The Case for RackOut: Scalable Data Serving Using Rack-Scale Systems

Stanko Novakovic, Alexandros Daglis, Edouard Bugnion, Babak Falsafi, Boris Grot

Research output: Chapter in Book/Report/Conference proceedingConference contribution


To provide low latency and high throughput guarantees, most large key-value stores keep the data in the memory of many servers. Despite the natural parallelism across lookups, the load imbalance, introduced by heavy skew in the popularity distribution of keys, limits performance. To avoid violating tail latency service-level objectives, systems tend to keep server utilization low and organize the data in micro-shards, which provides units of migration and replication for the purpose of load balancing. These techniques reduce the skew, but incur additional monitoring, data replication and consistency maintenance overheads. In this work, we introduce RackOut, a memory pooling technique that leverages the one-sided remote read primitive of emerging rack-scale systems to mitigate load imbalance while respecting service-level objectives. In RackOut, the data is aggregated at rack-scale granularity, with all of the participating servers in the rack jointly servicing all of the rack’s micro-shards. We develop a queuing model to evaluate the impact of RackOut at the datacenter scale. In addition, we implement a RackOut proof-of-concept key-value store, evaluate it on two experimental platforms based on RDMA and Scale-Out NUMA, and use these results to validate the model. Our results show that RackOut can increase throughput up to 6× for RDMA and 8.6× for Scale-Out NUMA compared to a scale-out deployment, while respecting tight tail latency service-level objectives.
Original languageEnglish
Title of host publicationSoCC '16 Proceedings of the Seventh ACM Symposium on Cloud Computing
Number of pages14
ISBN (Print)978-1-4503-4525-5
Publication statusPublished - 5 Oct 2016
EventSeventh ACM Symposium on Cloud Computing - Santa Clara, United States
Duration: 5 Oct 20167 Oct 2016


ConferenceSeventh ACM Symposium on Cloud Computing
Abbreviated titleSoCC '16
Country/TerritoryUnited States
CitySanta Clara
Internet address


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