Sequencing projects, like the Aqua Genome project, generate vast amounts of data which is processed through dif- ferent work ows composed of several steps linked together. Currently, such workflows are often run manually on large servers. With the increasing amount of raw data that approach is no longer feasible. The successful imple- mentation of the project's goals requires 2-3 orders of magnitude scaling of computing, while achieving high reli- ability on and supporting ease-of-use of super computing resources at the same time. We describe two example use cases, the implementation challenges and constraints, the actual application enabling and report our ndings.