Recognizing and solving a distributed application's performance problems can require information about the application's structure, the application-level services offered by each of its processes, and the resource demands and response times of each of these services. The Application Response Measurement package (ARM) Version 2.0 offers a de facto standard instrumentation paradigm for distributed applications that enables the monitoring of services and their relationships. The data that can be captured is adequate for deducing the structure of distributed applications and for gathering response time measures. However for most platforms it is not possible to measure a service's resource demands directly. This last step is necessary for sizing studies and the development of predictive performance models. In this paper we present the results of experiments that illustrate the conditions under which common statistical techniques, instead of direct measurement, can be used to accurately correlate the use of application level services with resource demand information. Both simulation and the measurement of a CORBA application are used to assess the accuracy of the techniques and the relative importance of various experimental factors. The results of the experiments are used to provide a set of requirements for ARM monitoring infrastructures and strategies for ARM instrumentation plans.

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