Article
Version 2
This version is not peer-reviewed
A Cloud-Based Data Collaborative to Combat the COVID-19 Pandemic and to Solve Major Technology Challenges
Version 1
: Received: 18 December 2020 / Approved: 21 December 2020 / Online: 21 December 2020 (10:13:05 CET)
Version 2 : Received: 12 January 2021 / Approved: 13 January 2021 / Online: 13 January 2021 (07:43:55 CET)
Version 3 : Received: 19 February 2021 / Approved: 19 February 2021 / Online: 19 February 2021 (11:31:42 CET)
Version 2 : Received: 12 January 2021 / Approved: 13 January 2021 / Online: 13 January 2021 (07:43:55 CET)
Version 3 : Received: 19 February 2021 / Approved: 19 February 2021 / Online: 19 February 2021 (11:31:42 CET)
A peer-reviewed article of this Preprint also exists.
DOI: 10.3390/fi13030061
Abstract
The XPRIZE Foundation designs and operates multi-million-dollar, global competitions to incentivize the development of technological breakthroughs that accelerate humanity toward a better future. To combat the COVID-19 pandemic, the Foundation coordinated with several organizations to make available data sets about different facets of the disease and to provide the computational resources needed to analyze those data sets. We describe the requirements, design, and implementation of the XPRIZE Data Collaborative, a cloud-based infrastructure that enables the XPRIZE to meet its COVID-19 mission and host future data-centric competitions. We offer our experiences as a case study of a Cloud Native application developed during the pandemic, from motivations and design to implementation. In contrast to previous Cloud deployment studies that focus on implementations of containers and microservices or serverless architecture, we describe how and why we used both containers, serverless, and other Cloud technologies, even older ones such as Virtual Machines. We include our experiences of having users successfully exercise the Data Collaborative, detailing the challenges encountered and areas for improvement.
Keywords
containers; virtual machines; cloud; COVID-19; serverless; analytics; software defined infrastructure
Subject
MATHEMATICS & COMPUTER SCIENCE, Algebra & Number Theory
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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