Im trying to deploy a web app that takes 1 web input, then "Set Column In Dataset" a few times for each model , and then sends out a web output for each model.
Right now the way I have it setup is I have a few web inputs, then a model that runs for each, and then a web output for each. It works for now, but it's a hassle because every time I want to add a new model to be predicted I have to add a bunch of stuff in both azure and my web application. Just wondering if there is an easier way I'm missing.
I am not quite sure I understand the workflow you described. Can you provide more details on what are you trying to accomplish with your web app and your experiment? For example, what do you mean when you say "I have to add a bunch of stuff"?
Azure ML does support multiple web service inputs and outputs. Adding a new model to the experiment requires you to re-deploy your web service.