Throw Away Your Nines
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People want their computer services to operate well, and consequently they often set targets for how reliable they hope to be. In addition to target percentages, percentiles are often used to make it easier to examine the data for most user experiences, while ignoring the outliers. But problems often arise because of a tendency to only think about "nines". All services and user experiences are unique, and it is all too common to ignore important data or stress your systems and humans by trying to be more performant than you need to be. Throw away your nines, and let's find some better numbers to use instead.
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Throw Away Your Nines
- 1. Brought to you by Throw Away Your Nines Alex Hidalgo Principal Reliability Advocate at Nobl9
- 2. Alex Hidalgo Principal Reliability Advocate at Nobl9 @ahidalgosre ■ Over a decade of SRE experience ■ Previous work includes food service, retail, game show host, and DJ ■ Wrote Implementing Service Level Objectives ■ Probably tweets too much
- 3. We live in a world of nines…
- 5. Let’s dig in a bit…
- 6. Percentiles ■ Primarily a way to talk about frequency distributions ■ Primarily used in tech for handling outliers or tails ■ Especially used for discussing latency
- 7. Percentages ■ Exist in many different forms ■ Used to think about sets of data ■ Often used in tech to talk about availability or error rates
- 8. SLOs ■ Service level objectives ■ An approach to measuring reliability ■ A decision making tool
- 9. SLAs ■ Service level agreements ■ Contractually obligated commitments ■ Imply recompense
- 10. P99 Conf ■ This conference ■ Named after a common percentile
- 12. Why are nines a problem? Percentiles SLOs P99 Conf
- 13. The Problem of Nines and Percentiles
- 16. Percentiles (normal distribution w/P99) CO U N T VALUES
- 17. Do not @ me about the accuracy of these
- 18. Percentiles (long tail distribution) CO U N T VALUES
- 19. Percentiles (long tail distribution w/P99) CO U N T VALUES
- 20. Percentiles (long tail distribution w/P99 & P95) CO U N T VALUES
- 22. Percentiles (bimodal distribution w/P99) CO U N T VALUES
- 23. Percentiles (bimodal distribution w/P99 & P95) CO U N T VALUES
- 24. Percentiles (left skewed distribution) CO U N T VALUES
- 26. Percentiles (some kind of distribution) CO U N T VALUES
- 27. Percentiles (some kind of distribution w/P99) CO U N T VALUES
- 28. How did we end up here?
- 29. The 99th Percentile ■ It’s common to want to capture a lot of data ■ People copy what already exists ● Dashboards ● Alerts ● Queries
- 30. People start at P9X all the time
- 31. Be meaningful in your decisions Don’t just copy what has come before
- 32. The Problem of Nines and SLOs
- 33. Service Level Objectives ■ Measurements used to help us think about our service reliability ■ And we want to be very reliable! ■ So lots of nines!
- 34. SO MANY NINES “Two Nines” = 99% “Three Nines” = 99.9% “Four Nines” = 99.99% “Five Nines” = 99.999%
- 35. What do these nines even mean? Target Per Day Per Month Per Year 99% 14m 24s 7h 18m 3d 15h 99.9% 1m 26s 43m 97s 8h 45m 99.99% 8.6s 4m 23s 52m 35s 99.999% 0.9s 26s 5m 15s
- 41. How did we end up here?
- 42. Too Many Nines SLO Targets ■ It’s common to want to be very reliable ■ This locks you into targets that are: ● Unachievable ● Unrealistic ● Don’t match the reality of a service ■ People don’t think about what users actually need
- 43. Be meaningful in your decisions Don’t just copy what has come before
- 44. The Problem of Nines and P99 Conf
- 45. Nothing - Nines are Just Fine
- 46. Being meaningful in your decisions should include looking to the past
- 47. Because sometimes what was done before was actually a really good idea
- 48. Brought to you by Alex Hidalgo Principal Reliability Advocate at Nobl9 @ahidalgosre