iPlant atmosphere: a gateway to cloud infrastructure for the plant sciences

The cloud platform complements traditional compute and storage infrastructures by introducing capabilities for efficiently provisioning resources in a self-service, on-demand manner. The new provisioning model promises to accelerate scientific discovery by improving access to customizable and task-specific computing resources. This paradigm is well-suited, especially for those applications tailored to leverage cloud-style of infrastructure capabilities.

Adoption of the cloud model has been challenging for many domain scientists and scientific software developers due to the technical expertise required to effectively utilize this infrastructure. Some of the key limitations of cloud infrastructure are: limited integration with institutional authentication and authorization frameworks, lack of frameworks to enable domain-specific configurations for instances, and integration with scientific data repositories alongside existing computational clusters and grid deployments. Specifically designed to address some of these operational barriers towards adoptions by the plant sciences community, the iPlant Collaborative cloud platform, aptly named Atmosphere, is an open-source, robust, configurable gateway that extends established cloud infrastructure to meet the diverse computing needs for the plant science.

Atmosphere manages the Virtual Machine (VM) lifecycle while maximizing the utilization of cloud resources for scientific workflows. Thus, Atmosphere allows researchers developing novel analytical tools to deploy them with ease while abstracting the underlying computing infrastructure, at the same time making it relatively easy for the users to access these tools via web browser. Atmosphere also provides a rich extensible Application Programming Interface (APIs) for integration and automation with other services. Since its launch, Atmosphere has seen a wide adoption by the plant sciences community for a broad array of applications that range from image processing to next generation sequence (NGS) analysis and can serve as a template for providing similar capabilities to other domains.