Speaker
Christophe Haen
(Univ. Blaise Pascal Clermont-Fe. II (FR))
Description
The LHCb online system relies on a large and heterogeneous IT infrastructure made from thousands of servers on which many different applications are running. They run a great variety of tasks : critical ones such as data taking and secondary ones like web servers. The administration of such a system and making sure it is working properly represents a very important workload for the small expert-operator team.
Research has been performed to try to automatize (some) system administration tasks, starting in 2001 when IBM defined the so-called “self objectives” supposed to lead to “autonomic computing”. In this context, we present a framework that makes use of artificial intelligence and machine learning to monitor and diagnose at a low level and in a non intrusive way Linux-based systems and their interaction with software. Moreover, the multi agent approach we use, coupled with a "object oriented paradigm" architecture should increase a lot our learning speed, and highlight relations between problems.
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Primary author
Christophe Haen
(Univ. Blaise Pascal Clermont-Fe. II (FR))
Co-authors
Enrico Bonaccorsi
(CERN)
Niko Neufeld
(CERN)
Prof.
Vincent BARRA
(LIMOS, UMR 6158 CNRS, Univ. Blaise Pascal)
