When it all Goes Wrong |Nordic PGDay 2019 | Will Leinweber
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You're woken up in the middle of the night to your phone. Your app is down and you're on call to fix it. Eventually you track it down to "something with the db," but what exactly is wrong? And of course, you're sure that nothing changed recently… Knowing what to fix, and even where to start looking, is a skill that takes a long time to develop. Especially since Postgres normally works very well for months at a time, not letting you get practice! In this talk, I'll share not only the more common failure cases and how to fix them, but also a general approach to efficiently figuring out what's wrong in the first place.
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When it all Goes Wrong |Nordic PGDay 2019 | Will Leinweber
- 1. When it all Goes Wrong Nordic PGDay 2019 — March 19 — Copenhagen
- 2. @leinweber Will Leinweber @leinweber Citus Data (Microsoft) bitfission.com (warning autoplays midi)
- 3. @leinweber coming from citus cloud heroku postgres
- 4. @leinweber special thanks citus cloud — dan farina (@danfarina) heroku postgres — maciek sakrejda (@uhoh_itsmaciek)
- 5. @leinweber same sorts of problems from pages & alerts from support tickets
- 6. @leinweber this talk more app dev who uses postgres rather than dba
- 7. @leinweber the problem with Postgres it’s pretty good you don’t get experience with how it breaks
- 8. @leinweber what to do for a problem
- 9. @leinweber what to do for a problem
- 11. @leinweber using the database (too much) 95% application 4% auto vacuum 1% everything else
- 12. @leinweber hard to convince all the graphs saying DB is slow and nothing has changed …must be the database!
- 14. @leinweber “but I didn’t change anything” no deploys! no database migrations! no scaling!
- 15. @leinweber “but I didn’t change anything” https://upload.wikimedia.org/wikipedia/commons/0/09/Redherring.gif
- 16. @leinweber “but I didn’t change anything” more traffic? change in access patterns? one big user logged in?
- 17. @leinweber run out of a resource
- 19. @leinweber example manageable user 1s query => 2x expensive frequent, small queries 3ms => 12ms
- 21. @leinweber assumptions postgres should not crash …with overcommit off and no containers large extensions increase chance
- 22. @leinweber if not postgres, then what
- 23. @leinweber system resources cpu memory disk parallelism / backends locks
- 24. @leinweber cpu mem disk parallelismcpu mem disk parallelism
- 25. @leinweber cpu mem disk parallelism credentials wrong networking broken locking issue, check pg_locks idle in transaction
- 26. @leinweber cpu mem disk parallelism application submitting backlogged workload connection leak pool sizes set too large pg_lock issue + application backlog
- 27. @leinweber cpu mem disk parallelism workload skew causing thrashing unusual sequential scan workload failover or restart => no cache pg_prewarm
- 28. @leinweber cpu mem disk parallelism same as just disk, but also the application is piling on
- 29. @leinweber cpu mem disk parallelism large GROUP BYs high disk latency due to unusual page dispersion pattern in the workload
- 30. @leinweber cpu mem disk parallelism workload has high mem (GROUP BY) + app adding backlog lock contention slowing mem release
- 31. @leinweber cpu mem disk parallelism large GROUP BYs + paging in unusual data
- 32. @leinweber cpu mem disk parallelism Look for what is causing disk access
- 33. @leinweber cpu mem disk parallelism small, in-memory workload lots of seq scans on small table index scan w/ filter dropping lots
- 34. @leinweber cpu mem disk parallelism app backlog + too much processing on small data simply a lot of work
- 35. @leinweber cpu mem disk parallelism large seq scans
- 36. @leinweber cpu mem disk parallelism loading cold data + application backlog
- 37. @leinweber cpu mem disk parallelism small # of backends doing a lot more work
- 38. @leinweber cpu mem disk parallelism entity, workload, entity*workload soft deletes and non-conditional indexes
- 39. @leinweber cpu mem disk parallelism reporting query
- 40. @leinweber cpu mem disk parallelism app backlog, but with CPU/mem problems
- 41. @leinweber tools of the trade
- 42. @leinweber tools of the trade C symbols
- 43. @leinweber tools of the trade: perf perf record -p <pid> && perf report
- 44. @leinweber tools of the trade: perf perf top
- 45. @leinweber tools of the trade: perf www.brendangregg.com/perf.html
- 46. @leinweber tools of the trade: gdb gdb -batch -ex 'bt' -p <pid>
- 47. @leinweber
- 48. @leinweber
- 49. @leinweber tools of the trade: iostat iostat -xm 10
- 50. @leinweber tools of the trade: iotop
- 51. @leinweber tools of the trade: htop
- 52. @leinweber Tools of the trade: bwm-ng
- 53. @leinweber tools of the trade: backends pgrep -lf postgres + grep + wc select * from pg_stat_activity
- 54. @leinweber tools of the trade: pg_s_s select * from pg_stat_statements
- 55. @leinweber tools of the trade: summary cpu mem disk parallelism network perf x gdb x iostat x iotop x htop x x bwm x pgrep x
- 57. @leinweber what to do configuration change
- 58. @leinweber what to do db change
- 59. @leinweber what to do code change
- 60. @leinweber flirting with disaster Velocity NY 2013: Richard Cook "Resilience In Complex Adaptive Systems” Jens Rasmussen: Risk management in a dynamic society: a modeling problem
- 68. @leinweber flirting with disaster Velocity NY 2013: Richard Cook "Resilience In Complex Adaptive Systems” Jens Rasmussen: Risk management in a dynamic society: a modeling problem