Cost-Effective Data Pipelines
Cost-Effective Data Pipelines
Balancing Trade-Offs When Developing Pipelines in the Cloud
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Sign in or Sign up!- Release Date: 28/07/2023
- Barcode: 9781492098645
- Genre: Computing & The Internet
- Sub-Genre: Data Management
- Imprint: O'Reilly Media
- Publisher: O'Reilly Media

Cost-Effective Data Pipelines
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DESCRIPTION
Balancing Trade-Offs When Developing Pipelines in the Cloud
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.
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 strategiesMinimize waste without sacrificing performance by rightsizing compute resourcesDrive pipeline evolution, head off performance issues, and quickly debug with effective monitoringSet up development and test environments that minimize cloud service dependenciesCreate data pipeline code bases that are testable and extensible, fostering rapid development and evolutionImprove data quality and pipeline operation through validation and testing
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