Correlating Instrumentation Data to System States: A Building Block for Automated Diagnosis and Control

By Ira Cohen, Jeffrey S. Chase, Moisés Goldszmidt, Terence Kelly, Julie Symons. USENIX Symposium on Operating Systems Design and Implementation, 2004

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Understanding and detecting real-world performance bugs (2012, background): “Many previous works tried to isolate bottlenecks in (semi-) blackbox systems [1], correlate system metrics with performance behaviors [8, 48], avoid performance problems at runtime [52], and diagnose problems through logs [59].”
An analytical model for multi-tier internet services and its applications (2005, methodology): “A recent paper [Cohen et al. 2004] uses a probabilistic modeling approach called Tree-Augmented Bayesian Networks (TANs) to identify combinations of system-level metrics and threshold values that correlate with high-level performance states - compliance with service-level agreements for average resp”
Structured Comparative Analysis of Systems Logs to Diagnose Performance Problems (2012, methodology): “Although these specific applications of machine learning (including [1,3,5,6]) can leverage path structures, D ISTALYZER”