Statistical Techniques for Online Anomaly Detection in Data Centers

[摘要] Online anomaly detection is an important step in data center management, requiring light-weight techniques that provide sufficient accuracy for subsequent diagnosis and management actions. This paper presents statistical techniques based on the Tukey and Relative Entropy statistics, and applies them to data collected from a production environment and to data captured from a testbed for multi-tier web applications running on server class machines. The proposed techniques are lightweight and improve over standard Gaussian assumptions in terms of performance.

[发布机构] HP Development Company

[学科分类] 计算机科学（综合）

[关键词] Anomaly Detection;Data Center Management;Statistics;Algorithms