Mining Web Logs to Debug Distant Connectivity Problems

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

Abstract

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.

Details

Publication typeProceedings
Published inACM SIGCOMM Workshop on Mining Network Data (MineNet-06)
PublisherAssociation for Computing Machinery, Inc.
> Publications > Mining Web Logs to Debug Distant Connectivity Problems