Deploying a pipeline to production endpoint allows your to begin using your model to get predictions immediately. Auger will deploy to lambda to return an array of predictions in json format.
Expanding the deployed pipeline row allows you try your endpoint, get a code snipped or share a url to this pipeline.
Try. Auger has an inline editor that allows you to paste records directly into it and then call predict to retrieve predictions. This is a nice way to validate your model with some new test data and see the return format when you do incorporate into your application.
Code. Currently code snippets in Curl and Python are available which show you how to format your request programatically.
Share url. A public URL to your deployed pipeline.