data Science, Machine Learning and Artificial Intelligence
  • Application Development and Modernization with Containers
  • Networking
  • Security

You’ll find richly illustrated flowcharts and decision diagrams with straightforward explanations in each category, making it easy to adopt and adapt Google’s cloud services to your use cases. With coverage of the major categories of cloud models—including infrastructure-, containers-, platforms-, functions-, and serverless—and discussions of storage types, databases and Machine Learning choices, Visualizing Google Cloud: Illustrated References for Cloud Engineers & Architects is perfect for Every Google Cloud enthusiast, of course. It is for anyone who is planning a cloud migration or new cloud deployment. It is for anyone preparing for cloud certification, and for anyone looking to make the most of Google Cloud. It is for cloud solutions architects, IT decision-makers, and cloud data and ML engineers. In short, this book is for YOU.

Table of contents

  1. COVER
  2. TITLE PAGE
  3. INTRODUCTION
    1. Reader Support for This Book
  4. CHAPTER ONE: Infrastructure
  5. CHAPTER TWO: Storage
  6. CHAPTER THREE: Databases
    1. Relational Databases
    2. Nonrelational databases
    3. Which One Is Best?
    4. How to Set Up Cloud SQL
    5. Reliability and Availability
    6. Migrating an Existing MySQL Database to Cloud SQL
    7. Security and Compliance
    8. Cloud SQL in Action
    9. How Does Spanner Work?
    10. How Does Spanner Provide High Availability and Scalability?
    11. How Do Reads and Writes Work?
    12. How Does Spanner Provide Global Consistency?
    13. What Is Firestore?
    14. Document-Model Database
    15. How Do You Use Firestore?
    16. Some Cloud Bigtable Features
    17. Scale and High Availability (HA)
    18. How Does It Optimize Throughput?
    19. What are Your Application's Availability Needs?
    20. Features and Capabilities
    21. Use Cases
  7. CHAPTER FOUR: Data Analytics
    1. 5 Steps to Create a Data Analytics Pipeline
    2. How Does Pub/Sub Work?
    3. Pub/Sub Features
    4. Pub/Sub Use Cases
    5. Main Components
    6. How Does Cloud IoT Core Work?
    7. Design Principles of Cloud IoT Core
    8. Use Cases
    9. How Does Data Processing Work?
    10. How to Use Dataflow
    11. Dataflow Governance
    12. How Does Dataproc Work?
    13. Migrating HDFS Data from On-Premises to Google Cloud
    14. What Is Data Preparation?
    15. How Does Dataprep Work?
    16. BigQuery Unique Features
    17. How Does It Work?
    18. BigQuery Storage Internals
    19. Dremel: BigQuery’s query engine
    20. Security
    21. Cost
    22. Data Integration Capabilities
    23. How Does Data Catalog Wor?
    24. Data Catalog Architecture
    25. Data Governance
    26. How Does Cloud Composer Work?
    27. How to Run Workflows in Cloud Composer
    28. Cloud Composer Security Features
    29. How Does It Work?
    30. Connectivity Options
    31. Datastream Use Cases
    32. Looker's Platform
    33. In-Database Architecture
    34. Semantic Modeling Layer
    35. Cloud Native
    36. Capture
    37. Process
    38. Store
    39. Analyze
    40. Use
    41. Services Spanning the Pipeline
  8. CHAPTER FIVE: Application Development and Modernization Opening
    1. Building and Modernizing Cloud Applications
    2. Microservices or Monolith?
    3. What Do Most Microservices Need?
    4. Where to Begin?
    5. Should You Migrate to Google Cloud?
    6. Which Migration Path Is Right for You?
    7. Common Cloud Migration Use Cases
    8. Why Is Traditional Hybrid and Multicloud Difficult?
    9. How Does Anthos Make Hybrid and Multicloud Easy?
    10. Deployment Option 1: Google Cloud
    11. Deployment Option 2: VMware vSphere
    12. Deployment Option 3: Bare-Metal Servers
    13. Deployment Option 4: Anthos Attached Clusters
    14. Deployment Option 5: AWS
    15. Deployment Option 6: Microsoft Azure
    16. How Has the Application Development Landscape Changed?
    17. What Is Microservices Architecture?
    18. How Are Monolithic and Microservices Architectures Different?
    19. Microservices Use Cases
    20. Service Choreography and Service Orchestration
    21. Google Cloud Support for Service Orchestration
    22. Google Cloud Support for Service Choreography
    23. Additional Services That Help with Both Choreography and Orchestration
    24. What Is API Management?
    25. What Is Apigee?
    26. What is API Gateway?
    27. API Gateway Architecture
    28. What's the Difference Between API Gateway and Apigee API Management Platform?
    29. What Is the Operations Suite?
    30. What Does Cloud Operations Include?
    31. How Does Cloud Operations Work?
    32. Sample Application Architecture
  9. CHAPTER SIX: Networking
    1. How Is the Google Cloud Physical Network Organized?
    2. Cloud Networking Services
    3. Premium Tier
    4. Standard Tier
    5. Choosing a Tier
    6. Cloud Interconnect and Cloud VPN
    7. Network Connectivity Center
    8. Peering
