专利名称：Large-scale distributed correlation发明人：Edward A. Sykes申请号：US14952313申请日：20151125公开号：US10291463B2公开日：20190514
专利附图：
摘要：Disclosed herein are system, method, and computer program product
embodiments for performing distributed correlation to determine a probable cause for aperformance problem detected in an application. An embodiment operates by triggeringan alert for a performance metric of an application executing on a local-level node. The
alert may be sent to a higher-level node. Upon receiving the alert, the higher-level nodemay send a distributed correlation request, used to determine a root cause of the alert,to the lower-level node. Upon receiving the distributed correlation request, the lower-level node may produce and send a correlation result to the higher-level node. Uponreceiving the correlation result, the higher-level node may select the probable cause oftriggering the alert based on the correlation result. The probable cause may then bepresented to the user.
申请人：Riverbed Technology, Inc.
地址：San Francisco CA US
国籍：US
代理机构：Park, Vaughan, Fleming & Dowler LLP
代理人：Laxman Sahasrabuddhe
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