Crepalde Big Data on Kubernetes

A practical guide to building efficient and scalable data solutions
1. Auflage 2024
ISBN: 978-1-83546-899-9
Verlag: De Gruyter
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 296 Seiten

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.

Autoren/Hrsg.

Crepalde, Neylson

Fachgebiete

• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Automatische Datenerfassung, Datenanalyse
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Warehouse
• Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung Verteilte Systeme (Netzwerke)

Inhaltsverzeichnis

Table of Contents - Getting Started with Containers
- Kubernetes Architecture
- Kubernetes - Hands On
- The Modern Data Stack

- Big Data Processing with Apache Spark
- Apache Airflow for Building Pipelines
- Apache Kafka for Real-Time Events and Data Ingestion
- Deploying the Big Data Stack on Kubernetes
- Data Consumption Layer
- Building a Big Data Pipeline on Kubernetes
- AI/ML Workloads on Kubernetes
- Where to Go from Here

Über Autor(innen)

Crepalde Neylson :

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.