Interactive analysis notebooks on DESY batch resources

Batch scheduling systems are usually designed to maximise fair resource utilisation and efficiency, but are less well designed for demanding interactive processing, which requires fast access to resources while low upstart latency is only of secondary significance for high throughput of high performance computing scheduling systems. The computing clusters at DESY are intended as batch systems for end users to run massive analysis and simulation jobs enabling fast turnaround systems, in particular when processing is expected to feed back to operation of instruments in near real-time. The continuously increasing popularity of Jupyter Notebooks for interactive and online processing made an integration of this technology into the DESY batch systems indispensable. We present here our approach to utilise the HTCondor and SLURM backends to integrate Jupyter Notebook servers and the techniques involved to provide fast access. The chosen approach offers a smooth user experience allowing users to customize resource allocation tailored to their computational requirements. In addition, we outline the differences between the HPC and the HTC implementations and give an overview of the experience of running Jupyter Notebook services