Big Data on Kubernetes
A practical guide to building efficient and scalable data solutions
Created by Neylson Crepalde
Discover how to design and manage scalable data pipelines using Kubernetes. Through practical examples, you'll learn to deploy big data tools and build efficient solutions that handle large-scale data processing with ease.
Packt | Jul 2024 | 296 min
What You Will Learn
You'll start by setting up containers and understanding Kubernetes architecture. Step by step, you'll install and configure leading big data tools, then build real-world data pipelines on Kubernetes. Hands-on examples and use cases help you apply concepts directly to your own projects.
Key Features
- Set up and manage Kubernetes clusters for big data workloads in the cloud
- Build, deploy, and orchestrate data pipelines using Spark, Airflow, and Kafka
- Optimize performance and resource use for reliable, cost-effective data solutions
Target Audience
Ideal for data engineers, BI analysts, data architects, and technical managers with a basic grasp of Python, SQL, and YAML. If you're looking to expand your skills in deploying and managing big data solutions on Kubernetes, you'll find practical guidance to help you build robust, scalable systems.
