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PREDICTIVE DIAGNOSIS OF SLA VIOLATIONS IN CLOUD SERVICES BY SEASONAL TRENDING AND FORECASTING WITH THREAD INTENSITY ANALYTICS

  • US 20140310714A1
  • Filed: 12/17/2013
  • Published: 10/16/2014
  • Est. Priority Date: 04/11/2013
  • Status: Active Grant
First Claim
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1. A computer-implemented method comprising:

  • obtaining a series of thread dump samples by generating a separate thread dump during each particular time interval in a series of time interval;

    based on the series of thread dump samples, automatically generating a set of stack segment classifications;

    for each particular thread represented in the series of thread dump samples, automatically selecting, from the set of stack segment classifications, a particular stack segment classification for the particular thread based at least in part on a number of invocations of a code block in the particular stack segment multiple by an execution time of the code block;

    determining a trend for each stack segment classification in the set of stack segment classifications, thereby generating a set of trends;

    determining a set of anomalies based at least in part on the set of trends; and

    generating output based at least in part on the set of anomalies;

    wherein said set of anomalies includes at least one of;

    a level spike, a level shift, a level drift, a variance change, a saturation, a stuck thread, a lingering thread, a deadlock condition, a congestion upstream, a congestion downstream, a congestion in resource pool, a convoy effect, an impedance mismatch, an outlying measurement, or a burst of outlying measurements.

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