µTune: Auto-Tuned Threading for OLDI Microservices

Modern On-Line Data Intensive (OLDI) applications have evolved from monolithic systems to instead comprise numerous, distributed microservices interacting via Remote Procedure Calls (RPCs). Microservices face sub-millisecond (sub-ms) RPC latency goals, much tighter than their monolithic counterparts that must meet ≥ 100 ms latency targets. Sub-ms-scale threading and concurrency design effects that were once insignificant for such monolithic services can now come to dominate in the sub-ms-scale microservice regime. We investigate how threading design critically impacts microservice tail latency by developing a taxonomy of threading models--a structured understanding of the implications of how microservices manage concurrency and interact with RPC interfaces under wide-ranging loads. We develop µTune, a system that has two features: (1) a novel framework that abstracts threading model implementation from application code, and (2) an automatic load adaptation system that curtails microservice tail latency by exploiting inherent latency trade-offs revealed in our taxonomy to transition among threading models. We study µTune in the context of four OLDI applications to demonstrate up to 1.9× tail latency improvement over static threading choices and state-of-the-art adaptation techniques.