Unsupervised Anomaly Detection via Variational Auto-Encoder for Seasonal KPIs in Web Applications

    Haowen Xu
    Haowen Xu
    Wenxiao Chen
    Wenxiao Chen
    Nengwen Zhao
    Nengwen Zhao
    Zeyan Li
    Zeyan Li
    Jiahao Bu
    Jiahao Bu
    Zhaogang Wang
    Zhaogang Wang

    WWW '18: The Web Conference 2018 Lyon France April, 2018, pp. 187-196, 2018.

    Cited by: 54|Bibtex|Views36|Links
    EI

    Abstract:

    To ensure undisrupted business, large Internet companies need to closely monitor various KPIs (e.g., Page Views, number of online users, and number of orders) of its Web applications, to accurately detect anomalies and trigger timely troubleshooting/mitigation. However, anomaly detection for these seasonal KPIs with various patterns and d...More

    Code:

    Data:

    Your rating :
    0

     

    Tags
    Comments