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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

Product type Paperback

Published in Jul 2024

Publisher Packt

ISBN-13 9781835462140

Length 296 pages

Edition 1st Edition

Languages

Python

Tools

Kubernetes

Concepts

Big Data

Author (1):

Neylson Crepalde

View More author details

Table of Contents (18) Chapters

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

Why subscribe?

17. Other Books You May Enjoy

To get the most out of this book

Some basics in Python programming knowledge and experience with Spark, Docker, Airflow, Kafka, and Git will help you get the most out of this book.

Software/hardware covered in the book	Operating system requirements
Python>=3.9	Windows, macOS, or Linux
Docker, the latest version available	Linux
Docker Desktop, the latest version available	Windows or macOS
Kubectl	Windows, macOS, or Linux
Awscli	Windows, macOS, or Linux
Eksctl	Windows, macOS, or Linux
DBeaver Community Edition	Windows, macOS, or Linux

All guidance needed for software installation will be provided in each chapter.

If you are using the digital version of this book, we advise you to type the code yourself or access the code from the book’s GitHub repository (a link is available in the next section). Doing so will help you avoid any potential errors related to the copying and pasting of code.

The rest of the chapter is locked

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Authors (1)

Neylson Crepalde

Neylson Crepalde

Neylson Crepalde is a Generative AI Strategist at AWS. Prior to that, he was CTO at A3Data, a consulting company focused on Data, Analytics and Artificial Intelligence. He holds a PhD in Economic Sociology, a master in Sociology of Culture, an MBA in Cultural Management and a Bachelor in Orchestra Conducting. He has been working with data since 2015. He is committed to sharing knowledge with people of every professional level and helping data teams achieve their best. He is several times AWS certified, Spark certified, Neo4j certified and Airflow certified. Neylson has been teaching for 10+ years now in colleges and MBA programs and he gives regular talks and lectures on Data Architecture, AI strategy, Data Governance and Network Science.

See other products by Neylson Crepalde

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