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DTSTAMP:20260522T150117Z
LOCATION:D174
DTSTART;TZID=America/Chicago:20181116T113000
DTEND;TZID=America/Chicago:20181116T115000
UID:submissions.supercomputing.org_SC18_sess146_ws_ftxs117@linklings.com
SUMMARY:SaNSA - the Supercomputer and Node State Architecture
DESCRIPTION:Neil Agarwal (University of California, Berkeley) and Hugh Gre
 enberg, Sean Blanchard, and Nathan DeBardeleben (Los Alamos National Labor
 atory)\n\nIn this work, we present SaNSA, the Supercomputer and Node State
  Architecture, a software infrastructure for historical analysis and anoma
 ly detection. SaNSA consumes data from multiple sources including system l
 ogs, the resource manager, scheduler, and job logs. Furthermore, additiona
 l context such as scheduled maintenance events or dedicated application ru
 n times for specific science teams can be overlaid. We discuss how this co
 ntextual information allows for more nuanced analysis. SaNSA allows the us
 er to apply arbitrary attributes, for instance, positional information whe
 re nodes are located in a data center. We show how using this information 
 we identify anomalous behavior of one rack of a 1,500 node cluster. We exp
 lain the design of SaNSA and then test it on four open compute clusters at
  LANL. We ingest over 1.1 billion lines of system logs in our study of 190
  days in 2018. Using SaNSA, we perform a number of different anomaly detec
 tion methods and explain their findings in the context of a production sup
 ercomputing data center. For example, we report on instances of misconfigu
 red nodes which receive no scheduled jobs for a period of time as well as 
 examples of correlated rack failures which cause jobs to crash.\n\nTag: Re
 siliency, Scientific Computing\n\nRegistration Category: Workshop Reg Pass
 \n\n
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