Name: Cost-Effective Data Pipelines: Balancing Trade-Offs When Developing Pipelines in the Cloud (en Inglés)
SKU: 55254980
Price: 60.72 USD
Availability: InStock
Author: Sev Leonard

portada Cost-Effective Data Pipelines: Balancing Trade-Offs When Developing Pipelines in the Cloud (en Inglés)

Cost-Effective Data Pipelines: Balancing Trade-Offs When Developing Pipelines in the Cloud (en Inglés)

Formato

Libro Físico

Editorial

O'reilly Media

Autor

Sev Leonard

Idioma

Inglés

N° páginas

286

Encuadernación

Tapa Blanda

ISBN13

9781492098645

N° edición

Cost-Effective Data Pipelines: Balancing Trade-Offs When Developing Pipelines in the Cloud (en Inglés)

Sev Leonard (Autor) · O'reilly Media · Tapa Blanda

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Reseña del libro "Cost-Effective Data Pipelines: Balancing Trade-Offs When Developing Pipelines in the Cloud (en Inglés)"

The low cost of getting started with cloud services can easily evolve into a significant expense down the road. That's challenging for teams developing data pipelines, particularly when rapid changes in technology and workload require a constant cycle of redesign. How do you deliver scalable, highly available products while keeping costs in check? With this practical guide, author Sev Leonard provides a holistic approach to designing scalable data pipelines in the cloud. Intermediate data engineers, software developers, and architects will learn how to navigate cost/performance trade-offs and how to choose and configure compute and storage. You'll also pick up best practices for code development, testing, and monitoring. By focusing on the entire design process, you'll be able to deliver cost-effective, high-quality products. This book helps you: Reduce cloud spend with lower cost cloud service offerings and smart design strategies Minimize waste without sacrificing performance by rightsizing compute resources Drive pipeline evolution, head off performance issues, and quickly debug with effective monitoring Set up development and test environments that minimize cloud service dependencies Create data pipeline code bases that are testable and extensible, fostering rapid development and evolution Improve data quality and pipeline operation through validation and testing