Understanding Online Failure Prediction in Linux Through Complementary Multi-View Explainability
Accurate Online Failure Prediction (OFP) has been shown to be feasible in Operating Systems (OSs) settings, but prediction alone is not sufficient for practical adoption. Without diagnostic insight, operators have limited basis to trust alerts or decide how to respond. Moreover, even when predictive accuracy is high, it is often unclear whether models are capturing meaningful failure processes or merely exploiting workload-specific noise and incidental correlations in telemetry. This paper reports a practical experience building and evaluating an explainable OFP pipeline for Linux OSs. We combine consensus-based feature selection for detection with temporal onset analysis, subsystemlevel ...
| Authors | Diogo Dória, João R. Campos |
|---|---|
| Primary category | cs.SE |
| Published | 1 August 2026 |
| Last updated at source | 1 August 2026 |
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