| Issue |
EPJ Web of Conf.
Volume 295, 2024
26th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2023)
|
|
|---|---|---|
| Article Number | 07042 | |
| Number of page(s) | 8 | |
| Section | Facilities and Virtualization | |
| DOI | https://doi.org/10.1051/epjconf/202429507042 | |
| Published online | 06 May 2024 | |
https://doi.org/10.1051/epjconf/202429507042
The CloudVeneto initiative: 10 years of operations to support interdisciplinary open science
1 INFN, Sezione di Padova, Via Marzolo 8, 35131 Padova, Italy
2 INFN, Laboratori Nazionali di Legnaro, Viale dell’Università 2, 35020 Legnaro (Padova), Italy
3 Padova Neuroscience Center, Università di Padova, Via Orus 2/B, 35131 Padova, Italy
4 Dipartimento di Fisica e Astronomia ‘Galileo Galilei”, Università di Padova, Via Marzolo 8, 35131 Padova, Italy
5 Dipartimento di Scienze Chimiche, Università di Padova, Via Marzolo 1, 35131 Padova, Italy
* Corresponding author: Federica.Fanzago@pd.infn.it
Published online: 6 May 2024
CloudVeneto is a private cloud targeted to scientific communities based on OpenStack software. It was designed in 2013 and put in operation one year later, to support INFN projects, mainly HEP ones. Its resources are physically distributed among two sites: the Physics Department of University of Padova-INFN Padova Unit and the INFN Legnaro National Laboratories. During these 10 years CloudVeneto evolved to integrate also resources funded by ten Departments of the University of Padova, and to support several scientific disciplines of different domains. The use cases the communities have to face up often show a common pattern. This was an opportunity for us to develop and improve the services on our infrastructure to provide common solutions to different use cases. It happened for example with the Container as a Service (CaaS) that makes the management of Kubernetes clusters easier from a user point of view. Moreover, CloudVeneto joined the INFN national cloud infrastructure (INFN Cloud), making available some resources to this federated infrastructure. CloudVeneto is also involved in an R&D project to realize a distributed analysis facility for the CMS experiment based on the HTCondor batch system. In this paper we describe some use-cases of different projects pointing out the common patterns and the new implementations and configurations done in the infrastructure.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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