The Hybrid Data Platform
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Home > Computing and Information Technology > Databases > Database design and theory > The Hybrid Data Platform: Architecting Cloud-Native Pipelines with AWS Glue and Kubernetes as a Data Engineer(Cloud Data Engineering Series: Pipelines, Automation, and Modern Architectures)
The Hybrid Data Platform: Architecting Cloud-Native Pipelines with AWS Glue and Kubernetes as a Data Engineer(Cloud Data Engineering Series: Pipelines, Automation, and Modern Architectures)

The Hybrid Data Platform: Architecting Cloud-Native Pipelines with AWS Glue and Kubernetes as a Data Engineer(Cloud Data Engineering Series: Pipelines, Automation, and Modern Architectures)


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About the Book

The Hybrid Data Platform: Architecting Cloud-Native Pipelines with AWS Glue and Kubernetes as a Data Engineer Building modern data pipelines isn't just about moving information from point A to point B-it's about creating systems that are scalable, governed, and adaptable to the demands of today's enterprises. In a world where data volume, velocity, and variety keep increasing, how do you design architectures that are both efficient and future-ready? This book answers that question by showing how AWS Glue and Kubernetes can be combined to create hybrid data platforms that balance automation with flexibility. Written for data engineers, architects, and technical leaders, it provides a step-by-step framework for architecting cloud-native pipelines that handle batch, streaming, and advanced analytics workloads. Whether you're aiming to improve enterprise reporting, enable machine learning pipelines, or expand into multi-cloud operations, this book gives you the strategies and tools to succeed. What sets this book apart is its practical structure, moving from foundations to real-world implementations. You'll explore: The Evolution of Data Engineering - why hybrid architectures are becoming essential. Foundations of AWS Glue and Kubernetes - core components, architecture, and how they complement each other. Designing Hybrid Pipelines - patterns that integrate serverless workflows with containerized workloads. Building Data Lakes and Handling Mixed Workloads - strategies for batch, streaming, and real-time data. Security, Governance, and Compliance - IAM, RBAC, and regulatory alignment in hybrid environments. Monitoring, Logging, and Optimization - how to ensure reliability, observability, and cost efficiency. Real-World Use Cases and Future-Proofing - enterprise analytics, AI integration, and sustainable scaling. Every chapter blends technical depth with practical insights, supported by extended code snippets, deployment templates, and curated recommendations in the appendix. The result is a resource that doesn't just explain hybrid data platforms-it equips you to build and operate them confidently. If you're a data engineer looking to stay ahead of the curve, or a decision-maker seeking to guide your team toward sustainable cloud-native solutions, this book will show you how to architect hybrid data platforms that scale with your needs. Take the next step toward mastering hybrid cloud data engineering-make this book your guide to building pipelines that deliver both immediate results and long-term value.


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Product Details
  • ISBN-13: 9798267629393
  • Publisher: Independently Published
  • Publisher Imprint: Independently Published
  • Height: 254 mm
  • No of Pages: 114
  • Returnable: N
  • Spine Width: 6 mm
  • Weight: 263 gr
  • ISBN-10: 8267629394
  • Publisher Date: 29 Sep 2025
  • Binding: Paperback
  • Language: English
  • Returnable: N
  • Series Title: Cloud Data Engineering Series: Pipelines, Automation, and Modern Architectures
  • Sub Title: Architecting Cloud-Native Pipelines with AWS Glue and Kubernetes as a Data Engineer
  • Width: 178 mm


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The Hybrid Data Platform: Architecting Cloud-Native Pipelines with AWS Glue and Kubernetes as a Data Engineer(Cloud Data Engineering Series: Pipelines, Automation, and Modern Architectures)
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