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Large scientific facilities are unique and complex infrastructures that have become fundamental instruments for enabling high quality, world-leading research to tackle scientific problems at unprecedented scales. Cyberinfrastructure (CI) is an essential component of these facilities, providing the user community with access to data, data products, and services with the potential to transform data into knowledge. However, the timely evolution of the CI available at large facilities is challenging and can result in science communities requirements not being fully satisfied. Furthermore, integrating CI across multiple facilities as part of a scientific workflow is hard, resulting in data silos. In this paper, we explore how science gateways can provide improved user experiences and services that may not be offered at large facility datacenters. Using a science gateway supported by the Science Gateway Community Institute, which provides subscription-based delivery of streamed data and data products from the NSF Ocean Observatories Initiative (OOI), we propose a system that enables streaming-based capabilities and workflows using data from large facilities, such as the OOI, in a scalable manner. We leverage data infrastructure building blocks, such as the Virtual Data Collaboratory, which provides data and comput- ing capabilities in the continuum to efficiently and collaboratively integrate multiple data-centric CIs, build data-driven workflows, and connect large facilities data sources with NSF-funded CI, such as XSEDE. We also introduce architectural solutions for running these workflows using dynamically provisioned federated CI. 

Enterprise and Cloud environments are rapidly evolving with the use of lightweight virtualization mechanisms such as containers. Containerization allow users to deploy applications in any environment faster and more efficiently than using virtual machines. However, most of the work in this area focused on Linux-based containerization such as Docker and LXC and other mature solutions such as FreeBSD Jails have not been adopted by production-ready environments. In this work we explore the use of FreeBSD virtualization and provide a comparative study with respect to Linux containerization using Apache Spark. Preliminary results show that, while Linux containers provide better performance, FreeBSD solutions provide more stable and consistent results.