Managing Tail Latency in Datacenter-Scale File Systems Under Production Constraints

Distributed file systems often exhibit high tail latencies, especially in large-scale datacenters and in the presence of competing (and possibly higher priority) workloads. This paper introduces techniques for managing tail latencies in these systems, while addressing the practical challenges inherent in production datacenters (e.g., hardware heterogeneity, interference from other workloads, the need to maximize simplicity and maintainability). We implement our techniques in a scalable distributed file system (an extension of HDFS) used in production at Microsoft. Our evaluation uses 70k servers in 3 datacenters, and shows that our techniques reduce tail latency significantly for production workloads.