Performance prediction for burstable cloud resources

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Title: Performance prediction for burstable cloud resources
Authors: Dubois, DJ
Casale, G
Item Type: Conference Paper
Abstract: We propose ForeBurst, an open source tool for performance prediction for complex cloud-based applications. ForeBurst leverages queueing network models for predicting performance metrics such as resource utilizations, request response times, and credit usage in burstable resources, such as the Amazon EC2 T-family instances.
Issue Date: 26-Oct-2016
Date of Acceptance: 5-Sep-2016
Publisher: ACM
Copyright Statement: © 2016 ACM. This paper is embargoed until publication.
Sponsor/Funder: Commission of the European Communities
Commission of the European Communities
Funder's Grant Number: PIEF-GA-2013-629982
Conference Name: 10th EAI International Conference on Performance Evaluation Methodologies and Tools
Publication Status: Accepted
Start Date: 2016-10-26
Finish Date: 2016-10-28
Conference Place: Taormina, Italy
Embargo Date: publication subject to indefinite embargo
Appears in Collections:Faculty of Engineering

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