The introduction of stochastic process algebra (SPA) has had a profound impact on the field of performance modelling. Hillston’s PEPA has been at the forefront of this development . There are a number of reasons why the use of stochastic process algebra is attractive to the stochastic modeller. The parsimonious set of operators creates an almost programming-like simplicity to model specification, meaning complex behaviours can be modelled in a concise and relatively understandable way. The models, although complex, can be analysed to show that they are deadlock free and that intended behaviours are reachable in its evolution (unlike simulation). The formal underpinning of the algebra means that models can be derived from other formal (or semi-formal) specifications in an automatic or semi-automatic way. This formality also means that the process algebra model can itself be manipulated into provably equivalent alternative forms that are more readily solved by numerical analysis. In the case of PEPA, the specification and analysis is also supported by a powerful set of modelling tools [2, 3, 4, 5, 6].