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Architecting Google Cloud Solutions

You're reading from   Architecting Google Cloud Solutions Learn to design robust and future-proof solutions with Google Cloud technologies

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Product type Paperback
Published in Apr 2021
Publisher Packt
ISBN-13 9781800563308
Length 472 pages
Edition 1st Edition
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Author (1):
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Victor Dantas Victor Dantas
Author Profile Icon Victor Dantas
Victor Dantas
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Toc

Table of Contents (17) Chapters Close

Preface 1. Section 1: Introduction to Google Cloud
2. Chapter 1: An Introduction to Google Cloud for Architects FREE CHAPTER 3. Chapter 2: Mastering the Basics of Google Cloud 4. Section 2: Designing Great Solutions in Google Cloud
5. Chapter 3: Designing the Network 6. Chapter 4: Architecting Compute Infrastructure 7. Chapter 5: Architecting Storage and Data Infrastructure 8. Chapter 6: Configuring Services for Observability 9. Chapter 7: Designing for Security and Compliance 10. Section 3: Designing for the Modern Enterprise
11. Chapter 8: Approaching Big Data and Data Pipelines 12. Chapter 9: Jumping on the DevOps Bandwagon with Site Reliability Engineering (SRE) 13. Chapter 10: Re-Architecting with Microservices 14. Chapter 11: Applying Machine Learning and Artificial Intelligence 15. Chapter 12: Achieving Operational Excellence 16. Other Books You May Enjoy

Securing data and ensuring compliance

The first step toward efficiently securing your data is classifying it. After all, not all data is created equal, and you don't want to spend the same measure of effort and money on protecting every type of data.

Classifying your data

As discussed in Chapter 5, Architecting Storage and Data Infrastructure, data can be classified according to sensitivity levels. Example levels could be restricted, sensitive, and unrestricted. Alternatively, the levels could be confidential, internal use, and public. A three-tier classification system works well in most cases, but it could be different for your organization. The basis for classification can either be the data's content itself, the context surrounding the data (for example, which application or business function created it?), or a manual classification. A data classification policy could look like the following:

On GCP, the Cloud Data Loss Prevention (Cloud...

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