Have you guys run into the issue of gRPC being used for ML inference engines/platforms, and having the message size be an issue? Recently, I was working on bui

Have you guys run into the issue of gRPC being used for ML inference engines/platforms, and having the message size be an issue? Recently, I was working on building the backend for our Speech Recognition engine and it seems like the message size limit came in the way of being able to perform batch/offline inference. I might be lacking some of the intuition behind designing and deploying such services, and am curious if you guys have run into this issue. The platform doesn't seem to accept the channel options from the client. That and the issue of no easy way to do gRPC calls from a browser yet, and the resulting architecture then needing to have been built the ground up with considerations for an extra piece - a gateway, or something like Envoy to make it more accessible over the web. I feel like that would be okay if I was working on a project with k8 ingress set up already and already utilizing microservices. But for getting running it seems like added complexity. Not hating on it or anything, just sharing my experiences and thoughts, hoping that some of you might've had experience reasoning and dealing with such designs and can offer some insight.