When IT people think about application performance monitoring, they're
usually thinking about which metrics they should monitor. Some examples of
resource metrics may include CPU utilization, disk queue length, and thread
pool size. Examples of performance metrics may be application response time,
responses per interval of time, and concurrent invocations of an application.
"Modeling" is probably not the first term that comes to mind when considering
application performance monitoring. But, in fact, "modeling" is exactly what
a "domain expert" does when he decides how application components are related
with one another, and which metrics matter in gauging application
performance.
The problem for IT organizations is to extract this type of "institutional
knowledge" from a handful of experts to make it accessible and relevant to
more people in IT Operations and Applic... (more)
Machine learning and IT analytics can be just as beneficial to IT operations
as it is for monitoring vital signs of premature babies to identify danger
signs too subtle or abnormal to be detected by a human. But an enterprise
must be willing to implement monitoring and instrumentation that gathers data
and incorporates business activity across organizational silos in order to
get meaningful results from machine learning.
Machine learning is a topic that has gone from obscure niche to mainstream
visibility over the last few years. High profile software companies like
Splunk have ... (more)