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Phronesis, a diagnosis and recovery tool for system administrators

Abstract : 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 shared experience approach we use, coupled with an "object oriented paradigm" architecture increases a lot our learning speed, and highlight relations between problems.
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Submitted on : Friday, February 21, 2014 - 7:57:08 PM
Last modification on : Sunday, June 26, 2022 - 9:36:31 AM
Long-term archiving on: : Wednesday, May 21, 2014 - 12:20:46 PM


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  • HAL Id : tel-00950700, version 1


Christophe Haen. Phronesis, a diagnosis and recovery tool for system administrators. Other [cs.OH]. Université Blaise Pascal - Clermont-Ferrand II, 2013. English. ⟨NNT : 2013CLF22387⟩. ⟨tel-00950700⟩



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