Production input distributions diverge substantially from the training dataset, but outcome labels arrive much later. Which approach best fits?

1. Evaluate and monitor relevant subgroup metrics.
2. Monitor serving reliability separately from model-quality metrics.
3. Monitor feature distribution drift and investigate its impact.
4. Monitor task-quality metrics using the delayed ground truth.