I was looking for the lowest friction solution to quickly to share my work with the team for review and collaboration. Currently, there are a lot of offerings for cloud-hosted notebooks and they all seem promising.

After tweaking an ML ensemble model for a few weeks it came time to deploy and in this case the project was utilizing an AWS pipeline. I had already dumped the trained model to an S3 bucket with joblib, so the goal now was to deploy an inference endpoint as an AWS Lambda function.

A few lesser documented simple functions I've found handy along the way...

I previously deployed an ML inference on AWS via the Serverless framework and at the time I was using a scikit-learn model with a couple standard libraries...

Pushing an ML docker container to AWS Lambda made easy with Serverless.