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Google Cloud Certified Professional Cloud Developer Exam Guide

You're reading from   Google Cloud Certified Professional Cloud Developer Exam Guide Modernize your applications using cloud-native services and best practices

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Product type Paperback
Published in Sep 2021
Publisher Packt
ISBN-13 9781800560994
Length 382 pages
Edition 1st Edition
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Author (1):
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Sebastian Moreno Sebastian Moreno
Author Profile Icon Sebastian Moreno
Sebastian Moreno
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Table of Contents (21) Chapters Close

Preface 1. Section 1: Welcome to the Google Cloud Developers' Guide
2. Chapter 1: Google Cloud Platform Developer Fundamentals FREE CHAPTER 3. Chapter 2: Security Fundamentals and Best Practices 4. Section 2: Developing and Modernizing Applications on Google Cloud Platform
5. Chapter 3: Application Modernization Using Google Cloud 6. Chapter 4: Using Cloud Functions and Google App Engine 7. Chapter 5: Virtual Machines and Container Applications on Google Cloud Platform 8. Chapter 6: Managing APIs on Google Cloud Platform 9. Section 3: Storage Foundations
10. Chapter 7: Handling Unstructured Data 11. Chapter 8: Databases and Event Messages in Google Cloud 12. Chapter 9: Data Management and Database Strategies 13. Chapter 10: Optimizing Applications with Caching Strategies on Google Cloud Platform 14. Section 4: SRE for Developers
15. Chapter 11: Logging on Google Cloud Platform 16. Chapter 12: Cloud Monitoring, Tracing, and Debugging 17. Section 5: Analyzing a Sample Case Study
18. Chapter 13: HipLocal Sample Case Study Preparation 19. Chapter 14: Questions and Answers 20. Other Books You May Enjoy

Data management strategies for your databases in Google Cloud

In the previous section, we learned that the choice we make from the different database options offered by Google Cloud will depend on the workloads we face when considering factors such as data structure, data volume, latency, and throughput. In this section, we will focus on factors that allow us to get the best performance from our database, to ensure that applications developed on these databases function optimally.

What is database sharding?

Database sharding is a horizontal partition of data held on a separate server to spread the load.

Some of the database solutions that Google Cloud offers, such as Firestore, Cloud Spanner, and Bigtable, do database sharding in order to give the benefits of horizontal scaling.

One of the problems of database sharding is hot-spotting, a performance problem that we are going to review in the next section.

What is hot-spotting, and why should you avoid it?

Hot-spotting...

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