Another approach, which I think is more preferable, is to build a separate pipeline that monitors new training data in s3 and triggers training job - if you are using BentoML for model serving deployment, BentoML supports updating an existing deployment to a newer version - that work is still working in progress though. Support for deployment update in AWS lambda and AWS fargate are coming soon.