This document discusses measuring performance impact on Chrome OS. It recommends using chrome://tracing and Tast to analyze performance. Performance analysis involves observing differences, collecting data, analyzing it, implementing changes, and checking for improvements. Manual analysis can be expensive, error-prone, and difficult for fast releases. Integration testing refines test strategies, develops automated tests using Tast, deploys tests to Tast, and generates reports on chromeperf.appspot.com to track performance on target devices.

1. Measuring performance impact
of your changes on Chrome OS
Tiago Vignatti
BlinkOn 16

2. Motivation #1
Chromium dev: "I just landed this CL. Could you
test to see if there's any performance regression
in our target devices?"

3. Motivation #2
Chromium dev: "I got this performance related
bug assigned to me but I don't know where start
looking"

4. tl;dr
For Chrome OS, learn chrome://tracing and Tast

5. Measuring performance impact

6. Measuring performance impact
Performance analysis

7. Measuring performance impact
Performance analysis
Integration testing

8. Performance analysis
Observe
performance
difference

9. Performance analysis
Observe
performance
difference
Collect data

10. Performance analysis
Observe
performance
difference
Collect data Analysis

11. Performance analysis
Observe
performance
difference
Collect data Analysis Implement
changes

12. Performance analysis
Observe
performance
difference
Collect data Analysis Implement
changes

13. Performance analysis
Observe
performance
difference
Collect data Analysis Implement
changes
DID WE
IMPROVE?

14. Performance analysis
Observe
performance
difference
Collect data Analysis Implement
changes
chrome://tracing

15. Performance analysis
Are we done? But how all target devices are being tracked?

16. Performance analysis
Are we done? But how all target devices are being tracked?
Manual analysis can be cumbersome

17. Performance analysis
Are we done? But how all target devices are being tracked?
Manual analysis can be cumbersome
● very expensive

18. Performance analysis
Are we done? But how all target devices are being tracked?
Manual analysis can be cumbersome
● very expensive
● prone to human error

19. Performance analysis
Are we done? But how all target devices are being tracked?
Manual analysis can be cumbersome
● very expensive
● prone to human error
● difficulty on fast releases

20. Integration testing

21. Integration testing
1. REFINE TEST STRATEGY
Initial
Development
Launch

22. Integration testing
1. REFINE TEST STRATEGY 2. AUTOMATED TEST
DEVELOPMENT
Initial
Development
Launch

23. Integration testing
1. REFINE TEST STRATEGY 2. AUTOMATED TEST
DEVELOPMENT
3. DEPLOY TO RUN
Initial
Development
Launch

24. Integration testing
1. REFINE TEST STRATEGY 2. AUTOMATED TEST
DEVELOPMENT
3. DEPLOY TO RUN
4. GENERATE REPORTS
Initial
Development
Launch

25. Integration testing
1. REFINE TEST STRATEGY
Go
2. AUTOMATED TEST
DEVELOPMENT
Tast tests
3. DEPLOY TO RUN
Tast
4. GENERATE REPORTS
chromeperf.appspot.com
and other perf dashs
Launch Initial
Development

26. Key takeaways
Performance analysis: many hours on
chrome://tracing then analysis
Integration testing: Go and Tast

27. Thanks