Title:

Mining Web Server Logs to Debug Distant Connectivity Problems


Abstract:

Content providers on the Internet base their business on their ability
to   receive and answer  requests from  clients distributed across the
Internet. Since  disruptions in the   flow of these requests  directly
translate into lost revenue, there is tremendous incentive to diagnose
why some   requests   fail and  prod   the responsible   parties  into
corrective  action. However,   a  content provider  has  only  limited
visibility into the state of the Internet outside its domain. Instead,
it must  mine failure diagnoses  from available information sources to
infer what is going wrong and who is responsible.

Our   ultimate  goal is  to  help  Internet  content providers resolve
reliability  problems  in  the wide-area network    that are affecting
end-user perceived  reliability. We  describe several algorithms  that
represent our first steps  towards    enabling content providers    to
extract actionable  debugging information from  content provider logs,
and we  present the  results  of applying the  algorithms  to a week's
worth of logs  from  a large content   provider, during which  time it
handled over 1 billion  requests   originating from over  10  thousand
ASes.


Bio:

Emre Kiciman is  a  researcher   in  the Cybersecurity   and   Systems
Management group   at   Microsoft  Research.  His  interests   lie  in
large-scale systems  management and the  use of aggressive monitoring,
machine  learning  and data  analysis    techniques to  improve  their
reliability and  administration.   He received his  Ph.D.  in Computer
Science from Stanford in 2005.