A deployment's feature distributions change significantly after a new upstream data release. What should happen before automatically retraining and promoting?

1. Change feature order silently to match whichever source arrives
2. Investigate data quality and drift, evaluate candidate models, and apply release criteria
3. Promote any retrained model without validation
4. Ignore all distribution shifts if the endpoint remains available