Here are some of the considerations:
- Model drift, dataset dependencies, and brittle pipelines
- Hidden biases accumulating over time
- Versioning challenges
Best approach to manage them includes:
- Establish model versioning
- Continuous monitorin
- Automated testing of inference
- Reproducible pipelines, and
- Code/data lineage tracking