Abstract. The performance of multi-tier systems is known to be significantly degraded by workloads that place bursty service demands on system resources. Burstiness can cause queueing delays, oversubscribe limited threading resources, and even cause dynamic bottleneck switches between resources. Thus, there is need for a methodology to create benchmarks with controlled burstiness and bottleneck switches to evaluate their impact on system performance. We tackle this problem using a model-based technique for the automatic and controlled generation of bursty benchmarks. Markov models are constructed in an automated manner to model the distribution of service demands placed by sessions of a given system on various system resources. The models are then used to derive session submission policies that result in user-specified levels of service demand burstiness for resources at the different tiers in a system. Our approach can also predict under what conditions these policies can create dy...