Using Magpie for Request Extraction and Workload Modelling

By Paul Barham, Austin Donnelly, Rebecca Isaacs, R. Mortier. USENIX Symposium on Operating Systems Design and Implementation, 2004

687 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/9894b3f9755705571cbb23be41864282e5dfa9a9

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Citations in the corpus

Structured Comparative Analysis of Systems Logs to Diagnose Performance Problems (2012, methodology): “Magpie [3] and Pinpoint [5] model request paths in the system to cluster performance behaviors, and identify root causes of failures and anomalous performance.”
FIRM: An Intelligent Fine-Grained Resource Management Framework for SLO-Oriented Microservices (2020, methodology): “Tracing requires either application-level instrumentation [18,32,57,95,111–115] or middleware/OS-level instrumentation [10,16,63,109] (e.”
Towards highly reliable enterprise network services via inference of multi-level dependencies (2007, background): “Magpie [3], FUSE [5] and Pinpoint [4], instrument middleware on every host to track requests as they flow through the system.”
AppInsight: Mobile App Performance Monitoring in the Wild (2012, unknown): “Magpie [4] is a system for monitoring and modeling server workload.”
Carat: collaborative energy diagnosis for mobile devices (2013, background): “Some notable performance debugging work includes historybased analysis in datacenters [5], resource accounting [4], and blackbox debugging [2] Pinpoint [6] and Magpie [4] track communication dependencies with the aim of isolating the root cause of misbehavior; they require instrumentation of th”
X-Trace: A Pervasive Network Tracing Framework (2007, background): “Magpie [ 5 ] is a toolchain that works with events generated by operating system, middleware, and application instrumentation, correlates them, and produces representations of paths through a system by inferring causal relations from a total ordering of events.”
Making Sense of Performance in Data Analytics Frameworks (2015, background): “Blocked time analysis lacks the sophistication and generality of general purpose distributed systems performance analysis tools (e.g., [5] [15] ), and unlike black-box approaches, requires adding instrumentation within the application.”
Tools and Benchmarks for Automated Log Parsing (2018, background): “Typical examples include user behaviour analysis (e.g., Twitter [1]), API proﬁling, logs-based metrics couting (e.g., Google Cloud [32]), and workload modeling (e.g., Microsoft [33]).”
Capturing, indexing, clustering, and retrieving system history (2005, background): “At the opposite extreme of this knowledge-lean approach, Magpie characterizes transaction resource footprints in fine detail but requires that application logic be meticulously encoded in “event schema” [2].”