Complex embedded systems today commonly involve a mix of real-time and best-effort applications. The recent emergence of small low-cost commodity UMA multicore processors raises the possibility of running both kinds of applications on a single machine, with virtualization ensuring that the best-effort applications cannot steal CPU cycles from the real-time applications. Nevertheless, memory contention can introduce other sources of delay, that can lead to missed deadlines. In this research report, we present a combined offline/online memory bandwidth monitoring approach. Our approach estimates and limits the impact of the memory contention incurred by the best-effort applications on the execution time of the real-time application. We show that our approach is compatible with the hardware counters provided by current small commodity multicore processors. Using our approach, the system designer can limit the overhead on the real-time application to under 5% of its expected execution time, while still enabling progress of the best-effort applications.