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We present a non-analytic approach to self-assessment for Autonomic Computing. Our approach leverages utility functions, at the level of an autonomic application, or even a single task or feature being exercised within that application. This paper describes the fundamental steps of our approach: instrumentation of the application; collection of exhaustive samples of runtime data about relevant quality attributes of the application, as well as characteristics of its runtime environment; elicitation of a utility function through statistical correlation over the collected data points; and embedding of code corresponding to the equation of the elicited utility function within the runtime of the application, which enables online evaluation of utility values. To illustrate our elicitation method, as well as our framework for instrumentation, monitoring, and utility function embedding/evaluation, we discuss our experience with two different …