What events trigger automatic model retraining beyond code changes?

This tests whether you design ML systems as event-driven pipelines rather than treating them like standard software CI/CD. A strong answer covers six trigger categories in order: data drift and schema changes detected in the feature store; scheduled cron or batch windows; production model performance degradation or concept drift; upstream data pipeline completion events; dependency or base image updates; and manual business-driven triggers.