Structured Comparative Analysis of Systems Logs to Diagnose Performance Problems

By Karthik Nagaraj, Charles Edwin Killian Jr, Jennifer Neville. Symposium on Networked Systems Design and Implementation, 2012

314 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/988b44eee2fac0bfdbdacb2ebd23e3caff4cac00

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Citations in the corpus

• A Survey on Automated Log Analysis for Reliability Engineering (2020, background): “articularly, these research studies mainly focus on the large-scale software systems where failure diagnosis is burdensome, including the software applications [148, 150], general distributed systems [16, 51, 68, 98, 115], storage systems [69], microservice systems [163, 164], big data systems such ”
• Spell: Streaming Parsing of System Event Logs (2016, methodology): “Researchers have also used system logs to discover and diagnose performance problems [7].”
• Tools and Benchmarks for Automated Log Parsing (2018, methodology): “Typical applications include anomaly detection [12], [18], [23], problem diagnosis [4], [5], program verification [55], [56], performance modeling [3], etc.”
• DeepLog: Anomaly Detection and Diagnosis from System Logs through Deep Learning (2017, methodology): “Besides workflows, other systems that perform anomaly diagnosis using system logs include DISTALYZER [26] that diagnoses system performance issues by comparing a problematic log against a normal one, LogCluster [19] which clusters and organizes historical logs to help future problem identification,…”