Improving Tail Latency of Stateful Cloud Services via GC Control and Load Shedding

Abstract

Most of the modern cloud web services execute on top of runtime environments like .NET's Common Language Runtime or Java Runtime Environment. On the one hand, runtime environments provide several off-the-shelf benefits like code security and cross-platform execution. On the other hand, runtime's features such as just-in-time compilation and automatic memory management add a non-deterministic overhead to the overall service time, increasing the tail of the latency distribution. In this context, the Garbage Collector (GC) is among the leading causes of high tail latency. To tackle this problem, we developed the Garbage Collector Control Interceptor (GCI) - a request interceptor algorithm, which is agnostic regarding the cloud service language, internals, and its incoming load. GCI is wholly decentralized and improves the tail latency of cloud services by making sure that service instances shed the incoming load while cleaning up the runtime heap. We evaluated GCI's effectiveness in a stateful service prototype, varying the number of available instances. Our results showed that using GCI eliminates the impact of the garbage collection on the service latency for small (4 nodes) and large (64 nodes) deployments with no throughput loss.