    9. CDN Interconnect
    10. Features of VPC Networks
    11. Shared VPC
    12. VPC Network Peering
    13. VPC Packet Mirroring
    14. How Does DNS Work?
    15. What Does Cloud DNS Offer?
    16. Hybrid Deployments: DNS Forwarding
    17. Hybrid Deployments: Hub and Spoke
    18. What Is Cloud Load Balancing?
    19. How Does Cloud Load Balancing Work?
    20. How to Use Global HTTP(S) Load Balancing
    21. How to Secure Your Application with Cloud Load Balancing
    22. How to Choose the Right Load-Balancing Option
    23. What Is Cloud CDN?
    24. How Does Cloud CDN Work?
    25. How to Use Cloud CDN
    26. Security
    27. How Is Cloud NAT Different from Typical NAT Proxies?
    28. Benefits of Using Cloud NAT
    29. NAT Rules
    30. Basic Cloud NAT Configuration Examples
    31. Network Topology
    32. Connectivity Tests
    33. Performance Dashboard
    34. Firewall Insights
    35. How Does a Typical Service Mesh Work in Kubernetes?
    36. How Is Traffic Director Different?
    37. How Does Traffic Director Support Proxy-less gRPC and VMs?
    38. How Does Traffic Director Work Across Hybrid and Multicloud Environments?
    39. Ingress and gateways
    40. Why Service Directory?
    41. How Service Directory Works with Load Balancer
    42. Using Cloud DNS with Service Directory
    43. Connect
    44. Scale
    45. Secure
    46. Optimize
    47. Modernize
  10. CHAPTER SEVEN: Data Science, Machine Learning, and Artificial Intelligence
    1. Data Engineering
    2. Data Analysis
    3. Model Development
    4. ML Engineering
    5. Insights Activation
    6. Orchestration
    7. Prepackaged AI Solutions
    8. Pretrained APIs
    9. BigQuery ML
    10. Vertex AI
    11. End-to-End Model Creation in Vertex AI
    12. What Does Vertex AI Include?
    13. AutoML Behind the Scenes
    14. How Do I Work with AutoML in Vertex AI?
    15. What Is MLOps?
    16. Vertex AI Pipelines
    17. Vertex AI Pipelines Under the Hood
    18. Vertex AI Pipelines Open Source Support
    19. Benefits of BigQuery ML
    20. Supported Models in BigQuery ML
    21. How to Use Vision AI
    22. What Can I Do with Vision API?
    23. How to Use Video AI
    24. What Can I Do with the Video Intelligence API?
    25. Use Case Scenarios
    26. What Is Translation AI?
    27. What If Your Business Has Specific Terms?
    28. AutoML Translation
    29. What Is the Media Translation API?
    30. How to Use Natural Language AI
    31. What Can I Do with the Natural Language API?
    32. What Can I Do with the Speech-to-Text API?
    33. How to Use the Speech-to-Text API
    34. What Is Contact Center AI?
    35. How Does Contact Center AI Work?
    36. What Is Document AI?
    37. How to Use Document AI
    38. Sample Document AI Architecture
    39. Vertical Solutions
    40. What Is Recommendations AI?
    41. Sample Customer Journey with Recommendations AI
    42. How Does Recommendations AI Work?
    43. Data Engineering
    44. Data Analysis
    45. Model Development
    46. ML Engineering
    47. Insights Activation
    48. Orchestration
  11. CHAPTER EIGHT: Security
    1. Cloud Security Is Shared Fate
    2. Infrastructure Security
    3. Network Security
    4. Application Security
    5. Secure Software Supply Chain Security
    6. Data Security
    7. Identity and Access Management
    8. Endpoint Security
    9. Security Monitoring and Operations
    10. Governance, Risk, and Compliance
    11. Defense in Depth at Scale
    12. End-to-End Provenance and Attestation
    13. Application Security
    14. Risk Points for a Software Supply Chain
    15. How Does Google Secure the Software Supply Chain Internally?
    16. What is SLSA?
    17. How Does Google Cloud Help You Secure Your Software Supply Chain?
    18. Encryption
    19. At-Rest Encryption Options
    20. Other Data Security Services
    21. What Is DLP?
    22. How Does It Work?
    23. A Variety of Deidentification Techniques
    24. What Is Cloud Identity?
    25. Authentication Options
    26. User experience
    27. Advantages
    28. What Is Cloud IAM?
    29. Cloud IAM best practices
    30. What Are Service Accounts?
    31. Service Account Types
    32. Service Account Credentials
    33. Service Account Best Practices
    34. What Is BeyondCorp?
    35. What Is BeyondCorp Enterprise?
    36. How Does BeyondCorp Enterprise Work?
    37. What Is Security Command Center?
    38. How Does Security Command Center work?
    39. Infrastructure Security
    40. Network Security
    41. Application Security
    42. Software Supply Chain Security
    43. Data Security
    44. Identity and Access Management (IAM)
    45. Endpoint Security
    46. Security Monitoring and Operations
    47. Governance, Risk, and Compliance
  12. COPYRIGHT
  13. DEDICATION
  14. ACKNOWLEDGMENTS
  15. ABOUT THE AUTHOR
  16. END USER LICENSE AGREEMENT

Product information

  • Title: Visualizing Google Cloud
  • Author(s): Priyanka Vergadia
  • Release date: April 2022
  • Publisher(s): Wiley
  • ISBN: 9781119816324