Dynamic Request Splitting for Interactive Cloud Applications

Deploying interactive applications in the cloud is a challenge due to the high variability in performance of cloud services. In this paper, we present Dealer - a system that helps geo-distributed, interactive and multi-tier applications meet their stringent requirements on response time despite such variability. Our approach is motivated by the fact that, at any time, only a small number of application components of large multi-tier applications experience poor performance. Dealer continually monitors the performance of individual components and communication latencies between them to build a global view of the application. In serving any given request, Dealer seeks to minimize user response times by picking the best combination of replicas (potentially located across different data centers). While Dealer requires modifications to application code, we show the changes required are modest. Our evaluations on two multi-tier applications using real cloud deployments indicate the 90%ile of response times could be reduced by more than a factor of 6 under natural cloud dynamics. Our results indicate the cost of inter-data-center traffic with Dealer is minor, and that Dealer can in fact be used to reduce the overall operational costs of applications by up to 15% by leveraging the difference in billing plans of cloud instances.