A set of algorithms for detecting a renewal power-tail behavior which often
relates to chaotic system activities in one or more computer system
resources of a distributed computing environment, i.e., an enterprise.
Analysis and/or prediction software receives a set of metric data points
from agent software on one or more computer systems. The analysis and/or
prediction software performs three analytic tests relating to distinctive
properties of power-tail distributions: a first test to determine whether
the set of data points exhibits large deviations from the mean, a second
test to determine whether the set of data points exhibits a high variance,
and a third test to determine whether the set of the largest data points
exhibits properties consistent with large values in a tail portion of a
power-tail distribution. The tests can be performed in any order, and in
other embodiments, fewer than three can be performed. Each test has two
possible results: successful if the test indicates a likelihood of
power-tail behavior, or unsuccessful if it indicates that power-tail
behavior is unlikely. The results of the three tests are combined to
determine the overall likelihood of a power-tail distribution. If all
three tests are successful, then power-tail behavior is likely. If all
three tests are unsuccessful, then power-tail behavior is unlikely. If the
results are mixed, then typically more data or analysis is needed. The
results are used for modeling and/or altering the configuration of the
enterprise.