Application Splitting in the Cloud: A Performance Study

被引:0
|
作者
Faul, Franz [1 ]
Arizcorreta, Rafael [1 ]
Dudouet, Florian [2 ]
Bohnert, Thomas Michael [2 ]
机构
[1] Swiss Re, Zurich, Switzerland
[2] Zurich Univ Appl Sci, Winterthur, Switzerland
来源
PROCEEDINGS OF THE 6TH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING AND SERVICES SCIENCE, VOL 1 (CLOSER) | 2016年
关键词
Cloud Computing; Performance; Database; Hybrid Cloud;
D O I
10.5220/0005857102450252
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Cloud-based deployments have become more and more mainstream in recent years, with many companies evaluating moving their infrastructure to the cloud, whether a public cloud, a private cloud, or a mix of the two through the hybrid cloud concept. One service offered by many clouds providers is Database-as-a-Service, where a user is offered a direct endpoint and access credentials to a chosen type of database. In this paper, we evaluate the performance impact of application splitting in a Hybrid Cloud environment. In this context, the database may be located in a cloud setting and the application servers on another cloud or on-premises, or the other way around. We found that for applications with low database latency and throughput requirements, moving to a public cloud environment can be a cost saving solution. None of the cloud providers evaluated were able to provide comparable performance for database-heavy database applications when compared to an optimized enterprise environment. Evaluating application splitting, we conclude that bursting to the cloud is a viable option in most cases, provided that the data is moved to the cloud before performing the requests.
引用
收藏
页码:245 / 252
页数:8
相关论文
共 50 条
  • [1] The application of cloud computing to astronomy: A study of cost and performance
    Berriman G.B.
    Juve G.
    Deelman E.
    Regelson M.
    Plavchan P.
    Proceedings - 6th IEEE International Conference on e-Science Workshops, e-ScienceW 2010, 2010, : 1 - 7
  • [2] HPC Application Performance and Cost Efficiency in the Cloud
    Roloff, Eduardo
    Diener, Matthias
    Gaspary, Luciano Paschoal
    Navaux, Philippe O. A.
    2017 25TH EUROMICRO INTERNATIONAL CONFERENCE ON PARALLEL, DISTRIBUTED AND NETWORK-BASED PROCESSING (PDP 2017), 2017, : 473 - 477
  • [3] CloudProphet: Towards Application Performance Prediction in Cloud
    Li, Ang
    Zong, Xuanran
    Kandula, Srikanth
    Yang, Xiaowei
    Zhang, Ming
    ACM SIGCOMM COMPUTER COMMUNICATION REVIEW, 2011, 41 (04) : 426 - 427
  • [4] Performance analysis of key splitting algorithms for cloud computing
    Buchade, Amar
    Ingle, Rajesh
    2016 INTERNATIONAL CONFERENCE ON COMPUTING, ANALYTICS AND SECURITY TRENDS (CAST), 2016, : 562 - 566
  • [5] The application of cloud computing to scientific workflows: a study of cost and performance
    Berriman, G. Bruce
    Deelman, Ewa
    Juve, Gideon
    Rynge, Mats
    Voeckler, Jens-S
    PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, 2013, 371 (1983):
  • [6] An OVF Toolkit Supporting Inter-Cloud Application Splitting
    Anastasi, Gaetano F.
    Carlini, Emanuele
    Coppola, Massimo
    Dazzi, Patrizio
    Distefano, Marco
    2014 IEEE 3RD INTERNATIONAL CONFERENCE ON CLOUD NETWORKING (CLOUDNET), 2014, : 96 - 101
  • [7] Performance Analysis of Cloud-Based Application
    Budai, Peter
    Goldschmidt, Balazs
    LARGE-SCALE SCIENTIFIC COMPUTING, LSSC 2013, 2014, 8353 : 476 - 483
  • [8] Improving HPC Application Performance in Public Cloud
    Hassani, Rashid
    Aiatullah, Md
    Luksch, Peter
    INTERNATIONAL CONFERENCE ON FUTURE INFORMATION ENGINEERING (FIE 2014), 2014, 10 : 169 - 176
  • [9] Experimental Study on Performance and Energy Consumption of Hadoop in Cloud Environments
    Jlassi, Aymen
    Martineau, Patrick
    CLOUD COMPUTING AND SERVICES SCIENCE, CLOSER 2016, 2017, 740 : 254 - 271
  • [10] A Study of the Performance of a Cloud Datacenter Server
    Mershad, Khaleel
    Artail, Hassan
    Saghir, Mazen A. R.
    Hajj, Hazem
    Awad, Mariette
    IEEE TRANSACTIONS ON CLOUD COMPUTING, 2017, 5 (04) : 590 - 603