In this paper we consider a model for scheduling under uncertainty. In this model, we combine the main characteristics of online and stochastic scheduling in a simple and natural way. Jobs arrive in an online manner and as soon as a job becomes known, the scheduler only learns about the probability distribution of the processing time and not the actual processing time. This model is called the stochastic online scheduling (sos) model. Both online scheduling and stochastic scheduling are special cases of this model. In this paper, we survey the results for the sos model.