JupyterLab Notebooks, especially with beakerX extensions provide a complete environment for data scientists to develop their models, but there are Infrastructure challenges that they must first surmount:
In this talk we will discuss a potential solution to these challenges with platform to provision Jupyter notebooks in a self-service, multi-tenant environment. By using Apache Mesos/DC/OS as the underlying cluster manager, we are able to keep the overall system very flexible (e.g., allowing simple provision of a range of Big Data Frameworks such as Apache Spark, Flink, or Cassandra) but still make very efficient use of the underlying infrastructure.
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