Preparing Distributed Computing Operations for the HL-LHC Era With Operational Intelligence Di Girolamo et al. Operational Intelligence and HL-LHC Computing Operations

Abstract

'Jaroslava Schovancová' 'Thomas Beermann' 'Michael Boehler' 'Daniele Bonacorsi' 'Luca Clissa' 'Leticia Decker de Sousa' 'Tommaso Diotalevi' 'Luca Giommi' 'Maria Grigorieva' 'Domenico Giordano' 'David Hohn' 'Tomáš Javůrek' 'Stephane Jezequel' 'Valentin Kuznetsov' 'Mario Lassnig' 'Vasilis Mageirakos' 'Micol Olocco' 'Siarhei Padolski' 'Matteo Paltenghi' 'Lorenzo Rinaldi' 'Mayank Sharma' 'Simone Rossi Tisbeni' 'Nikodemas Tuckus'] As a joint effort from various communities involved in the Worldwide LHC Computing Grid, the Operational Intelligence project aims at increasing the level of automation in computing operations and reducing human interventions. The distributed computing systems currently deployed by the LHC experiments have proven to be mature and capable of meeting the experimental goals, by allowing timely delivery of scientific results. However, a substantial number of interventions from software developers, shifters, and operational teams is needed to efficiently manage such heterogenous infrastructures. Under the scope of the Operational Intelligence project, experts from several areas have gathered to propose and work on “smart” solutions. Machine learning, data mining, log analysis, and anomaly detection are only some of the tools we have evaluated for our use cases. In this community study contribution, we report on the development of a suite of operational intelligence services to cover various use cases: workload management, data management, and site operations.