I am looking for a reference on applied machine learning, esp. around model deployment to production environments and model evaluation. There are plenty of references about models, how to learn models, how to engineer features ... but deploying models to production is not trivial at all. For example, how do you measure the performance of a new model, if there is an existing one deployed, and you don't want to perturb the actions of the first model too much? Is there any good reference on that kind of topic?