Pivotal Labs Lunch Talk; 3 Infrastructure and workflow lessons learned at an early stage startup
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Pivotal Labs Lunch Talk; 3 Infrastructure and workflow lessons learned at an early stage startup
- 1. Rainforest QA Lunch talk:! 3 Infrastructure + workflow lessons learned at an early-stage startup rainforest @rainforestqa
- 2. Rainforest Human powered QA SaaS Designed for ‘Continuous QA’ Built for PMs and Developers rainforest @rainforestqa
- 3. Us Team of 3 in SoMa All developers YC S12 rainforest @rainforestqa
- 4. 3 Infrastructure + workflow lessons learned rainforest @rainforestqa
- 5. #1: Mongo isn’t right for! early-stage SaaS rainforest @rainforestqa
- 6. (Aside: we 💖 Mongo) rainforest @rainforestqa
- 9. Transactions -> Less junk rainforest @rainforestqa
- 15. #2: QueueClassic > Resque! for simplicity rainforest @rainforestqa
- 19. #3: Use your own product! (aka dogfooding) rainforest @rainforestqa
- 20. Find your users’ pain! before they do rainforest @rainforestqa
- 22. Goal:! Rainforest + Continuous Delivery rainforest @rainforestqa
- 25. push -> circle -> rainforest rainforest @rainforestqa
- 26. push -> circle -> rainforest -> prod rainforest @rainforestqa
- 27. Rainforest tests fail = no deploy rainforest @rainforestqa
- 28. Step 1: Built CLI client rainforest @rainforestqa
- 30. Step 2: Put in build process rainforest @rainforestqa
- 31. #1 - add gem! #2 - add to circle.yml rainforest @rainforestqa
- 32. Our Extreme Dogfooding rules rainforest @rainforestqa
- 33. #1 Make it disruptive rainforest @rainforestqa
- 34. #2 Fix it quickly rainforest @rainforestqa
- 38. < 20 mins to test rainforest @rainforestqa
- 41. ~9.5 hours of testing in ~20 min rainforest @rainforestqa
- 42. we run 5-10 x per day rainforest @rainforestqa
- 43. Conclusion Simpler = better Transactions = better Use your own product = better product rainforest @rainforestqa
Editor's Notes
- - Master - Run SF Mongo meetup
- - No support in mongo
- - Inconsistent data in db due to our code breaking - We fixed with helper scripts. Slow and sucked.
- - No formal or standard way of doing them - All complex or slow if large - Schema design suffers as a result
- - Non-trivial reporting queries require code - Great if you know what you’re after when you design your schema - Ours is evolving
- - We especially love window functions in PG
- - wanted to know how much each client costed us per week - this joins 4 tables, partitions by week and sorts by most expensive first
- - Don’t exist - Fix by de normalizing data - Usually results in-consistent data without transactions
- - No redis
- - We sent emails and enqueued jobs before things were consistent