The Evolution of Cloud Computing in ATLAS

21st International Conference on Computing in High Energy and Nuclear Physics

物理学;计算机科学

Taylor, Ryan P.^1 ; Berghaus, Frank^1 ; Brasolin, Franco^2 ; Cordeiro, Cristovao Jose Domingues^3 ; Desmarais, Ron^1 ; Field, Laurence^3 ; Gable, Ian^1 ; Giordano, Domenico^3 ; Di Girolamo, Alessandro^3 ; Hover, John^4 ; Leblanc, Matthew^1 ; Love, Peter^5 ; Paterson, Michael^1 ; Sobie, Randall^1 ; Zaytsev, Alexandr^4

University of Victoria, Victoria, Canada^1

INFN Bologna, Bologna, Italy^2

CERN, Geneva, Switzerland^3

Brookhaven National Laboratory, Upton, United States^4

Lancaster University, Lancaster, United Kingdom^5

关键词: Cloud computing technologies;    Cloud environments;    Cloud technologies;    Distributed computing frameworks;    Dynamic locations;    Evolutionary changes;    High-level triggers;    Management systems;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/664/2/022038/pdf
DOI  :  10.1088/1742-6596/664/2/022038

学科分类：计算机科学（综合）

来源: IOP

【 摘 要 】

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.