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Scalable Data Architecture with Java

You're reading from   Scalable Data Architecture with Java Build efficient enterprise-grade data architecting solutions using Java

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Product type Paperback
Published in Sep 2022
Publisher Packt
ISBN-13 9781801073080
Length 382 pages
Edition 1st Edition
Languages
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Author (1):
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Sinchan Banerjee Sinchan Banerjee
Author Profile Icon Sinchan Banerjee
Sinchan Banerjee
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Table of Contents (19) Chapters Close

Preface 1. Section 1 – Foundation of Data Systems
2. Chapter 1: Basics of Modern Data Architecture FREE CHAPTER 3. Chapter 2: Data Storage and Databases 4. Chapter 3: Identifying the Right Data Platform 5. Section 2 – Building Data Processing Pipelines
6. Chapter 4: ETL Data Load – A Batch-Based Solution to Ingesting Data in a Data Warehouse 7. Chapter 5: Architecting a Batch Processing Pipeline 8. Chapter 6: Architecting a Real-Time Processing Pipeline 9. Chapter 7: Core Architectural Design Patterns 10. Chapter 8: Enabling Data Security and Governance 11. Section 3 – Enabling Data as a Service
12. Chapter 9: Exposing MongoDB Data as a Service 13. Chapter 10: Federated and Scalable DaaS with GraphQL 14. Section 4 – Choosing Suitable Data Architecture
15. Chapter 11: Measuring Performance and Benchmarking Your Applications 16. Chapter 12: Evaluating, Recommending, and Presenting Your Solutions 17. Index 18. Other Books You May Enjoy

Virtualization and containerization platforms

With the spread of information technology (IT) in all spheres of life, the dependency and reliability on IT infrastructure have increased manifold. Now, IT runs so many critical and real-time businesses. This means that there can be zero or negligible downtime for maintenance or failure. Also, rapid real-time demands have grown. For example, during the holiday season, there’s a huge amount of traffic on online shopping websites. So, now, IT needs to be highly available, elastic, flexible, and quick. These were the reasons that motivated the creation of virtual platforms such as virtualization and containerization. For example, Barclays, a multinational financial firm based in the UK, was facing a hard time from competitors due to their slow pace of innovation and project deliveries. One of its major roadblocks was the time it took to provision new servers. So, they decided to use Red Hat OpenShift to containerize their application...

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