Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Big Data on Kubernetes

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

Arrow left icon
Product type Paperback
Published in Jul 2024
Publisher Packt
ISBN-13 9781835462140
Length 296 pages
Edition 1st Edition
Languages
Concepts
Arrow right icon
Author (1):
Arrow left icon
Neylson Crepalde Neylson Crepalde
Author Profile Icon Neylson Crepalde
Neylson Crepalde
Arrow right icon
View More author details
Toc

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

Summary

In this chapter, we covered the fundamental concepts and architecture behind Apache Kafka – a popular open source platform for building real-time data pipelines and streaming applications.

You learned how Kafka provides distributed, partitioned, replicated, and fault-tolerant PubSub messaging through its topics and brokers architecture. Through hands-on examples, you gained practical experience with setting up local Kafka clusters using Docker, creating topics, and producing and consuming messages. You understood offsets and consumer groups that enable fault tolerance and parallel consumption from topics.

We introduced Kafka Connect, which allows us to stream data between Kafka and external systems such as databases. You implemented a source connector to ingest changes from a PostgreSQL database into Kafka topics. We also set up a sink connector to deliver the messages from Kafka to object storage in AWS S3 in real time.

The highlight was building an end-to...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime