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Richard Park

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Top Stories by Richard Park

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 tapped into the Big Data "explosion" to highlight the benefits of building systems that use algorithms and data to make decisions and evolve over time. One recent article on machine learning on the O'Reilly Radar blog that caught my attention made a connection between web operations and medi... (more)

Losing Sleep Over Monitoring Complex Distributed Java Apps?

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 ... (more)