| Issue |
EPJ Web Conf.
Volume 214, 2019
23rd International Conference on Computing in High Energy and Nuclear Physics (CHEP 2018)
|
|
|---|---|---|
| Article Number | 07001 | |
| Number of page(s) | 4 | |
| Section | T7 - Clouds, virtualisation & containers | |
| DOI | https://doi.org/10.1051/epjconf/201921407001 | |
| Published online | 17 September 2019 | |
https://doi.org/10.1051/epjconf/201921407001
Fair Share Scheduler for OpenNebula
Implementation and performance tests
1
Istituto Nazionale di Fisica Nucleare, Sezione di Torino,
Via Pietro Giuria 1, 10125,
Torino,
Italy
2
Università e INFN, Dipartimento di Fisica di Trieste,
Via Alfonso Valerio 2, 34127
Trieste,
Italy
* e-mail: stefano.bagnasco@to.infn.it
** e-mail: sara.vallero@to.infn.it
*** e-mail: valentina.zaccolo@ts.infn.it
Published online: 17 September 2019
A small Cloud infrastructure for scientific computing likely operates in a saturated regime, which imposes to optimize the allocation of resources. Tenants typically pay a priori for a fraction of the overall resources. Within this business model, an advanced scheduling strategy is needed in order to optimize the data centre occupancy. FaSS, a Fair Share Scheduler service for OpenNebula, addresses this issue by satisfying resource requests according to an algorithm, which prioritizes tasks according to an initial weight and to the historical resource usage of the project. In this proceedings, we are going to describe the implementation of FaSS Version 1.0, released in March 2017 as a product of the INDIGO-DataCloud project. We are also going to discuss the results of FaSS functional and stress tests performed at the Cloud infrastructure of the INFN-Torino computing centre.
© 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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