Ray uses apache arrow plasma store to avoid the copy and serialization costs that usually come with multiprocessing in python.
Most of the models I use can be converted to a more optimized formats for inference like https://treelite.readthedocs.io/en/latest/ so the code and interfaces are pretty similar and it makes the architecture less complex to update and deploy.
Depending on string names and handles is also very hacky and completely cripples PyCharm autocomplete / type checking.
The core of the project is great though. We're working on a video processing system that has a ton of downstream models and using Ray makes it possible to get away with running inference in pytorch without going down the TensorRT/inference engine rabbit hole (would be torture for some of our detection and sequential models).
For anyone looking into it I recommend starting with their Architecture Doc(https://docs.google.com/document/d/1lAy0Owi-vPz2jEqBSaHNQcy2...) and Design Patterns (https://docs.google.com/document/d/167rnnDFIVRhHhK4mznEIemOt...) Docs.