| Issue |
EPJ Web Conf.
Volume 337, 2025
27th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2024)
|
|
|---|---|---|
| Article Number | 01195 | |
| Number of page(s) | 7 | |
| DOI | https://doi.org/10.1051/epjconf/202533701195 | |
| Published online | 07 October 2025 | |
https://doi.org/10.1051/epjconf/202533701195
DUNE Rucio development and monitoring
The University of Edinburgh
* e-mail: wenlong.yuan@ed.ac.uk
Published online: 7 October 2025
The Deep Underground Neutrino Experiment (DUNE) is scheduled to start running in 2029, expected to record 30 PB/year of raw data. To handle this large-scale data, DUNE has adopted and deployed Rucio, the nextgeneration Data Replica service originally designed by the ATLAS collaboration, as an essential component of its Distributed Data Management system.
DUNE’s use of Rucio has demanded the addition of various features to the Rucio code base, both specific functionality for DUNE alone, and more general functionality that is crucial for DUNE whilst being potentially useful for other experiments. As part of our development work, we have introduced a “policy package” system allowing experiment-specific code to be maintained separately from the core Rucio code, as well as creating a DUNE policy package containing algorithms such as logical to physical filename translation, and special permission checks. We have also developed other features such as improved object store support, and customisable replica sorting. A DUNE-specific test suite that will run on GitHub Actions is currently under development.
Recently, DUNE has deployed new internal monitoring to Rucio, enabling us to extract more useful information from core Rucio servers, and daemons such as conveyor, reaper, hermes etc. Additionally, DUNE has implemented monitoring for Rucio transfer and deletion activities which are sent to a Message Queue via Rucio Hermes daemon. Information such as data location, accounting, and storage summary is extracted from the Rucio internal database and dumped into Elasticsearch for visualisation. The visualisation platforms utilised are based at Fermilab and Edinburgh. This monitoring is crucial for the ongoing DUNE data transfers and management development.
© The Authors, published by EDP Sciences, 2025
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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