Enterprise networks with speeds up to 100 gigabits per second are now moving into wide-scale deployment. However, these high-speed links are a challenge to monitor and control. Fortunately, the parallel emergence of software-defined networking (SDN) protocols makes it possible to consider not only dynamically reconfiguring the network, but also transparently managing individual connections. An ability to make these decisions in realtime would permit more efficient use of available bandwidth especially high-cost links. In this talk we present the results of experiments in realtime traffic managment on the Stanford University network. An illustrative example test case is the management of "elephant flows". This term is used to describe the large file transfers and streaming sensor data often seen on research networks. In an elephant flow, the connection typically starts out with small exchanges for authentication and resource allocation, then switches into a phase of high-volume data transfer, ramping down at the end with confirmations and teardown. The goal of the system is to identify the changing characteristics of the flow and move it to a link appropriate to its size. We observe that the fields and metrics in argus flow status records which are emitted periodically during connections contain the fundamental data necessary to make such bandwidth-based decisions. The decisions can then be turned into dynamically-issued commands to an OpenFlow controller. The presentation will describe the experimental setup; the challenges of flow collection at 100G; and report on the effectiveness of dynamic flow management. Bandwidth management for individual connections is not the only kind of realtime intervention which could be envisioned as SDN provides mechanisms applicable to a variety of tasks.The presentation concludes with a look at other opportunities drawn from traditional traffic engineering and network security.