# Sync & Share self service provisioning on INFN Cloud

- Institution: CERN
- Department: HEP Computing
- Speaker: Stefano Stalio
- Year: 2023
- Language: English
- Subjects: Computer science
- Source: [CERN](https://videos.cern.ch/record/3002167)
- Licence: [CERN](http://copyright.web.cern.ch)
- Who can watch: Tweens profiles and older (sources give no ratings; placed by Invisible Network from the source's own words)

Following up on 20 years of successful development and operation of the largest Italian research e-infrastructure through the Grid, the Italian National Institute for Nuclear Physics (INFN) has been running for the past three years INFN Cloud, a production-level, integrated and comprehensive cloud-based set of solutions, delivered through distributed and federated infrastructures.

INFN Cloud provides a large and customizable set of services, ranging from simple IaaS to specialized SaaS solutions, centered through a PaaS layer built upon flexible authentication and authorization services offered via INDIGO-IAM, and optimized resources and services orchestration.

Sync & Share instances based on ownCloud or NextCloud are among the several applications and services that users can self-deploy via the INFN Cloud dashboard.

Besides giving a general overview of INFN Cloud and its federated model, this talk will describe how the deployment of Sync & Share services for small to medium sized communities is fully automated. We will show how added-value features are integrated: a geographically distributed S3 storage backend, automated database and configuration backup, dedicated resource monitoring, secure connections and centralized authentication/authorization. We will also describe how INFN Cloud may provide a dedicated solution for supporting sensitive data privacy that exploits end-user level encryption of the storage block devices, used by ownCloud or NextCloud to store user data.

## Lectures

1. [Sync & Share self service provisioning on INFN Cloud](https://invisiblenetwork.ai/learn/cern/3002167/d901bedce3b1), 12 min (CERN's player)