Rubik: Unlocking the Power of Locality and End-point Flexibility in Cloud Scale Load Balancing

Cloud scale load balancers, such as Ananta and Duet are critical components of the data center (DC) infrastructure, and are vital to the performance of the hosted online services. In this paper, using traffic traces from a production DC, we show that prior load balancer designs incur substantial overhead in the DC network bandwidth usage, due to the intrinsic nature of traffic redirection. Moreover, in Duet, traffic redirection results in extra bandwidth consumption in the core network and breaks the full-bisection bandwidth guarantees offered by the underlying networks such as Clos and FatTree.

We present RUBIK, a load balancer that significantly lowers the DC network bandwidth usage while providing all the performance and availability benefits of Duet. RUBIK achieves its goals by applying two principles in the scale-out load balancer design—exploiting locality and applying end-point flexibility in placing the servers. We show how to jointly exploit these two principles to maximally contain the traffic load balanced to be within individual ToRs while satisfying service-specific failure domain constraints. Our evaluation using a testbed prototype and DC-scale simulation using real traffic traces shows that compared to the prior art Duet, RUBIK can reduce the bandwidth usage by over 3x and the maximum link utilization of the DC network by 4x, while providing all the performance, scalability, and availability benefits.