Analyzes OpenShift release regression metrics to grade component health and identify triage bottlenecks.
This skill automates the evaluation of OpenShift component health by analyzing regression management metrics across specific release cycles. It calculates critical KPIs such as triage coverage, response timeliness, and resolution speed to generate automated scorecards. By identifying components with high untriaged regression counts or slow resolution times, it helps engineering teams prioritize effort, improve release quality, and maintain high standards for regression handling through both text-based summaries and interactive HTML reports.
Key Features
01Identification of actionable open regressions requiring immediate attention
02Generation of interactive HTML reports for stakeholder communication
03Per-component performance scorecards with ranked health status
04Automated health grading based on triage coverage and resolution speed
0541 GitHub stars
06Release-specific analysis using dynamic development windows and GA dates
Use Cases
01Evaluating team performance and component stability during an OpenShift release cycle
02Identifying specific components that need additional resources for regression handling
03Generating quality health reports for stakeholders and release readiness meetings
