..unless you’re dealing with baseball. When dealing with systems, many of us think “Average” is a measure of “Typical” or “Normal“. Many systems people will also use averages to look for “Abnormal“. However, average (or mean) doesn’t represent either “normal” or “abnormal” very well..
Many of us have dealt with making changes in production environments, possibly against hundreds or thousands of systems and, we’d like to know how the change impacted performance. It was with this in mind that I eagerly read through the paper describing WSMeter.
Just for fun, how many combinations of months are there where Friday falls on the 13th? This one-liner will print out a table of month combinations along with the years for a given range.
While working at RIM, I had the privilege of working with some brilliant engineers. During that time I developed a few of the techniques that I’ll be describing; the EPD (Event-Pair-Difference) graph described in my previous post and the EPL (Event-Pair-Latency) Dotplot are a few of them.
System failures are often not black and white, but shades of grey (gray?).. Detecting and alerting on “performance-challenged” system components are a lot more difficult than detecting black or white (catastrophic failures). The metrics used are usually of the “time vs. latency” or “time vs. event count” variety, often aggregated and, often by using averages. …