University of Cambridge > Talks.cam > Computer Laboratory Opera Group Seminars > Run-time behavioural models for error detection, fault diagnosis, and self-recovery

Run-time behavioural models for error detection, fault diagnosis, and self-recovery

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Existing systems-management tools are essentially a plumbing infrastructure: they collect data and present it to administrators, typically with an API to allow administrators to code scripts for automated analysis. Plumbing is the easy part; analysis is the hard part; this talk will describe our research on creating effective run-time behavioural models of log and metric data, together with work on how to then use that data for fault localisation and diagnosis, leading to self-recovering systems. Given the large costs of running enterprise information systems ($100 billion annually in the US alone; US Bureau of Labor Statistics), our research is expected to result in very significant cost reductions.

This talk is part of the Computer Laboratory Opera Group Seminars series.

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