The Developer's DevOps Mountain

Slides I presented at WebPerfDays Barcelona 2014 - a little more context on the slides available at http://trp0.wordpress.com/2014/11/24/the-developers-devops-mountain/

Transcript

1. Department of Informatics The Developer’s DevOps Mountain If the developer won’t go to the metrics, the metrics must go to the developer Jürgen Cito, Christian Bosshard, Philipp Leitner WebPerfDays 2014, Barcelona
2. 2 MSc, Technical University of Vienna Research Intern @ Catchpoint, New York Statistics in Web Performance Monitoring PhD Candidate, University of Zurich Software Evolution and Architecture Lab Software Engineering </> Cloud Computing Jürgen Cito @citostyle
3. 3 cloudwave-fp7.eu @CloudWaveFP7
4. Software Development in the Cloud [Interview and Survey Study] Preprint available: http://arxiv.org/abs/1409.6502 4
5. 5 Exploratory Study Interviews Coding & Analysis Quantitative Survey
6. Tools for Cloud Software Development 6
7. 7 Quantitative Survey
8. Quantitative Survey 8 62% say more metrics are available in the cloud
9. Reality: Majority of study participants reported that they rather go “by intuition” than look at metrics 9
10. Ops be like… 10 https://www.youtube.com/watch?v=ZC56jND10V4 “I gave you everything you needed, you piece of …”
11. DevOps Mountain 11 Source: https://flic.kr/p/phfUy4 (Stoos, Switzerland) “I gave you everything you needed, you piece of …” If the developer won’t go to the metrics… …the metrics must go to the developer
12. How? Serve application level metrics for developers in their IDE (+do some predictive analysis) 12
13. Use Case Application (VoIP Client) 13 •  Use Case: Lookup Online status of users •  Users can be queried from a “User Directory Service”
14. Predictive Performance Analysis in the IDE 14
15. 15 High-Level Architecture
16. Software Performance Anti-Patterns Hot Spots / Hot Paths Loops (Redundancy in inner/outer loops, inefficient inner/outer loops) Too Many Remote Calls n+1 selection problem … 16
17. Conclusion Study shows that more performance metrics are widely available, but developers rather go “by intuition” Tighter feedback loop between the runtime environment and the development environment (IDE) 17
18. Conclusion (cont’d) Predictive analysis helps to identify performance issues before the developer even commits Continuous evolution of software and informed architecture decisions 18 Jürgen Cito @citostyle cito@ifi.uzh.ch Slides at speakerdeck.com/citostyle