INDIGO-DataCloud:A data and computing platform to facilitate seamless access to e-infrastructures
Abstract
This paper describes the achievements of the H2020 project INDIGO-DataCloud. The project has provided e-infrastructures with tools, applications and cloud framework enhancements to manage the demanding requirements of scientific communities, either locally or through enhanced interfaces. The middleware developed allows to federate hybrid resources, to easily write, port and run scientific applications to the cloud. In particular, we have extended existing PaaS (Platform as a Service) solutions, allowing public and private e-infrastructures, including those provided by EGI, EUDAT, and Helix Nebula, to integrate their existing services and make them available through AAI services compliant with GEANT interfederation policies, thus guaranteeing transparency and trust in the provisioning of such services. Our middleware facilitates the execution of applications using containers on Cloud and Grid based infrastructures, as well as on HPC clusters. Our developments are freely downloadable as open source components, and are already being integrated into many scientific applications.
Keywords
Cite
@article{arxiv.1711.01981,
title = {INDIGO-DataCloud:A data and computing platform to facilitate seamless access to e-infrastructures},
author = {DataCloud Collaboration and Davide Salomoni and Isabel Campos and Luciano Gaido and Jesus Marco de Lucas and Peter Solagna and Jorge Gomes and Ludek Matyska and Patrick Fuhrman and Marcus Hardt and Giacinto Donvito and Lukasz Dutka and Marcin Plociennik and Roberto Barbera and Ignacio Blanquer and Andrea Ceccanti and Mario David and Cristina Duma and Alvaro López-García and Germán Moltó and Pablo Orviz and Zdenek Sustr and Matthew Viljoen and Fernando Aguilar and Luis Alves and Marica Antonacci and Lucio Angelo Antonelli and Stefano Bagnasco and Alexandre M. J. J. Bonvin and Riccardo Bruno and Eva Cetinic and Yin Chen and Fabrizio Chiarello and Alessandro Costa and Stefano Dal Pra and Davor Davidovic and Alvise Dorigo and Benjamin Ertl and Federica Fanzago and Marco Fargetta and Sandro Fiore and Stefano Gallozzi and Zeynep Kurkcuoglu and Lara Lloret and Joao Martins and Alessandra Nuzzo and Paola Nassisi and Cosimo Palazzo and Joao Pina and Eva Sciacca and Matteo Segatta and Massimo Sgaravatto and Daniele Spiga and Sonia Taneja and Marco Antonio Tangaro and Michal Urbaniak and Sara Vallero and Marco Verlato and Bas Wegh and Valentina Zaccolo and Federico Zambelli and Lisa Zangrando and Stefano Zani and Tomasz Zok},
journal= {arXiv preprint arXiv:1711.01981},
year = {2022}
}
Comments
39 pages, 15 figures.Version accepted in Journal of Grid Computing