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DTSTAMP:20181221T160727Z
LOCATION:D170
DTSTART;TZID=America/Chicago:20181112T105000
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UID:submissions.supercomputing.org_SC18_sess169_ws_daac111@linklings.com
SUMMARY:Tivan: A Scalable Data Collection and Analytics Cluster
DESCRIPTION:Workshop\nData Analytics, HPC Center Planning and Operations, 
 Heterogeneous Systems, Scientific Computing, State of the Practice, Worksh
 op Reg Pass, Datacenter, monitoring\n\nTivan: A Scalable Data Collection a
 nd Analytics Cluster\n\nGreenberg, Debardeleben\n\nLog analysis is a criti
 cal part of every data center to diagnose system issues and determine perf
 ormance problems. As data centers increase in size, the need for a dedicat
 ed, scalable log analysis system becomes necessary. At Los Alamos National
  Laboratory, our clusters and support infrastructure are currently produci
 ng over seventy million logs a day. The large amount of log data makes it 
 extremely difficult for system administrators, application developers, and
  researchers to find relevant events and perform detailed analysis. In ord
 er to manage this data and to run scalable analytics, we designed and depl
 oyed a data analytics cluster based on open source software. In this paper
 , we describe the design and trade-offs, the current uses of this system, 
 and analytics utilizing the system that are aiding in the discovery of sys
 tem issues. We have found that this data analytics cluster has helped us t
 o proactively identify cluster issues more efficiently.
URL:https://sc18.supercomputing.org/presentation/?id=ws_daac111&sess=sess1
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