Review of CERN Data Centre Infrastructure

Andrade, Pedro; Bell, T; Eldik, J. Van; McCance, Gavin; Panzer-Steindel, B.; Santos, M.; and, S Traylen; Schwickerath, U.

doi:10.1088/1742-6596/396/4/042002

Cited by 22 publications

(12 citation statements)

References 3 publications

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“…A pilot test system was built subsequently and is also described below. The pilot system used Puppet [3] for configuration management in a similar way as many of the CERN Data Centre systems [4]. It used similar hardware as testbed 2 but consisted of 3 similar storage servers.…”

Section: Testbed Systemsmentioning

confidence: 99%

Sharing server nodes for storage and computer

et al. 2019

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Based on the observation of low average CPU utilisation of several hundred file storage servers in the EOS storage system at CERN, the Batch on EOS Extra Resources (BEER) project developed an approach to also utilise these resources for batch processing. Initial proof of concept tests showed little interference between batch and storage services on a node. Subsequently a model for production was developed and implemented. This has been deployed on part of the CERN EOS production service. The implementation and test results will be presented. The potential for additional resources at the CERN Tier-0 centre is of the order of ten thousand hardware threads in the near term, as well as being a step towards a hyper-converged infrastructure.

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Section: Testbed Systemsmentioning

confidence: 99%

Sharing server nodes for storage and computer

et al. 2019

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“…The HammerCloud service is a Django [12] web framework application backed by a MySQL [13] database. We run HammerCloud infrastructure on CERN Agile Infrastructure resources [14]. To scale up and utilize our testing infrastructure, we integrated Celery cluster [15] backed by Redis [16] in our infrastructure.…”

Section: Hammercloud Architecture and Evolutionmentioning

confidence: 99%

Evolution of HammerCloud to commission CERN Compute resources

et al. 2019

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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.

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“…The most relevant project for the scientific reference domain of INFN is certainly the CERN OpenStack Private Cloud [2]. In 2011 CERN's IT team decided to build a private cloud that would need to integrate well with their very heterogeneous environment.…”

Section: Related Workmentioning

confidence: 99%

The Cloud Area Padovana? An OpenStack Based IaaS for the INFN User Community

Verlato¹

2016

Proceedings of International Symposium on Grids and Clouds 2015 — PoS(ISGC2015)

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At the end of 2013 INFN-Padova division and Legnaro National Laboratories (LNL) jointly started a new project aiming at expanding their grid-based computing and storage facility, mainly targeted to the needs of the big LHC experiments, with a cloud-based offering best suited to address the needs of the smaller sized physics experiments carried out by the local teams. Despite the great success of the grid model in supporting large scale HEP experiments, its adoption within smaller experiments has in fact been quite limited due to the well known lack of flexibility of the grid, e.g. in terms of: authentication/authorisation mechanisms; few OS and execution environments supported; batch-like only access to resources (no interactivity); deep learning curve for deploying/using services. This leads to a proliferation of several small computing clusters, disconnected from the grid infrastructure, owned by each experiment and fully dedicated to it, often underutilised but not powerful enough to satisfy peak usage needs concentrated in short periods (typically close to a scientific conference deadline). This scenario clearly implies low efficiency and large waste of both human and hardware resources for the data centre. The new cloud-based infrastructure is aimed at merging these scattered computing and storage resources in a unique facility that can serve the different experimental teams ondemand with the maximum of flexibility and elasticity made possible by the cloud paradigm. Leveraging the long-standing experience and collaboration as LHC Tier-2 of the Padova and LNL data centres, separated by 10 km but connected with a dedicated 10 Gbps optical link, the "Cloud Area Padovana" was built and put into production at the end of October 2014, after six months of pre-production operations while a couple of pilot experiments tested the capabilities of the infrastructure with real use-cases. OpenStack was chosen as Cloud Management Framework for implementing a IaaS where computing and storage resources were shared between the two data centres. However, several customisations and innovative services were added to the standard OpenStack deployment in order to address the users' needs, ensure system reliability and implement an efficient resource allocation. These concern the integration with OpenStack of authentication protocols like SAML and OpenID in order to enable user registration and access at first via INFN-AAI and later via Italian (IDEM) and possibly other international identity federations; the implementation of advanced functionalities for the management of users and projects by the IaaS administrators; the High Availability solution adopted to implement fault-tolerance of the cloud services; the development of a fair-share resource allocation mechanism analogous to the ones available in the batch system schedulers for maximizing the usage of shared resources among concurrent users/projects. An overall description of the cloud infrastructure and its operations will be given, together with the perspective of the mai...

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Review of CERN Data Centre Infrastructure

Cited by 22 publications

References 3 publications

Sharing server nodes for storage and computer

Sharing server nodes for storage and computer

Evolution of HammerCloud to commission CERN Compute resources

The Cloud Area Padovana? An OpenStack Based IaaS for the INFN User Community

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