Seer: Leveraging Big Data to Navigate the Complexity of Performance Debugging in Cloud Microservices
Authors: Yu Gan, Yanqi Zhang, Kelvin Hu, Dailun Cheng, Yuan He, Meghna Pancholi, Christina Delimitrou Venue: ASPLOS 2018 Seer presents a framework to diagnose and avoid QoS violations in real-time. The motivation, design, and experimental framework in this paper are some of the best and most through I have seen in my recent reading. The work begins by discussing the microservice design of cloud providers. Such frameworks have numerous layers of abstraction, are often written in multiple programming languages, and have complex (and changing) dependency graphs. A performance bug in one microservice can cause QoS in many others, and diagnosing the root cause can be difficult. The work then builds a complex data collection framework which uses RPC-level and perf counters. When perf counters aren't available, the system uses microbenchmarks to diagnose the bottleneck. This area is particularly complex, and the authors even note that their system is similar to Dapper and Zipkin wh...