Online recommender systems are increasingly prevalent given their ability to adapt to the customer's needs in real time. Nonetheless, they come with additional costs (computation, operational) and complexity (infrastructure). In this keynote, we explore when it makes sense to use an online recommender and when a batch recommender is good enough. Then, to better understand the diferentiating strengths of online recommenders, we share three systems at Amazon Books that play to these strengths, high-level results, and lessons from making them work in the field.