Ask HN: What is your ML stack like?
What didn't work:Shipping pickled models to other teams.Deploying Sagemaker endpoints (too costly).Requiring editing of config files to deploy endpoints.What did work:Shipping http endpoints.Deriving api documentation from model docstrings.Deploying lambdas (less costly than Sagemaker endpoints).Writing a ~150 line python script to pickle the model, save a requirements.txt, some api metadata, and test input/output data.Continuous deployment (after model is saved no manual intervention if model response matches output data).