DUNE Rucio development and monitoring

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.

Authors

Institutions

Publication Details

Journal
EPJ Web of Conferences
Published
2025-01-01
DOI
https://doi.org/10.1051/epjconf/202533701195
Primary Topic
Neutrino Physics Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

DUNE Rucio development and monitoring

Wenlong Yuan
EPJ Web of Conferences
Neutrino Physics Research
article

DUNE Rucio development and monitoring

Wenlong Yuan
article en

Abstract

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.

EPJ Web of ConferencesVol. 337
University of Edinburgh (GB)
Openalex Percentile: Top 88%
Neutrino Physics Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.