I think a decent solution is coming up with a system for storing the models and datasets, checkpoints, etc. in S3 - store the metadata, references, etc. in a well structures postgres table (schema versioning, audit logs, etc. with snapshots). Also, embedding the metadata in the model/dataset as well, in a way you could always reconstruct the database from the artifacts (in Arrow and Parquet files, you can embed arbitrary metadata at the file-level and the field level).

But perhaps the best solution is to just use something like MlFlow or WandB that handles this for you, if you use the API correctly!