
The computational demands for scientific applications are continuously increasing. The emergence of cloud computing has enabled on-demand resource allocation. However, relying solely on infrastructure as a service does not achieve the degree of flexibility required by the scientific community. Here we present a microservice-oriented methodology, where scientific applications run in a distributed orchestration platform as software containers, referred to as on-demand, virtual research environments. The methodology is vendor agnostic and we provide an open source implementation that supports the major cloud providers, offering scalable management of scientific pipelines. We demonstrate applicability and scalability of our methodology in life science applications, but the methodology is general and can be applied to other scientific domains.
FOS: Computer and information sciences, Bioinformatics, Orchestration, QA75.5-76.95, Microservices, Computer Science - Distributed, Parallel, and Cluster Computing, Virtual research environments, Electronic computers. Computer science, Cloud computing, Distributed, Parallel, and Cluster Computing (cs.DC), Application containers
FOS: Computer and information sciences, Bioinformatics, Orchestration, QA75.5-76.95, Microservices, Computer Science - Distributed, Parallel, and Cluster Computing, Virtual research environments, Electronic computers. Computer science, Cloud computing, Distributed, Parallel, and Cluster Computing (cs.DC), Application containers
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 13 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
