I've used probability distributions to generate the incoming events, but the simulation is always deterministic. In the netflix case for example, I would generate 40% of users that would be playing things around 8am with a normal distribution, and 40% that would play around 8pm, and then 20% that play at random times of the day, etc...

I also played with pymc3 where you can just place plain python inside your probabilistic model and MCMC the heck out of it. It's slow but you can use some real world input and see what distributions arise at each point of the graph.