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This paper presents Swing, a closed-loop, network-responsive traffic generator that accurately captures the packet interactions of a range of applications using a simple structural model. Starting from observed traffic at a single point in the network, Swing automatically extracts distributions for user, application, and network behavior. It then generates live traffic corresponding to the underlying models in a network emulation environment running commodity network protocol stacks. We find that the generated traffic is statistically similar to the original traffic. Furthermore, to the best of our knowledge, we are the first to reproduce burstiness in traffic across a range of time-scales using a model applicable to a variety of network settings. An initial sensitivity analysis reveals the importance of our individual model parameters to accurately reproduce such burstiness. Finally, we explore Swing's ability to vary user characteristics, application properties, and wide-area network conditions to project traffic characteristics into alternate scenarios.