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  • Book Overview & Buying Big Data on Kubernetes
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Big Data on Kubernetes

Big Data on Kubernetes

By : Neylson Crepalde
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Big Data on Kubernetes

Big Data on Kubernetes

By: Neylson Crepalde

Overview of this book

In today's data-driven world, organizations across different sectors need scalable and efficient solutions for processing large volumes of data. Kubernetes offers an open-source and cost-effective platform for deploying and managing big data tools and workloads, ensuring optimal resource utilization and minimizing operational overhead. If you want to master the art of building and deploying big data solutions using Kubernetes, then this book is for you. Written by an experienced data specialist, Big Data on Kubernetes takes you through the entire process of developing scalable and resilient data pipelines, with a focus on practical implementation. Starting with the basics, you’ll progress toward learning how to install Docker and run your first containerized applications. You’ll then explore Kubernetes architecture and understand its core components. This knowledge will pave the way for exploring a variety of essential tools for big data processing such as Apache Spark and Apache Airflow. You’ll also learn how to install and configure these tools on Kubernetes clusters. Throughout the book, you’ll gain hands-on experience building a complete big data stack on Kubernetes. By the end of this Kubernetes book, you’ll be equipped with the skills and knowledge you need to tackle real-world big data challenges with confidence.
Table of Contents (18 chapters)
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Lock Free Chapter
1
Part 1:Docker and Kubernetes
5
Part 2: Big Data Stack
10
Part 3: Connecting It All Together

Summary

In this chapter, we explored the next steps in your journey toward mastering big data on Kubernetes. We covered several important topics that are essential for building a robust and production-ready big data infrastructure on Kubernetes, including Kubernetes monitoring and application monitoring, building a service mesh, important security considerations to take into account in a production environment, scalability automation methods, GitOps and CI/CD for Kubernetes, and Kubernetes cost control.

We also discussed the importance of having a team with the right skills and expertise to tackle these challenges successfully. We covered the key roles and skill sets required for each of the topics mentioned, including SREs, DevOps engineers, cloud engineers, security engineers, and release engineers.

Congratulations on reaching the end of this book! You’ve taken a significant step toward mastering the art of running big data workloads on Kubernetes. The journey ahead...

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Big Data on Kubernetes
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