Vmware, Inc.

Karen Aghajanyan

Ashot Nshan Harutyunyan

Arnak Poghosyan

Naira Movses Grigoryan

Tigran Bunarjyan

Vahan Tadevosyan

Artur Grigoryan

Tigran Avagimyants

Automated computer-implemented methods and systems for discovering clusters of alerts triggered by abnormal events occurring with objects in a data center are described. In one aspect, alerts with start times in a sliding run-time window are retrieved from an alerts database. Each alert corresponds to a run-time event occurring with an object of the data center. Clusters of alerts in the sliding run-time window are detected based on the start times of the alerts and topological proximity of the objects. High priority alerts in the clusters of alerts are determined based on alert types. The events associated with discovered clusters of alerts and high priority alerts are displayed in a graphical user interface ('GUI'). Time evolution clustering of alerts and coverage evolution of alerts are over time based on the start times of the alerts and topological proximity of objects exhibiting abnormal behavior in the data center.

Methods and systems for discovering incidents through clustering of alert occurring in a data center

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Yerevan, Armenia

Karen Aghajanyan