Processing over 10 billion messages per day, PayPal's product performance tracking platform is one of the busiest systems in PayPal. And it is all constitutes an end-to-end reactive data processing pipeline consisting of Akka Streams, Kafka, Spark and Druid components. In this session, we will share our experiences putting together this pipeline in real life. We will address the technical and the organizational challenges of converting a well-established team into this reactive mindset. We will show how we channel the enthusiasm and the energy we had into large-scale adoption. We will also highlight economic benefits derived from greater resource utilization inherent with reactive systems adoption. This session puts explicit and implicit lessons we have learned into a single narrative useful for both beginner and intermediate audiences, builders and managers alike, helping contextualize conceptual and practical aspects of switching to reactive systems.