Android Battery @ Facebook

on YouTube ↗37m

" summary

Shows how Facebook measures battery in production by instrumenting CPU frequency, radio bytes and tail time, camera open time, location accuracy and wake locks, then maps those proxies to energy using device power profiles so metrics are stable and not noisy. Describes using Android Studio, trepn and power monitors for spot checks, Battery Historian for logs, a CPU spin detector that uploads aggregated stack traces, and an open source battery metrics library. Catches an 11% energy regression, fixes animation and camera leaks and ships.

AI-written summary · about

" chapters (25)

1. 0:00Introduction to battery monitoring
2. 1:26Challenges measuring battery usage
3. 3:11Tools for battery debugging
4. 5:39Problems with device-level battery metrics
5. 8:02Hardware component power modeling
6. 10:53CPU power consumption measurement
7. 11:14Radio tail energy and batching
8. 13:20Camera and location power tracking
9. 15:07GPU power measurement difficulties
10. 15:50Screen power consumption overview
11. 16:52Energy breakdown by app state
12. 18:39Secondary process instrumentation
13. 19:02Avoiding battery drain from measurement
14. 20:26Tracking power metrics across releases
15. 21:48Power profile validation and use
16. 23:56Detecting battery regressions
17. 25:19Thread-level CPU attribution
18. 26:22CPU spin detector tool
19. 27:25Animation leak detection
20. 29:08Network power attribution
21. 29:56Camera and location leak detection
22. 31:17Wake locks and job scheduler monitoring
23. 31:59Key points for battery efficiency
24. 34:04Battery Metrics open source library
25. 36:11Q&A on React Native and battery

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