The XSEDE User Portal (XUP) is a web interface providing a set of user specific XSEDE services and documentation to a diverse audience. The XUP architecture started out depending on monolithic services provided by large Java libraries, but continues to evolve to use an application programming interface (API) powered by a set of microservices. The goal is to have the XUP API provide development and deployment environments that are agile, sustainable, and capable of handling feature changes. In making this transition, we have developed guidelines for API services that balance complexity and reuse needs with flexibility requirements. In doing so, we have also created our own set of best practices on how to convert to using microservices. In this paper we will use the XSEDE User Portal API development as a case study to explain our rationale, approach, and experiences in working with microservices in a real production environment to provide better and more reliable science services for end users.
The CIPRES Science Gateway (CSG) is a public resource created to provide access to community phylogenetics codes on high performance computing resources. The CSG has been in operation since 2009, and has a large and growing user base. As a popular resource, the CSG provides an opportunity to study user behavior and job submissions in a Gateway environment. Here we examine CSG user and data turnover, jobs submissions success rates, and causes for job failures. The results of our investigation provide a better understanding of the populations that use the CSG, and point to areas where improvements can be made in meeting user needs and using resources more efficiently.
In this paper, we first present a brief summary of the Neuroscience Gateway (NSG) which has been in operation since 2013. NSG is providing computational neuroscientists access to Extreme Science and Engineering Discovery Environment (XSEDE) high performance computing (HPC) resources. As a part of running the NSG we have interacted closely with the neuroscience community. This has given us the opportunity to receive input and feedback from the neuroscience researchers regarding their cyberinfrastructure needs. This is now more important given the context of the BRAIN (Brain Research through Advancing Innovative Neurotechnologies) Initiative which is a national initiative announced in 2013. Based on this interaction with the neuroscience community and the input we have received for the last three years, we analyze the comprehensive cyberinfrastructure needs of the neuroscience community in the second part of the paper.