This is close to home. Our approach to DevOps for ML Data is to use S3 as the git core and build immutable datasets and models on top of S3 object versioning. I wrote the piece below on "Versioning data and models for faster iteration in ML" earlier this year. The key idea is for every model iteration to be a pure function F(code, environment, data). Ideas welcome: https://medium.com/pytorch/how-to-iterate-faster-in-machine-...