AI-Powered Database Anomaly Detection Service: Feature Analysis, Algorithm Selection, and Real-Time Monitoring

The article details Meituan's database platform team's end‑to‑end design of an AI‑driven anomaly detection service, covering feature analysis of time‑series patterns, algorithm selection (MAD, boxplot, EVT), model training, real‑time detection with Flink, operational metrics, and future enhancements.

AI AlgorithmsBoxplotDatabase Anomaly Detection

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AI-Powered Database Anomaly Detection Service: Feature Analysis, Algorithm Selection, and Real-Time Monitoring

vivo Internet Technology

Jan 13, 2021 · Big Data

Statistical Monitoring Using Normal Distribution and Boxplot: Theory, Implementation, and API Design

The article explains the origin of the normal distribution, the central limit theorem, and how boxplots identify anomalies, then describes a Java‑based API that partitions data into five median‑centered levels using same‑period and year‑over‑year ratios to automatically detect and classify abnormal trends in daily metrics.

Big DataBoxplotanomaly detection

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Statistical Monitoring Using Normal Distribution and Boxplot: Theory, Implementation, and API Design