Efficient Anomaly Detection for Batch Systems Using Machine Learning
Explore a lightning talk session focusing on using Collectd metrics and job data in HTCondor batch systems for anomaly detection. Challenges with raw historical data are addressed through data collection, manipulation, and application of anomaly detection techniques using ML. Various algorithms such
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Hardware Monitoring Evolution at CERN: Lemon vs. Collectd
Comparison between Lemon and Collectd for hardware monitoring at CERN, detailing the differences, necessary changes, choices made, status update, current issues, and proposed fixes in transitioning from Lemon to Collectd. Collectd's advantages, drawbacks, and the adaptation process are discussed, hi
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