Cuckoo: Scaling Microblogging Services with Divergent Traffic Demands

Today’s microblogging services such as Twitter have long outgrown their initial designs as SMSbased social networks. Instead, a massive and steadily-growing user population of more than 100 million is using Twitter for everything from capturing the mood of the country to detecting earthquakes and Internet service failures. It is unsurprising that the traditional centralized client-server architecture has not scaled with user demands, leading to server overload and significant impairment of availability. In this paper, we argue that the divergence in usage models of microblogging services can be best addressed using complementary mechanisms, one that provides reliable messages between friends, and another that delivers events from popular celebrities and media outlets to their thousands or even millions of followers. We present Cuckoo, a new microblogging system that offloads processing and bandwidth costs away from a small centralized server base while ensuring reliable message delivery. We use a 20day Twitter availability measurement to guide our design, and trace-driven emulation of 30,000 Twitter users to evaluate our Cuckoo prototype. Compared to the centralized approach, Cuckoo achieves 30-50% server bandwidth savings and 50-60% CPU load reduction, while guaranteeing reliable message delivery.