Issue |
EPJ Web Conf.
Volume 214, 2019
23rd International Conference on Computing in High Energy and Nuclear Physics (CHEP 2018)
|
|
---|---|---|
Article Number | 08029 | |
Number of page(s) | 8 | |
Section | T8 - Networks & facilities | |
DOI | https://doi.org/10.1051/epjconf/201921408029 | |
Published online | 17 September 2019 |
https://doi.org/10.1051/epjconf/201921408029
Notifications workflows using the CERN IT central messaging infrastructure
1
CERN, 1, Esplanade des Particules,
1211 Geneva 23,
Switzerland
2
EPFL, CE 3 316 (Centre Est), Station 1,
CH-1015,
Switzerland
* e-mail: Zhechka.Toteva@cern.ch
Published online: 17 September 2019
In the CERN IT agile infrastructure (AI), Puppet, the CERN IT central messaging infrastructure (MI) and the Roger application are the key constituents handling the configuration of the machines of the computer centre. The machine configuration at any given moment depends on its declared state in Roger and Puppet ensures the actual implementation of the desired configuration by running the Puppet agent on the machine at regular intervals, typically every 90 minutes. Sometimes it is preferable that the configuration change is propagated immediately to the targeted machine, ahead of the next scheduled Puppet agent run on this machine. The particular need of handling notifications in a highly scalable manner for a large scale infrastructure has been satisfied with the implementation of the CERNMegabus architecture, based on the ActiveMQ messaging system. The design and implementation of the CERN-Megabus architecture are introduced, followed by the implementation of the Roger notification workflow. The choice of ActiveMQ is analysed and the message flow between the Roger notification producer and the CASTOR, EOS, BATCH and Load Balancing consumers are presented. The employment of predefined consumer modules in order to speed up the on-boarding of new CERN-Megabus use cases is also described.
© The Authors, published by EDP Sciences, 2019
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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