This is a desired list of enhancements. It's not currently ordered by priority:
- Build data drift monitoring baseline as part of the training process.
- Deploy a seperate endpoint as part of the production deployment.
- Track and fix data capture issue.
- Track and fix VPC endpoint issues.
- General UX improvements:
- Configuration interface.
- ...
- Implement better granular pipeline triggers, so that only selective files trigger pipeline runs.
- Provide reporting capabilities to unify code and model lineage currently tracked by disparate systems: CodeCommit and SageMaker Experiments.
- Provide simplified end-to-end rollback UX.
- Add more drop in ML pipeline templates eg. HPO
- Replace the default ml pipeline training step with an Autopilot job once it is supported by the Data Science SDK.