It is a common problem that performance testing is often carried out on smaller scale test environments but project managers want to know that the system will scale and response times will not be degraded. Therefore can the performance test results be extrapolated? My view on extrapolation is it is a great technique when used properly but it does not guarantee that the system you tested will work well on the full sized production environment. The two main reasons for failure are
1) You have made a mistake in the creation of your model. These mistakes could be simply just a poorly built model or a bad assumption. However, with plenty of time and expertise you can overcome some of these limitations by building a good model.
2) There are “soft” bottlenecks in the system that are only detected at high load. A common example might be a piece of software may be limited to a certain number of threads that once all used, limit scalability. Some of these “soft” limits might be know by developers before hand and can be investigated with the model and the test environment but it the unknown unknowns that will be the problem on go live day
However, this does not mean that extrapolation is bad or should be avoided. Where as it cannot guarantee that the system will work in production is can be used to show that the system will fail and as we all know avoiding a costly failure is often worth the effort. Using modelling techniques you can estimate the needed hardware configuration for the production system which can be compared to what is expected to be deployed and if the deployed hardware is undersized you have a made a friend with the project manager.