AIOps at Meituan: Architecture, Design, and Practice of the Horae Time‑Series Anomaly Detection System

This article presents Meituan's AIOps exploration, focusing on the design and implementation of the Horae time‑series anomaly detection platform, covering background, technical roadmap, fault‑discovery workflow, time‑series classification, feature engineering, model training, real‑time detection, and future directions.

HoraeMeituanaiops

0 likes · 31 min read

AIOps at Meituan: Architecture, Design, and Practice of the Horae Time‑Series Anomaly Detection System

Meituan Technology Team

Oct 15, 2020 · Artificial Intelligence

AIOps at Meituan: Architecture and Practice of Time‑Series Anomaly Detection (Part 1)

Meituan’s AIOps initiative replaces manual rule‑based monitoring with the Horae platform, which automatically classifies time‑series metrics, applies CNN and XGBoost models to detect periodic anomalies, achieves over 90 % precision in production, and paves the way for broader metric types, forecasting, and advanced fault‑localization.

HoraeMachine LearningMeituan

0 likes · 33 min read

AIOps at Meituan: Architecture and Practice of Time‑Series Anomaly Detection (Part 1)

AIOps at Meituan: Architecture, Design, and Practice of the Horae Time‑Series Anomaly Detection System

AIOps at Meituan: Architecture and Practice of Time‑Series Anomaly Detection (Part 1)

AIOps at Meituan: Architecture and Practice of Time‑Series Anomaly Detection (Part 1)