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Building Google Cloud Platform Solutions

You're reading from   Building Google Cloud Platform Solutions Develop scalable applications from scratch and make them globally available in almost any language

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Product type Course
Published in Mar 2019
Publisher Packt
ISBN-13 9781838647438
Length 778 pages
Edition 1st Edition
Languages
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Authors (3):
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Steven Porter Steven Porter
Author Profile Icon Steven Porter
Steven Porter
Legorie Rajan PS Legorie Rajan PS
Author Profile Icon Legorie Rajan PS
Legorie Rajan PS
Ted Hunter Ted Hunter
Author Profile Icon Ted Hunter
Ted Hunter
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Toc

Table of Contents (29) Chapters Close

Title Page
Copyright and Credits
About Packt
Contributors
Preface
1. Why GCP? FREE CHAPTER 2. The Google Cloud Console 3. APIs, CLIs, IAM, and Billing 4. Google App Engine 5. Google Kubernetes Engine 6. Google Cloud Functions 7. Google Compute Engine 8. NoSQL with Datastore and Bigtable 9. Relational Data with Cloud SQL and Cloud Spanner 10. Google Cloud Storage 11. Stackdriver 12. Change Management 13. GCP Networking for Developers 14. Messaging with Pub/Sub and IoT Core 15. Integrating with Big Data Solutions on GCP 16. Compute 17. Storage and Databases 18. Networking 19. Security 20. Machine Learning and Big Data 21. Management Tools 22. Best Practices 1. Other Books You May Enjoy Index

Storage classes and locations


As an organization's data needs grow, a common problem they must tackle is how to manage that data effectively. Some of the major considerations when designing data storage solutions include infrastructure cost, operations cost, availability requirements, and security. A traditional approach to this problem is to distinguish between hot data that is in active use, and cold data that is not in active use, but needs to be persisted for other reasons such as auditing, archiving, and disaster recovery.

Each category of data has specific needs that must be taken into consideration when evaluating storage solutions. By distinguishing between hot and cold data, each category can be dealt with in the most appropriate manner. Because hot data is in active use, priority tends to be given to availability, latency, and throughput. On the other hand, cold data can often sacrifice availability for lower costs.

Today, there are many managed solutions for both hot and cold storage...

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