| Issue |
EPJ Web Conf.
Volume 251, 2021
25th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2021)
|
|
|---|---|---|
| Article Number | 02060 | |
| Number of page(s) | 11 | |
| Section | Distributed Computing, Data Management and Facilities | |
| DOI | https://doi.org/10.1051/epjconf/202125102060 | |
| Published online | 23 August 2021 | |
https://doi.org/10.1051/epjconf/202125102060
The ESCAPE Data Lake: The machinery behind testing, monitoring and supporting a unified federated storage infrastructure of the exabyte-scale
1 European Organization for Nuclear Research (CERN), Geneva, Switzerland
* e-mail: rizart.dona@cern.ch
** e-mail: riccardo.di.maria@cern.ch
Published online: 23 August 2021
The EU-funded ESCAPE project aims at enabling a prototype federated storage infrastructure, a Data Lake, that would handle data on the exabyte-scale, address the FAIR data management principles and provide science projects a unified scalable data management solution for accessing and analyzing large volumes of scientific data. In this respect, data transfer and management technologies such as Rucio, FTS and GFAL are employed along with monitoring enabling solutions such as Grafana, Elasticsearch and perf- SONAR. This paper presents and describes the technical details behind the machinery of testing and monitoring of the Data Lake – this includes continuous automated functional testing, network monitoring and development of insightful visualizations that reflect the current state of the system. Topics that are also addressed include the integration with the CRIC information system as well as the initial support for token based authentication / authorization by using OpenID Connect. The current architecture of these components is provided and future enhancements are discussed.
© The Authors, published by EDP Sciences, 2021
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.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.