Making it easy to work with data
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Presentation at the Crunch Data Conference about the history of the Netflix Data Platform
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Making it easy to work with data
- 1. Making it easy To work with data Charles Smith Data Platform Architecture
- 2. How do you decide what to build?
- 4. Good: Bad: Users These are the people that will use the data to move the platform. They really don’t know what they need technically.
- 5. Good: Bad: Vision Build the platform that works for you. Miss the real needs or build in a bubble.
- 6. Good: Bad: Peers Take the best ideas and even better tools. Missing context. They aren’t solving your problems.
- 9. History of Netflix and big data 2010 Netflix expands to Canada . 2009 Netflix starts moving to AWS 2007 Netflix begins Streaming 2011 AWS Cloud/Streaming only
- 10. Build fast, but expect change
- 11. Avoid undifferentiated heavy lifting
- 12. Self-service
- 16. What will we need in the future?
- 17. 2012 - 2016 2012 Netflix: Originals and Expansion 2016 Netflix streams globally
- 19. Genie
- 20. Genie
- 21. Metacat
- 22. Metacat
- 24. 2012 Datacenter -> AWS 2013 What’s happening?
- 25. Lipstick
- 27. Sting
- 28. Sting
- 30. Pensive
- 32. Charlotte
- 34. 2012 Datacenter -> AWS 2013 What’s happening? 2014 Better Patterns .
- 38. Kragle
- 39. Kragle
- 42. Big Data Portal
- 43. Big Data Portal
- 45. 2012 Datacenter -> AWS 2013 What’s happening? 2014 Better Patterns . 2015 Prepare for Scale
- 50. Kragle Genie Metacat Redshift Presto HiveSpark S3 Pig Big Data Portal Docker
- 53. Spinnaker
- 54. Commuter
- 55. Commuter
- 57. Microbots
- 58. Insight
- 59. Insight
- 60. What will we need in the future?
- 62. Data Platform ML Analysis Visualization
- 64. We currently have 100s of TB of usage data.
- 65. Thanks