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What We Learned from Three Years of Sciencing the Crap Out of DevOps
- 1. What We Learned from Three Years Sciencing the Crap Out of Devops Jez Humble @jezhumble Nicole Forsgren, PhD @nicolefv © 2016 DevOps Research and Assessments LLC. CC-BY-SA
- 2. Outline How to make your data suck less ● Writing good survey questions ● Making sure the survey questions are good - with SCIENCE What we found… that we did (AND didn’t) expect Things about Continuous Delivery Things about Management
- 3. Not all data is created equal Who here thinks surveys are sh*t? [Nicole should probably turn around]
- 4. Not all data is created equal Who here thinks surveys are sh*t? [Nicole should probably turn around] Who here LOVES the data from their log files? And who has seen sh*t data in a log file?
- 5. What is a Latent Construct?
- 6. We use PSYCHOMETRICS to make our survey data good* *or give us a reasonable assurance that it’s telling us what we think it’s telling us (& some of this can also apply to your log data)
- 7. Psychometrics includes: Construct creation (manual) ● When possible: use previously validated constructs ● Based on definitions and theory, carefully and precisely worded, card sorting task, pilot tested Construct evaluation (statistics) ● Establishing Validity: discriminant and convergent ● Establishing Reliability
- 8. Psychometrics Writing Example: Culture ● Does it matter to our study? ○ More than just intuition? ● What KIND of culture? ○ National identity and norms ○ Adaptive culture ○ Value learning (2014 study) ○ Value information flow and trust (2014 and 2015 studies -- Westrum culture)
- 9. Psychometrics Writing Example: Culture ● Does it matter to our study? ○ More than just intuition? ● What KIND of culture? ○ National identity and norms ○ Adaptive culture ○ Value learning (2014 study) ○ Value information flow and trust (2014 and 2015 studies -- Westrum culture)
- 10. Westrum typology Pathological Power-oriented Bureaucratic Rule-oriented Generative Performance-oriented Low cooperation Modest cooperation High cooperation Messengers shot Messengers neglected Messengers trained Responsibilities shirked Narrow responsibilities Risks are shared Bridging discouraged Bridging tolerated Bridging encouraged Failure leads to scapegoating Failure leads to justice Failure leads to inquiry Novelty crushed Novelty leads to problems Novelty implemented Try writing items yourself! Use strong statements with clear language.
- 11. Westrum Culture Items ● On my team, information is actively sought. ● On my team, failures are learning opportunities, and messengers of them are not punished. ● On my team, responsibilities are shared. ● On my team, cross-functional collaboration is encouraged and rewarded. ● On my team, failure causes inquiry. ● On my team, new ideas are welcomed. Found to be valid & reliable Predictive of IT Performance & Organizational Performance
- 12. Psychometrics Analysis Example: Notification of Failure At my organization… ● We are primarily notified of failures by reports from customers. ● We are primarily notified of failures by the NOC. ● We get failure alerts from logging and monitoring systems. ● We monitor system health based on threshold warnings (ex. CPU exceeds 100%). ● We monitor system health based on rate-of-change warnings (ex. CPU usage has increased by 25% over the last 10 minutes). Original in 2014, but there was a surprise. Can you spot it?
- 13. Psychometrics Analysis Example: Notification of Failure At my organization… ● We are primarily notified of failures by reports from customers. ● We are primarily notified of failures by the NOC. ● We get failure alerts from logging and monitoring systems. ● We monitor system health based on threshold warnings (ex. CPU exceeds 100%). ● We monitor system health based on rate-of-change warnings (ex. CPU usage has increased by 25% over the last 10 minutes). Notification from INSIDE Notification from OUTSIDE
- 14. More data tests! Plus, we test to make sure the survey doesn’t have other problems. ● Common method variance (CMV) (aka CMB for Bias) ● Early vs. late responders ● Survey drop-off rates and bias
- 15. Okay NOW we can look at the data
- 16. IT performance matters! “Firms with high-performing IT organizations were twice as likely to exceed their profitability, market share and productivity goals.” http://bit.ly/2014-devops-report/ http://bit.ly/2015-devops-report/
- 17. IT performance lead time for changes release frequency time to restore service change fail rate
- 18. Continuous delivery Okay NOW we can look at the data.
- 19. And now with added math Forsgren, N., J. Humble (2016). "The Role of Continuous Delivery in IT and Organizational Performance." In the Proceedings of the Western Decision Sciences Institute (WDSI) 2016, Las Vegas, NV. Available at SSRN: http://ssrn. com/abstract=2681909
- 20. some surprises
- 21. What’s not strongly correlated w/ ITPerf? Third-party scripts Homegrown scripts Commercial configuration management tools Open source Golden images Manual configuration management
- 22. What’s not strongly correlated w/ ITPerf? Third-party scripts Homegrown scripts Commercial configuration management tools Open source Golden images Manual configuration management
- 23. Which of these measure effective test practices? Developers primarily create & maintain acceptance tests QA primarily create & maintain acceptance tests Primarily created & maintained by outsourced party When automated tests pass, I’m confident the software is releasable Test failures are likely to indicate a real defect It’s easy for developers to fix acceptance tests Developers share a common pool of test servers to reproduce failures Developers create on demand test environments Developers use their own dev environments to reproduce failures
- 24. Which of these measure effective test practices? Developers primarily create & maintain acceptance tests QA primarily create & maintain acceptance tests Primarily created & maintained by outsourced party When automated tests pass, I’m confident the software is releasable Test failures are likely to indicate a real defect It’s easy for developers to fix acceptance tests Developers share a common pool of test servers to reproduce failures Developers create on demand test environments Developers use their own dev environments to reproduce failures
- 25. Change management All production changes must be approved by an external body (e.g. change approval board, manager, etc.) before deployment or implementation (R) Only high-risk changes, such as database changes, require approval We have no change approval process We rely on peer review to manage changes
- 26. Change management All production changes must be approved by an external body (e.g. change approval board, manager, etc.) before deployment or implementation (R) Only high-risk changes, such as database changes, require approval We have no change approval process We rely on peer review to manage changes
- 27. Now for management stuff We all know managing WIP is important, right?
- 28. Now for management stuff We all know managing WIP is important, right? Correlation between WIP and ITPerf is negligible
- 29. Now for management stuff We all know managing WIP is important, right? Correlation between WIP and ITPerf is negligible What’s going on?
- 31. Conclusions Even if you think it’s obvious, TEST WITH DATA. (if the results don’t surprise you, you’re doing it wrong) (if you don’t also confirm some things you expected, you’re doing it wrong) We CAN have it all, or at least throughput AND stability. DevOps culture & practices have a measurable impact on IT & org perf
- 32. Stay tuned! Take the 2016 State of DevOps Survey late March Read the 2016 State of DevOps Survey results late June Want to know how your OWN DevOps Capabilities compare? just pick up your phone and send an email to: jezhumble@sendyourslides.com subject: devops