You're reading from Professional Cloud Architect Google Cloud Certification Guide Build a solid foundation in Google Cloud Platform to achieve the most lucrative IT certification

Product type Paperback

Published in Dec 2021

Publisher Packt

ISBN-13 9781801812290

Length 664 pages

Edition 2nd Edition

Tools

Google Cloud Platform

Concepts

Cloud Computing

Authors (2):

Konrad Cłapa

Brian Gerrard

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Table of Contents (25) Chapters

Preface

1. Section 1: Introduction to GCP

2. Chapter 1: GCP Cloud Architect Professional FREE CHAPTER

3. Chapter 2: Getting Started with Google Cloud Platform

4. Chapter 3: Google Cloud Platform Core Services

5. Section 2: Manage, Design, and Plan a Cloud Solution Architecture

6. Chapter 4: Working with Google Compute Engine

7. Chapter 5: Exploring Google App Engine as a Compute Option

8. Chapter 6: Managing Kubernetes Clusters with Google Kubernetes Engine

9. Chapter 7: Deploying Cloud-Native Workloads with Cloud Run

10. Chapter 8: Managing Cloud-Native Workloads with Anthos

11. Chapter 9: Running Serverless Functions with Google Cloud Functions

12. Chapter 10: Networking Options in GCP

13. Chapter 11: Exploring Storage and Database Options in GCP – Part 1

14. Chapter 12: Exploring Storage and Database Options in GCP – Part 2

15. Chapter 13: Analyzing Big Data Options

16. Chapter 14: Putting Machine Learning to Work

17. Section 3: Secure, Manage and Monitor a Google Cloud Solution

18. Chapter 15: Security and Compliance

19. Chapter 16: Google Cloud Management Options

20. Chapter 17: Monitoring Your Infrastructure

21. Section 4: Exam Focus

22. Chapter 18: Case Studies

23. Chapter 19: Test Your Knowledge

24. Other Books You May Enjoy

Going through big data services

Big data services enable the user to process large amounts of data to provide answers to complex problems. GCP offers many services that tightly integrate to create an End-to-End (E2E) data analysis pipeline. These services are as follows:

BigQuery: BigQuery is a highly scalable and fully managed cloud data warehouse. It allows users to perform analytics operations with built-in ML. BigQuery is completely serverless and can host petabytes of data. The underlying infrastructure scales seamlessly and allows parallel data processing. The data can be stored in BigQuery Storage, Cloud Storage, Bigtable, Sheets, or Google Drive. The user defines datasets containing tables. BigQuery uses familiar ANSI-compliant SQL for queries and provides ODBC and JDBC drivers. Users can choose from two types of payment models—one is flexible and involves paying for storage and queries, and the other involves a flat rate with stable monthly costs. It is ideal...

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Going through big data services

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Table of Contents (25) Chapters