At the Minnesota Supercomputing Institute we are exploring ways to provide the immediacy and flexibility of interactive computing within the batch-scheduled, tightly controlled world of traditional cluster supercomputing. As Jupyter Notebook has gained in popularity, the steps needed to use it within such an environment have proven to be a barrier to entry even as increasingly powerful Python tools have developed to take advantage of large computational resources. JupyterHub to the rescue! Except out of the box, it doesn't know anything about resource types, job submission, and so on. We developed BatchSpawner and friends as a general JupyterHub backend for batch-scheduled environments. In this talk I will walk through how we have deployed JupyterHub to provide a user-friendly gateway to interactive supercomputing.