This paper considers self-adaptive (mu/mu_I,lambda)-evolution strategies on the noisy sharp ridge. The evolution strategy (ES) is treated as a dynamical system using the so-called evolution equations to model the ES's behavior. The approach requires the determination of the one-generational expected changes of the state variables - the progress measures. For the analysis, the stationary state behavior of the ES on the sharp ridge is considered. Contrary to the usual perception of noise, it is shown that noise has a positive influence on the performance. An explanation for this astonishing behavior is given and conditions for the usefulness of noise in other fitness landscapes are discussed.