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Total Cost of Ownership and Evaluation of Google Cloud Resources for the ATLAS Experiment at the LHC

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Total Cost of Ownership and Evaluation of Google Cloud Resources for the ATLAS Experiment at the LHC. / collaboration, The ATLAS; Ali, Hanadi; Alsolami, Zainab et al.
In: Computing and Software for Big Science, Vol. 9, No. 1, 2, 28.01.2025.

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collaboration TATLAS, Ali H, Alsolami Z, Barton AE, Borissov G, Bouhova-Thacker EV et al. Total Cost of Ownership and Evaluation of Google Cloud Resources for the ATLAS Experiment at the LHC. Computing and Software for Big Science. 2025 Jan 28;9(1):2. doi: 10.1007/s41781-024-00128-x

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collaboration, The ATLAS ; Ali, Hanadi ; Alsolami, Zainab et al. / Total Cost of Ownership and Evaluation of Google Cloud Resources for the ATLAS Experiment at the LHC. In: Computing and Software for Big Science. 2025 ; Vol. 9, No. 1.

Bibtex

@article{b47ea29b5d274eed9b819e5f50c538fb,
title = "Total Cost of Ownership and Evaluation of Google Cloud Resources for the ATLAS Experiment at the LHC",
abstract = "The ATLAS Google Project was established as part of an ongoing evaluation of the use of commercial clouds by the ATLAS Collaboration, in anticipation of the potential future adoption of such resources by WLCG grid sites to fulfil or complement their computing pledges. Seamless integration of Google cloud resources into the worldwide ATLAS distributed computing infrastructure was achieved at large scale and for an extended period of time, and hence cloud resources are shown to be an effective mechanism to provide additional, flexible computing capacity to ATLAS. For the first time a total cost of ownership analysis has been performed, to identify the dominant cost drivers and explore effective mechanisms for cost control. Network usage significantly impacts the costs of certain ATLAS workflows, underscoring the importance of implementing such mechanisms. Resource bursting has been successfully demonstrated, whilst exposing the true cost of this type of activity. A follow-up to the project is underway to investigate methods for improving the integration of cloud resources in data-intensive distributed computing environments and reducing costs related to network connectivity, which represents the primary expense when extensively utilising cloud resources.",
author = "collaboration, {The ATLAS} and Hanadi Ali and Zainab Alsolami and A.E. Barton and G. Borissov and E.V. Bouhova-Thacker and Ruby Ferguson and James Ferrando and H. Fox and Alina Hagan and R.C.W. Henderson and R.W.L. Jones and V. Kartvelishvili and P.A. Love and E.J. Marshall and L. Meng and D. Muenstermann and N. Ribaric and Elliot Sampson and M. Smizanska and A.M. Wharton",
year = "2025",
month = jan,
day = "28",
doi = "10.1007/s41781-024-00128-x",
language = "English",
volume = "9",
journal = "Computing and Software for Big Science",
issn = "2510-2036",
publisher = "Springer Science and Business Media LLC",
number = "1",

}

RIS

TY - JOUR

T1 - Total Cost of Ownership and Evaluation of Google Cloud Resources for the ATLAS Experiment at the LHC

AU - collaboration, The ATLAS

AU - Ali, Hanadi

AU - Alsolami, Zainab

AU - Barton, A.E.

AU - Borissov, G.

AU - Bouhova-Thacker, E.V.

AU - Ferguson, Ruby

AU - Ferrando, James

AU - Fox, H.

AU - Hagan, Alina

AU - Henderson, R.C.W.

AU - Jones, R.W.L.

AU - Kartvelishvili, V.

AU - Love, P.A.

AU - Marshall, E.J.

AU - Meng, L.

AU - Muenstermann, D.

AU - Ribaric, N.

AU - Sampson, Elliot

AU - Smizanska, M.

AU - Wharton, A.M.

PY - 2025/1/28

Y1 - 2025/1/28

N2 - The ATLAS Google Project was established as part of an ongoing evaluation of the use of commercial clouds by the ATLAS Collaboration, in anticipation of the potential future adoption of such resources by WLCG grid sites to fulfil or complement their computing pledges. Seamless integration of Google cloud resources into the worldwide ATLAS distributed computing infrastructure was achieved at large scale and for an extended period of time, and hence cloud resources are shown to be an effective mechanism to provide additional, flexible computing capacity to ATLAS. For the first time a total cost of ownership analysis has been performed, to identify the dominant cost drivers and explore effective mechanisms for cost control. Network usage significantly impacts the costs of certain ATLAS workflows, underscoring the importance of implementing such mechanisms. Resource bursting has been successfully demonstrated, whilst exposing the true cost of this type of activity. A follow-up to the project is underway to investigate methods for improving the integration of cloud resources in data-intensive distributed computing environments and reducing costs related to network connectivity, which represents the primary expense when extensively utilising cloud resources.

AB - The ATLAS Google Project was established as part of an ongoing evaluation of the use of commercial clouds by the ATLAS Collaboration, in anticipation of the potential future adoption of such resources by WLCG grid sites to fulfil or complement their computing pledges. Seamless integration of Google cloud resources into the worldwide ATLAS distributed computing infrastructure was achieved at large scale and for an extended period of time, and hence cloud resources are shown to be an effective mechanism to provide additional, flexible computing capacity to ATLAS. For the first time a total cost of ownership analysis has been performed, to identify the dominant cost drivers and explore effective mechanisms for cost control. Network usage significantly impacts the costs of certain ATLAS workflows, underscoring the importance of implementing such mechanisms. Resource bursting has been successfully demonstrated, whilst exposing the true cost of this type of activity. A follow-up to the project is underway to investigate methods for improving the integration of cloud resources in data-intensive distributed computing environments and reducing costs related to network connectivity, which represents the primary expense when extensively utilising cloud resources.

U2 - 10.1007/s41781-024-00128-x

DO - 10.1007/s41781-024-00128-x

M3 - Journal article

VL - 9

JO - Computing and Software for Big Science

JF - Computing and Software for Big Science

SN - 2510-2036

IS - 1

M1 - 2

ER -