Title :
K-Feed - A Data-Oriented Approach to Application Performance Management in Cloud
Author :
Zareian, Saeed ; Veleda, Rodrigo ; Litoiu, Marin ; Shtern, Mark ; Ghanbari, Hamoun ; Garg, Manish
Author_Institution :
Sch. of Inf. Technol., York Univ., York, UK
Abstract :
This paper presents K-Feed (Knowledge Feed), a platform for real-time application performance analysis and provisioning in the cloud. K-Feed can perform at scale monitoring, analysis, and provisioning of cloud applications. We explain the components, the implementation and the validation of the K-feed platform. To illustrate its feasibility, we use it to monitor and build a performance model of a clustered web application. To model the application, we use off the shelf components.
Keywords :
cloud computing; software performance evaluation; K-feed platform; clustered Web application; data-oriented approach; knowledge feed; performance management; real-time application performance analysis; Cloud computing; Computational modeling; Conferences; Measurement; Monitoring; Neural networks; Virtual machining; applications; classification; cloud; monitoring; prediction;
Conference_Titel :
Cloud Computing (CLOUD), 2015 IEEE 8th International Conference on
Conference_Location :
New York City, NY
Print_ISBN :
978-1-4673-7286-2
DOI :
10.1109/CLOUD.2015.148
