Chapter 9. Queueing Theory for the Oracle Practitioner

Professionals can argue forever about how best to improve system performance unless there’s a way to prove who’s right. One way to validate performance improvement conjectures is by trial and error. The problem with trial-and-error performance optimization is that, on average, it’s hugely expensive. It costs so much money and time to try each scenario that, frequently, the number of scenarios that a company can afford to test is very small. Often, a company runs out of time or money before finding a satisfactory solution.

Trial and error has hope of being efficient only if some kind of intelligence guides the process of choosing which trial to try next. Such choices are usually based upon some combination of experience, intuition, and luck. However, experience, intuition, and luck are what drive those endless debates:

Analyst: We upgraded to faster CPUs at my former client, and everything became 50% faster overnight. We should upgrade CPUs here immediately, and just cut out the performance problem at its knees.

Other analyst: Well, I think that’s a waste of time and money. The last seven projects that I’ve seen upgrade to faster CPUs regretted the investment, because the upgrade didn’t produce any real impact. One of my recent clients upgraded to faster CPUs, and parts of the application actually got slower.

So, who’s right? It is certainly possible that each of the phenomena described here did in fact happen the way the teller ...

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