Issue |
EPJ Web Conf.
Volume 245, 2020
24th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2019)
|
|
---|---|---|
Article Number | 05002 | |
Number of page(s) | 8 | |
Section | 5 - Software Development | |
DOI | https://doi.org/10.1051/epjconf/202024505002 | |
Published online | 16 November 2020 |
https://doi.org/10.1051/epjconf/202024505002
Chopin Management System: improving Windows infrastructure monitoring and management
1
Warsaw University of Technology
2
CERN
* e-mail: m.pacuszka@stud.elka.pw.edu.pl
** e-mail: sebastian.bukowiec@cern.ch
*** e-mail: esteban.puentes@cern.ch
**** e-mail: guillaume.metral@cern.ch
Published online: 16 November 2020
CERN Windows server infrastructure consists of about 650 servers. The management and maintenance is often a challenging task as the data to be monitored is disparate and has to be collected from various sources. Currently, alarms are collected from the Microsoft System Center Operation Manager (SCOM) and many administrative actions are triggered through e-mails sent by various systems or scripts.
The objective of the Chopin Management System project is to maximize automation and facilitate the management of the infrastructure. The current status of the infrastructure, including essential health checks, is centralized and presented through a dashboard. The system collects information necessary for managing the infrastructure in the real-time, such as hardware configuration or Windows updates, and reacts to any change or failure instantly. As part of the system design, big data streaming technologies are employed in order to assure the scalability and fault-tolerance of the service, should the number of servers drastically grow. Server events are aggregated and processed in real-time through the use of these technologies, ensuring quick response to possible failures. This paper presents details of the architecture and design decisions taken in order to achieve a modern, maintainable and extensible system for Windows Server Infrastructure management at CERN.
© The Authors, published by EDP Sciences, 2020
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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