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Notebooks @ Netflix: From analytics to engineering with Jupyter notebooks
- 1. Notebooks @ Netflix. From analytics to engineering with notebooks. Michelle Ufford @MichelleUfford Kyle Kelley @rgbkrk
- 2. Data @ Netflix
- 3. 130 million members
- 4. * Well, almost anywhere. Anywhere in the world.*
- 5. Any device.
- 6. • 1 trillion events • 100PB data warehouse • 150,000 Genie jobs Data at scale.
- 7. $8 billion on content in 2018
- 8. Data Platform @ Netflix
- 9. Data driven.
- 10. subscriber activity 20180822
- 11. RAW data pipeline fast storage data viz events data data storage Pig DW RPT interactive query data movement data access subscriber activity 20180822
- 12. data scientists data engineers data viz engineers quantitative analysts product managers research scientists analytics engineers executivessoftware engineers algorithm engineers Data Products Data Insights Business Decisions & Product Improvements business analysts technical pgm mgr INSIGHTS DATA ML scientists
- 13. Notebooks @ Netflix
- 14. data scientists data engineers data viz engineers quantitative analysts research scientists analytics engineers algorithm engineers Data Products Data Insights INSIGHTS DATA ML scientists PRODUCTIONALIZATION product managers executivessoftware engineers Business Decisions & Product Improvements business analysts technical pgm mgr
- 15. Native support for parameterization.
- 16. What’s Next?
- 17. Better Scala Support
- 18. Scala support. • Kernel stability • Native data viz • Spark integration Goal: meet/exceed parity with top Scala notebook offerings
- 19. More Integration
- 20. Integration. • Scheduling • Surfacing logs & error messages • Native Goal: provide a single, cohesive platform experience
- 21. Improved Reliability
- 22. Reliability. Goal: build confidence in using notebooks for mission-critical workloads • Kernel stability • Visibility into kernel state • Automated source control
- 23. data scientists data engineers data viz engineers quantitative analysts research scientists analytics engineers algorithm engineers Data Products Data Insights INSIGHTS DATA ML scientists product managers executivessoftware engineers Business Decisions & Product Improvements business analysts technical pgm mgr
- 24. 1. Simple 2. Integrated 3. Collaborative Design Principles.
- 25. Open source.
- 26. Thank you. Michelle Ufford @MichelleUfford Kyle Kelley @rgbkrk Netflix Data @NetflixData Tech Blog techblog.netflix.com Netflix Jobs jobs.netflix.com
