Cost-Aware Cloud Provisioning

Cloud computing is often suggested as a low-cost and scalable model for executing and scaling scientific analyses. However, while the benefits of cloud computing are frequently touted, there are inherent technical challenges associated with scaling execution efficiently and cost-effectively. We describe here a cost-aware elastic provisioner designed to dynamically and cost-effectively provision cloud infrastructure based on the requirements of user-submitted scientific workflows. Our provisioner is used in the Globus Galaxies platform -- a Software-as-a-Service provider of scientific analysis capabilities using commercial cloud infrastructure. Using workloads from production usage of this platform we investigate the performance of our provisioner in terms of cost, spot instance termination rate, and execution time. We demonstrate cost savings across six production gateways of up to 95% and 12% improvement in total execution time when compared to a worst case scenario using a single instance type in a single availability zone.