Building an open source cloud environment with auto-scaling resources for executing bioinformatics and biomedical workflows

Abstract

Fast and simple access to computing resources for in-silico experiments and processing of large amounts of data have become crucial factors for researchers in the bioinformatics and biomedical domains. Cloud computing offers the possibility of accessing computing resources for a flexible amount of time and with varying requirements. We discuss how a full cloud stack ranging from Infrastructure-as-a-Service (IaaS) via Platform-as-a-Service (PaaS) to Software-as-a-Service (SaaS) can be built on open source technologies including the integration of high-throughput data transfers in all service types. Based on the scaling capabilities provided by the tools used on the IaaS level we devise a strategy to build a dynamically scaling PaaS offering for building and running workflows using Galaxy. Finally, applications — available as SaaS offerings — for two distinct use cases from the bioinformatics and biomedical domains are presented to demonstrate the feasibility and performance of our solution.