# Federated Sync&Share

- Institution: CERN
- Department: HEP Computing
- Speaker: Enrico Signoretti
- Year: 2024
- Language: English
- Subjects: Computer science
- Source: [CERN](https://videos.cern.ch/record/3008169)
- 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)

In this talk, we focus on a new paradigm to create a federated sync and share platform by integrating Next Cloud and Cubbit.

In this paradigm, NextCloud acts as the sync engine and front-end application for collaborative sharing, while Cubbit provides the scalable geo-distributed infrastructure on which data are stored in a disaster-proof, redundant geo-distributed scheme. The goal of the project is to build a federated cloud spread across European research centers and universities, where single institutions contribute computing and capacity resources and receive back highly resilient cloud storage at a very competitive price. This service is delivered in two different modes: Local or Global. The first is aimed at single departments and small teams, while the latter is aimed at international organizations and larger teams working across different countries. The combination of Next Cloud with Cubbit offers a unique solution centered on key aspects of modern data management and sharing: data sovereignty, security, resiliency and mobility, and cost..

0:00:00 Slide 1

0:00:14 Slide 2

0:00:26 Slide 3

0:00:38 Slide 4

0:00:50 Slide 5

0:01:02 Slide 6

0:01:14 Slide 7

0:01:27 Slide 8

0:01:39 Slide 9

0:01:51 Slide 10

0:02:03 Slide 11

0:02:15 Slide 12

0:02:27 Slide 13

0:02:40 Slide 14

0:02:52 Slide 15

0:03:04 Slide 16

0:03:16 Slide 17

0:03:28 Slide 18

0:03:40 Slide 19

0:03:53 Slide 20

0:04:05 Slide 21

0:04:17 Slide 22

0:04:29 Slide 23

0:04:41 Slide 24

0:04:53 Slide 25

0:05:06 Slide 26

0:05:18 Slide 27

0:05:30 Slide 28

0:05:42 Slide 29

0:05:54 Slide 30

## Lectures

1. [Federated Sync&Share](https://invisiblenetwork.ai/learn/cern/3008169/17ed21b108aa), 7 min (CERN's player)
