Microsoft Technology Licensing, LLC

Julien Hoachuck

Qingwei Lin

Si Qin

Kamaljit S Bath

Bo Qiao

Rakesh Namineni

Jian Zhang

Yu Kang

Yingnong Dang

Mohit Verma

Namrata Jain

Jeffrey Ding He

Pooja Rani

Jimmy Wong

Methods and systems for detecting systemwide service issues by using anomaly localization. In an example, a method includes receiving time-series monitoring data for multiple services, the time-series monitoring data including multiple dimensions and an error metric; for the monitoring data from each service, evaluating scopes within the monitoring data based on an objective function for a time-series of the error metric to identify at least one anomalous scope, each scope including at least one dimension and a value for the dimension; based on evaluating the scopes, generating a ranked list of scopes for each service based on objective function scores for the scopes; correlating the ranked lists of scopes across the multiple services to identify a cross-service anomaly; and generating an alert for the services based on the cross-service anomaly, the alert indicating at least one scope as a potential root cause for the cross-service anomaly.

Detecting systemwide service issues by using anomaly localization

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San Francisco, CA, United States of America

Julien Hoachuck