qcsd-production-swarm

To assess production health after a software release, analyze DORA metrics, incident reports, and telemetry data to synthesize a HEALTHY, DEGRADED, or CRITICAL recommendation. This process identifies performance regressions and confirms system stability post-deployment.

Automating root cause analysis for production incidents involves orchestrating a multi-agent swarm to systematically investigate telemetry and incident reports. This identifies underlying causes of issues to prevent recurrence and generates actionable reports for engineering teams.

Yes, you can use DORA metrics and telemetry data to predict future defect trends. Analyzing these post-release metrics enables systematic defect prediction, closing the feedback loop to inform future quality improvements during Ideation and Refinement phases.

Closing the feedback loop after a production health assessment works by persisting learnings from incident root cause analysis to memory. It generates actionable reports that inform immediate engineering actions and future sprint planning to improve development cycles.

Yes, telemetry data is required alongside DORA metrics and incident reports to receive an accurate production health recommendation. The system analyzes these combined data sources to determine whether the production environment is HEALTHY, DEGRADED, or CRITICAL.