Twitter’s 250+ million users generate tens of billions of tweet views per day. Aggregating these events in real time – in a robust enough way to incorporate into our products – presents a massive scaling challenge. In this talk I’ll introduce TSAR (the TimeSeries AggregatoR), a robust, flexible, and scalable service for real-time event aggregation designed to solve this problem and a range of similar ones. I’ll discuss how we built TSAR using Python and Scala from the ground up, almost entirely on open-source technologies (Storm, Summingbird, Kafka, Aurora, and others), and describe some of the challenges we faced in scaling it to process tens of billions of events per day.