Cloud Computing has long extended beyond the original focus of providing scalable on-demand resources for web applications and is now also ubiquitous in batch-style data processing applications. Employing Cloud services for data analysis tasks is also a viable alternative for researchers who are limited by their locally available compute power and in the need for timely execution. However, the provisioning and deployment of machines and applications at Infrastructure-as-a-Service (IaaS) providers is a non-trivial task for the average scientist. Within this paper, we propose a framework for automating the deployment and execution of existing applications in a data-parallel fashion in Cloud environments with only negligible effort by the user. Our evaluation of a real-world scientific use case exhibits a significant speedup compared to local execution.
['Michael Göttsche', 'Fabian Glaser', 'Steffen Herbold', 'Jens Grabowski']
Automated Deployment and Parallel Execution of Legacy Applications in Cloud Environments (Short Paper)