Your transactions have to flow through many things as they make their way though your computing world. If you can meter, even indirectly, one of these things in the transaction path you can create your own transaction meter.
Most applications have no throughput metering at all or only tell you their throughput on some useless time scale like daily or weekly. It is important to know the average throughput of work at the same time you are sampling the system performance meters. All you have to do is find one thing you can easily meter that has a stable relationship with the amount of work the system is doing and, Voila, you know the transaction rate.
For example, suppose your system only reported the throughput as a daily value, and you noticed a stable relationship between the daily transaction rate and the X meter over several days, like so:
Here it is clear that for every transaction, the X meter increments by 2.3 ≈ 23,045 /10,000. The relationship doesn’t have to be perfect because the metering is rarely perfectly aligned, and there is always noise in any data you collect. You don’t have to understand the details of the relationship just as you don’t have to understand daffodil biology to know that when they are blooming in your yard it is most likely spring.
Once you’ve found that relationship, keep metering and keep checking to build confidence in this new transaction meter. Look at resource utilization over smaller time periods and check if a change in the transaction rate shows a similar movement in the utilizations. When you’ve collected and analyzed enough data to be confident in the new X meter you can then study the X meter over any interval you like, divide its value by 2.3, and get the transactions per that interval.
For other useful performance insights, and the occasional funny story, please check out my book: The Every Computer Performance Book
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