For a system to be reliable, it must have one or more methods of dealing with failures. Distributed systems face both node failure and communication channel failure. Communication channels, in particular, may suffer failures at a very high rate. Different systems respond to task failure in different ways. The system may resume a failed task from the failure point (or a saved checkpoint shortly before the failure point), it may restart the task, or it may give up on the task and select a replacement task from the ready queue. These three responses to failure all change the distribution of task completion times. The distribution of completion times is important because it governs mean service time and queue length, and therefore quality of service and buffer size necessary to manage the risk of overflow. The changes to the distribution introduced by the failure response can even turn well behaved exponentially distributed times into powertail distributed times with infinite mean and variance. In this paper we examine the characteristics of distributions that result from restarting after each interrupt, with some discussion of Resume and Replace, for comparison. We provide analytic and simulation solutions.