[Sloppy]

We developed an OSS ML Server called Harness. It does all ingest, prepare, Algorithm management, workflow bits for pugable ML "Engines". These are Algorithms + Datasets + Models and are flexible enough to do most anything. We use the build-in Universal Recommender Engine, and have built our own for other uses.

Harness exposes a framework for adding Engines and does all the routing for Engine Instance workflow and lifecycle management. It also provides a toolbox of abstractions for using the Spark ecosystem with Mongo and Elasticsearch.

It comes in a docker-compose system for vertical scaling and Kubernetes for ultimate in scaling an automation. Quite a nice general system with out of the box usefulness.

https://github.com/actionml/harness