KPI Anomaly

KPI anomaly detection focuses on identifying unusual patterns in key performance indicators (KPIs), crucial time-series data for monitoring system health and performance. Research emphasizes developing robust and efficient algorithms, often employing machine learning techniques such as deep learning models and ensemble methods, to accurately detect anomalies while minimizing false positives and adapting to evolving data patterns. This field is vital for improving the reliability and stability of complex systems across various domains, enabling proactive issue resolution and optimizing resource allocation. Current efforts also include developing methods for root cause analysis to pinpoint the origin of detected anomalies.