Issue |
EPJ Web Conf.
Volume 214, 2019
23rd International Conference on Computing in High Energy and Nuclear Physics (CHEP 2018)
|
|
---|---|---|
Article Number | 03033 | |
Number of page(s) | 7 | |
Section | T3 - Distributed computing | |
DOI | https://doi.org/10.1051/epjconf/201921403033 | |
Published online | 17 September 2019 |
https://doi.org/10.1051/epjconf/201921403033
Evolution of HammerCloud to commission CERN Compute resources
CERN, 1 Esplanade Des Particules,
Geneva,
Switzerland
* e-mail: jaroslava.schovancova@cern.ch
Published online: 17 September 2019
HammerCloud is a testing service and framework to commission, run continuous tests or on-demand large-scale stress tests, and benchmark computing resources and components of various distributed systems with realistic full-chain experiment workflows.
HammerCloud, used by the ATLAS and CMS experiments in production, has been a useful service to commission both compute resources and various components of the complex distributed systems of the LHC experiments, as well as integral partof the monitoring suite that is essential for the computing operations of the experiments and their automation.
In this contribution we review recent developments of the HammerCloud service that allow use of HammerCloud infrastructure to test Data Centre resources in the early phases of the infrastructure and services commissioning process. One of thebenefits we believe HammerCloud can provide is to be able to tune the commissioning of the new infrastructure, functional and also stress testing, as well as benchmarking with "standard candle" workflows, with experiment realistic workloads, that can be heavy for CPU, or I/O, or IOPS, or everything together. This extension of HammerCloud has been successfully usedin CERN IT during the prototype phase of the "BEER" Batch on EOS (Evaluation of Resources) project, and is being integrated with the continuous integration/continuous deployment suite for Batch service VMs.
© 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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