#DataDrivenDevOps
summary
Claims three concrete metrics to start tomorrow and shows applied tooling: Microsoft Excel for sampling and ROI checks, JIRA for tracking build‑stability issues, and an auto‑return for test environments that cuts ten saturated environments down to eight. Provides the actual signals collected (environment checkout counts, stability‑issue counts flattening around 75%), argues for representative vs complete sampling, warns about perverse incentives, and demonstrates fixes that measurably reduce waste and improve trust.
AI-written summary · about
chapters (13)
- 0:00Start
- 3:41OVERCONFIDENCE
- 4:28HARD TO GIVE UP
- 5:26HOW DEPARTMENTS MEASURE
- 8:36ENGINEERING METRICS IN PRE-DEVOPS ERA
- 10:01VELOCITY TO AGILE IS LIKE PROFIT TO DEVOPS...
- 12:34WHAT'S THE PROBLEM?
- 13:14TOO COARSE!
- 13:44THIS IS DEVOPS
- 14:34SAME FOR METRICS!
- 15:12HOW DO METRICS COLLABORATE?
- 31:41STEP INTO DATA-DRIVEN LIFE
- 33:11PLATINUM sponsors
related talks
37m#DataDrivenDevops
42mData-Driven DevOps
47mWithout Data, you're just another Person with Opinions
59mDevSecOps Productivity Metrics and Tools
30mA Story of DevOps Transformations
33mMeasuring Developer Efficiency in DevOps: Key Questions, Metrics, Best Practices
42mData Driven DevOps
44mOpening Keynote: Testing in the age of DevOps