PerfDB: A Data Management System for Fine-Grained Performance Anomaly Detection
PerfDB: A Data Management System for Fine-Grained Performance Anomaly Detection
Joshua Kimball,Rodrigo Alves Lima,Yasuhiko Kanemasa,C. Pu
2020 · DOI: 10.1109/CIC50333.2020.00021
International Conference on Communications in Computing · 0 Citations
Abstract
In this work, we present our performance data management system, PerfDB, that we use to study fine-grained performance anomalies like Millibottlenecks. We use it to present the first experimental evidence of a phenomenon we call, “Localized Latency Requests.” These are performance bugs that are part of the long-tail of system latency. We also provide a population study of Very Long Response Time (VLRT) requests, a separate performance anomaly belonging to the latency long tail, being inducing by millibottlenecks through queueing effects.
