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Solutions Architect's Handbook

You're reading from   Solutions Architect's Handbook Kick-start your career as a solutions architect by learning architecture design principles and strategies

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Product type Paperback
Published in Jan 2022
Publisher Packt
ISBN-13 9781801816618
Length 590 pages
Edition 2nd Edition
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Authors (2):
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Saurabh Shrivastava Saurabh Shrivastava
Author Profile Icon Saurabh Shrivastava
Saurabh Shrivastava
Neelanjali Srivastav Neelanjali Srivastav
Author Profile Icon Neelanjali Srivastav
Neelanjali Srivastav
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Toc

Table of Contents (22) Chapters Close

Preface 1. The Meaning of Solution Architecture FREE CHAPTER 2. Solution Architects in an Organization 3. Attributes of the Solution Architecture 4. Principles of Solution Architecture Design 5. Cloud Migration and Hybrid Cloud Architecture Design 6. Solution Architecture Design Patterns 7. Performance Considerations 8. Security Considerations 9. Architectural Reliability Considerations 10. Operational Excellence Considerations 11. Cost Considerations 12. DevOps and Solution Architecture Framework 13. Data Engineering for Solution Architecture 14. Machine Learning Architecture 15. The Internet of Things Architecture 16. Quantum Computing 17. Rearchitecting Legacy Systems 18. Solution Architecture Document 19. Learning Soft Skills to Become a Better Solution Architect 20. Other Books You May Enjoy
21. Index

Data ingestion

Data ingestion is the act of collecting data for transfer and storage. There are lots of places that data can be onboarded. Predominantly, data ingestion falls into one of the categories from databases, streams, logs, and files. Among these, databases are the most popular. These typically consist of your main upstream transactional systems that are the primary data storage for your applications. They take on both relational and non-relational flavors, and there are several techniques for extracting data out of them.

Streams are open-ended sequences of time-series data such as clickstream data from websites or IoT devices, usually published into an API we host. Logs get generated by applications, services, and operating systems. A data lake is a great place to store all of the data for centralized analysis. Data lakes provide a single source of truth to store all data in one place and break data silos across various business units in the organization. In a later...

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