Completed
Systems scale with load.
Class Central Classrooms beta
YouTube videos curated by Class Central.
Classroom Contents
Refining Systems Data without Losing Fidelity
Automatically move to the next video in the Classroom when playback concludes
- 1 Intro
- 2 Complex systems are hard to manage.
- 3 User experiences.
- 4 User experiences marbles.
- 5 without breaking the bank?
- 6 Three strategies for taming the spew.
- 7 Reduce. Reuse. Recycle.
- 8 Store less data.
- 9 Stop writing read-never data.
- 10 First, structure your data.
- 11 One event per transaction.
- 12 Often, trimming isn't enough.
- 13 Sample your data.
- 14 Statistics to the rescue!
- 15 Count 1/N events.
- 16 Count traces together.
- 17 Don't be afraid of sample rates.
- 18 Don't believe me? Ask a data scientist.
- 19 Aggregate data.
- 20 Aggregation destroys cardinality.
- 21 Temporal correlation is weak.
- 22 Math on quantiles is misleading.
- 23 Aggregation is a last resort.
- 24 How can sampling be cheap enough?
- 25 Systems scale with load.
- 26 Reconcile using the sample rate.
- 27 How can we save the relevant events?
- 28 Normalize per-key.
- 29 Different key, different probability.
- 30 Retain errors & slow queries.
- 31 Metrics and events can be friends!
