Abstract
Cloud computing has revolutionized the development and operations of hardware and software across diverse technological arenas, yet academic biomedical research has lagged behind despite the numerous and weighty advantages that cloud computing offers. Biomedical researchers who embrace cloud computing can reap rewards in cost reduction, decreased development and maintenance workload, increased reproducibility, ease of sharing data and software, enhanced security, horizontal and vertical scalability, high availability, a thriving technology partner ecosystem, and much more. Despite these advantages that cloud-based workflows offer, the majority of scientific software developed in academia does not utilize cloud computing and must be migrated to the cloud by the user. In this article, we present 11 quick tips for architecting biomedical informatics workflows on compute clouds, distilling knowledge gained from experience developing, operating, maintaining, and distributing software and virtualized appliances on the world’s largest cloud. Researchers who follow these tips stand to benefit immediately by migrating their workflows to cloud computing and embracing the paradigm of abstraction.
Highlights
Cloud computing is the on-demand use of computational hardware, software, and networks provided by a third party [1]
We present 11 quick tips for architecting biomedical informatics workflows on compute clouds, distilling knowledge gained from experience developing, operating, maintaining, and distributing software and virtualized appliances on the world’s largest cloud
We provide a high-level overview of some best practices for cloud computing with an emphasis on reproducibility, cost reduction, efficiency of development and operations, and ease of implementation
Summary
Cloud computing has revolutionized the tech sector, but academia is slow to adopt. These 11 quick tips are geared towards helping academic researchers and their teams harness the power of cloud computing by utilizing the design patterns that have evolved in the past decade. Cloud computing can increase reproducibility, scalability, resilience, fault-tolerance, security, ease of use, cost- and time-efficiency, and much more. This is a PLOS Computational Biology Education paper
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