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Mining Web Logs to Debug Distant Connectivity Problems

Emre Kıcıman, Dave Maltz, John Platt, and Moises Goldszmidt


Content providers base their business on their ability to receive andfl answer requests from clients distributed across the Internet. Sincefl disruptions in the flow of these requests directly translate into lostfl revenue, there is tremendous incentive to diagnose why some requestsfl fail and prod the responsible parties into corrective action.fl However, a content provider has only limited visibility into the statefl of the Internet outside its domain. Instead, it must mine failure diagnosesfl from available information sources to infer what is goingfl wrong and who is responsible.fl Our ultimate goal is to help Internet content providers resolve reliabilityfl problems in the wide-area network that are affecting enduserfl perceived reliability. We describe two algorithms that representfl our first steps towards enabling content providers to extractfl actionable debugging information from content provider logs, andfl we present the results of applying the algorithms to a week’s worthfl of logs from a large content provider, during which time it handledfl over 1 billion requests originating from over 10 thousand ASes.


Publication typeProceedings
Published inACM SIGCOMM Workshop on Mining Network Data (MineNet-06)
PublisherAssociation for Computing Machinery, Inc.
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