DODAS enables the execution of user analysis code both in batch mode and interactively via the Jupyter interface. DODAS is highly customizable and offers several building blocks that can be combined together in order to create the best service composition for a given use case. The currently available blocks allow to combine Jupyter and HTCondor as well as Jupyter and Spark or simply a jupyter interface. In addition, they allow the management of data via caches to optimize the processing of remote data. This can be done either via XCache or MinIO S3 object storage capabilities. DODAS is based on docker containers and the related orchestration relies on Kubernetes that enables the possibility to compose the building blocks via a web-based user interface thanks to Kubeapps.
In this presentation we will explain the DODAS fundamentals and we will provide a user oriented demo.