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Big Data on Kubernetes

You're reading from   Big Data on Kubernetes A practical guide to building efficient and scalable data solutions

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Product type Paperback
Published in Jul 2024
Publisher Packt
ISBN-13 9781835462140
Length 296 pages
Edition 1st Edition
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Author (1):
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Neylson Crepalde Neylson Crepalde
Author Profile Icon Neylson Crepalde
Neylson Crepalde
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Table of Contents (18) Chapters Close

Preface 1. Part 1:Docker and Kubernetes FREE CHAPTER
2. Chapter 1: Getting Started with Containers 3. Chapter 2: Kubernetes Architecture 4. Chapter 3: Getting Hands-On with Kubernetes 5. Part 2: Big Data Stack
6. Chapter 4: The Modern Data Stack 7. Chapter 5: Big Data Processing with Apache Spark 8. Chapter 6: Building Pipelines with Apache Airflow 9. Chapter 7: Apache Kafka for Real-Time Events and Data Ingestion 10. Part 3: Connecting It All Together
11. Chapter 8: Deploying the Big Data Stack on Kubernetes 12. Chapter 9: Data Consumption Layer 13. Chapter 10: Building a Big Data Pipeline on Kubernetes 14. Chapter 11: Generative AI on Kubernetes 15. Chapter 12: Where to Go from Here 16. Index 17. Other Books You May Enjoy

Getting Started with Containers

The world is rapidly generating massive amounts of data from a variety of sources – mobile devices, social media, e-commerce transactions, sensors, and more. This data explosion is often referred to as “big data.” While big data presents immense opportunities for businesses and organizations to gain valuable insights, it also brings tremendous complexity in how to store, process, analyze, and extract value from huge volumes of diverse data.

This is where Kubernetes comes in. Kubernetes is an open source container orchestration system that helps automate the deployment, scaling, and management of containerized applications. Kubernetes brings important advantages for building big data systems. It provides a standard way to deploy containerized big data applications on any infrastructure. This makes it easy to migrate applications across on-premises servers or cloud providers. It also makes it simple to scale big data applications...

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