Theoretical evaluation of performance, availability, and reliability of distributed algorithms is always based on models and metrics that make some simplifying assumptions. Such assumptions are needed in order to have simple abstractions for reasoning about algorithms. However, such assumptions often lead to models, metrics, and analyses that fail to capture important aspects of actual system behavior. Using realistic system models and metrics is important, since distributed algorithms and systems are often designed to optimize over such metrics.