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Multi-Cloud Strategy for Cloud Architects

You're reading from   Multi-Cloud Strategy for Cloud Architects Learn how to adopt and manage public clouds by leveraging BaseOps, FinOps, and DevSecOps

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Product type Paperback
Published in Apr 2023
Publisher Packt
ISBN-13 9781804616734
Length 470 pages
Edition 2nd Edition
Tools
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Author (1):
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Jeroen Mulder Jeroen Mulder
Author Profile Icon Jeroen Mulder
Jeroen Mulder
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Toc

Table of Contents (23) Chapters Close

Preface 1. Introduction to Multi-Cloud FREE CHAPTER 2. Collecting Business Requirements 3. Starting the Multi-Cloud Journey 4. Service Designs for Multi-Cloud 5. Managing the Enterprise Cloud Architecture 6. Controlling the Foundation Using Well-Architected Frameworks 7. Designing Applications for Multi-Cloud 8. Creating a Foundation for Data Platforms 9. Creating a Foundation for IoT 10. Managing Costs with FinOps 11. Maturing FinOps 12. Cost Modeling in the Cloud 13. Implementing DevSecOps 14. Defining Security Policies 15. Implementing Identity and Access Management 16. Defining Security Policies for Data 17. Implementing and Integrating Security Monitoring 18. Developing for Multi-Cloud with DevOps and DevSecOps 19. Introducing AIOps and GreenOps in Multi-Cloud 20. Conclusion: The Future of Multi-Cloud 21. Other Books You May Enjoy
22. Index

Summary

In this chapter, we discussed the basic architecture principles to build and manage a data platform. We looked at data lakes that can hold vast amounts of raw data and how we can build these lakes on top of cloud storage. The next step is to fetch the right data that is usable in data models. We must extract, transfer and load – ETL or ELT for short - the accurate data sets in environments where data analysts can work with this data. Typically, data warehouses are used for this.

We studied the various propositions for data operations of the major cloud providers AWS, Azure, Google Cloud, Alibaba, and Oracle. Next, we discussed the challenges that come with building and operating data platforms. There will be challenges with respect to access to data, accuracy, but also privacy and compliancy. Data gravity is another problem that we must solve. It’s not easy to move huge amounts of data across platform, hence we must find other solutions to work with data in different...

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