Evolution of HammerCloud to commission CERN Compute resources

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...

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Bibliographic Details
Published in:EPJ Web of conferences Vol. 214; p. 3033
Main Authors: Schovancová, Jaroslava, Di Girolamo, Alessandro, Fkiaras, Aristeidis, Mancinelli, Valentina
Format: Journal Article Conference Proceeding
Language:English
Published: Les Ulis EDP Sciences 01-01-2019
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Summary: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.
ISSN:2100-014X
2101-6275
2100-014X
DOI:10.1051/epjconf/201921403033