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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

Table of Contents

  1. Preface
  2. 1. Designing Compute for Data Pipelines
  3. 2. Responding to Changes in Demand by Scaling Compute
  4. 3. Data Organization in the Cloud
  5. 4. Economical Pipeline Fundamentals
  6. 5. Setting Up Effective Development Environments
  7. 6. Software Development Strategies
  8. 7. Unit Testing
  9. 8. Mocks
  10. 9. Data for Testing
  11. 10. Logging
  12. 11. Finding Your Way with Monitoring
  13. 12. Essential Takeaways
  14. Appendix. Preparing a Cloud Budget
  15. Index
  16. About the Author