Using the DevOps Pipeline to Generate Continuous, Valuable Insights
summary
A predictive QA engine ingests logs and metadata from Jenkins pipelines, Sonar, Docker builds and test-management tools and returns a runtime test configuration over a REST API so the pipeline runs only required tests. A demo shows smoke dropping to 37 seconds and regression to ~22s; a mobile-device case study reports 30% test time reduction and 50% resource utilization savings. The system uses historical labeling, text classification to map components, and adaptive regression models that improve with each run.
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chapters (14)
- 0:00Introduction
- 0:47Who is Darren
- 1:47Agenda
- 3:41Release Cycles
- 5:05Make the Pipeline Smarter
- 9:35Smart DevOps
- 10:25Leveraging Data
- 12:33Demo
- 17:35Action Rate
- 21:15Data Classification
- 22:53Risk Prediction
- 24:36Regression
- 26:32Rest Interface
- 28:05Case Study
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