1. Bits of Experience DB Scaling, Cloud Hosting, Code Quality

2. Hi! Nice to meet you.

3. I want to offer some insights Everything's different, there's not one set of rules for everyone.

4. Small Dev team, big system 10 Applications, Up to 5 stages, 36 machines.

5. Our main tool is Python Also lots of SQL; More JavaScript than we'd like; Even some Perl.

6. A few Tera Bytes of data Most of it in PostgreSQL. We like PostgreSQL a lot.

7. Agenda Things I'll dive into a little.

8. 1. Scaling Data What we do, why it works.

9. 2. To cloud or not to cloud We've mostly run on bare metal, but how much longer?

10. 3. Complexity and Code Quality A few thoughts.

11. There's no universal right or wrong I just want to provide an additional perspective.

12. We're storing advertising data Lots of data, but not quite Big Data.

13. A SaaS business Isolated customers, varying amounts of data.

14. All relational, structured data We aggregate and filter data a lot. SQL is great for that.

15. Starting small One database, relational model by the book.

16. Trying built-in PG partitioning It's useful, but very limited.

17. Maybe use schemas? Then we'd lose other schema use cases.

18. Partition using databases Each customer his own db. Scales very well.

19. Very good tool support DBs can be easily created, copied, dumped, restored, dropped.

20. Isolation also benefits security Nothing to rely on, but helpful nonetheless.

21. There are downsides, of course Overhead, connection management, no quick global queries.

22. For us, it's great Your mileage may vary.

23. Dedicated Hardware Good performance for little money.

24. Roots precede AWS Why move a working infrastructure?

25. B2B: growth better predictable Elasticity requirements are limited.

26. We're missing: Proper Failover Automatic failover of all components is not that trivial.

27. For a while: mixed setup Frontend on AWS. Async Backend on our HW. IPSEC in between.

28. Now: Something different Software development is hard.

29. Start-up vs. Enterprise How different can it be?

30. When is a start-up a start-up? And when not?

31. Lots of uncertainty Building, testing, learning.

32. Building good systems In a startup that's not always easy.

33. Time is always a constraint In small companies as in big.

34. Clean code is not what sells Unfortunately.

35. Fast now, right later? Technical debt will cost you big time

36. Small but steady Little things add up

37. Delete code, drop features Code is a liability.

38. Thanks for listening Time for questions.