TY - GEN
T1 - The Evolution of Cloud Computing in ATLAS
AU - Taylor, Ryan P
AU - Berghaus, Frank
AU - Brasolin, Franco
AU - Cordeiro, Cristovao
AU - Desmarais, Ron
AU - Field, Laurence
AU - Gable, Ian
AU - Giordano, Domenico
AU - Di Girolamo, Alessandro
AU - Hover, John
AU - Leblanc, Matthew Edgar
AU - Love, Peter
AU - Paterson, Michael
AU - Sobie, Randall
AU - Zaytsev, Alexandr
PY - 2015
Y1 - 2015
N2 - The ATLAS experiment at the LHC has successfully incorporated cloud computing technology and cloud resources into its primarily grid-based model of distributed computing. Cloud R&D activities continue to mature and transition into stable production systems, while ongoing evolutionary changes are still needed to adapt and refine the approaches used, in response to changes in prevailing cloud technology. In addition, completely new developments are needed to handle emerging requirements. This paper describes the overall evolution of cloud computing in ATLAS. The current status of the virtual machine (VM) management systems used for harnessing Infrastructure as a Service resources are discussed. Monitoring and accounting systems tailored for clouds are needed to complete the integration of cloud resources within ATLAS' distributed computing framework. We are developing and deploying new solutions to address the challenge of operation in a geographically distributed multi-cloud scenario, including a system for managing VM images across multiple clouds, a system for dynamic location-based discovery of caching proxy servers, and the usage of a data federation to unify the worldwide grid of storage elements into a single namespace and access point. The usage of the experiment's high level trigger farm for Monte Carlo production, in a specialized cloud environment, is presented. Finally, we evaluate and compare the performance of commercial clouds using several benchmarks.
AB - The ATLAS experiment at the LHC has successfully incorporated cloud computing technology and cloud resources into its primarily grid-based model of distributed computing. Cloud R&D activities continue to mature and transition into stable production systems, while ongoing evolutionary changes are still needed to adapt and refine the approaches used, in response to changes in prevailing cloud technology. In addition, completely new developments are needed to handle emerging requirements. This paper describes the overall evolution of cloud computing in ATLAS. The current status of the virtual machine (VM) management systems used for harnessing Infrastructure as a Service resources are discussed. Monitoring and accounting systems tailored for clouds are needed to complete the integration of cloud resources within ATLAS' distributed computing framework. We are developing and deploying new solutions to address the challenge of operation in a geographically distributed multi-cloud scenario, including a system for managing VM images across multiple clouds, a system for dynamic location-based discovery of caching proxy servers, and the usage of a data federation to unify the worldwide grid of storage elements into a single namespace and access point. The usage of the experiment's high level trigger farm for Monte Carlo production, in a specialized cloud environment, is presented. Finally, we evaluate and compare the performance of commercial clouds using several benchmarks.
U2 - 10.1088/1742-6596/664/2/022038
DO - 10.1088/1742-6596/664/2/022038
M3 - Conference contribution
VL - 664
T3 - J. Phys. Conf. Ser.
SP - 022038
BT - 21st International Conference on Computing in High Energy and Nuclear Physics (CHEP 2015)
ER -