Cloud service analytics

Although Cloud Computing has been around for several years, only in recent years has its popularity risen globally. Amazon web services’ Elastic Cloud Compute (EC2) is one such service that has increased in its popularity, because of its ease of use and relatively cheap pricing. As with all...

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Main Author: Koo, Joel Chong En.
Other Authors: Chan Chee Keong
Format: Final Year Project
Language:English
Published: 2013
Subjects:
Online Access:http://hdl.handle.net/10356/54404
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-544042023-07-07T17:01:29Z Cloud service analytics Koo, Joel Chong En. Chan Chee Keong School of Electrical and Electronic Engineering A*STAR Institute for Infocomm Research DRNTU::Engineering::Computer science and engineering::Information systems::Information interfaces and presentation DRNTU::Engineering::Electrical and electronic engineering Although Cloud Computing has been around for several years, only in recent years has its popularity risen globally. Amazon web services’ Elastic Cloud Compute (EC2) is one such service that has increased in its popularity, because of its ease of use and relatively cheap pricing. As with all services, Price and Performance are directly proportional to each other. As price increases, so does the performance. This dynamic relationship is even more apparent in EC2’s Spot Instances. Accordingly, how much money should be invested in to Cloud Services to achieve maximum performance? The primary objective of this project is to find methods to obtain the Spot Instance Prices and explore methods to advise EC2 Spot Instance users of the appropriate amount of money to invest. With the use of Google Chart Tools, a GUI was developed during this project to represent Spot Price information and advice users of optimum bids to ensure maximum performance from the services they are purchasing. Bachelor of Engineering 2013-06-20T01:51:11Z 2013-06-20T01:51:11Z 2013 2013 Final Year Project (FYP) http://hdl.handle.net/10356/54404 en Nanyang Technological University 66 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Computer science and engineering::Information systems::Information interfaces and presentation
DRNTU::Engineering::Electrical and electronic engineering
spellingShingle DRNTU::Engineering::Computer science and engineering::Information systems::Information interfaces and presentation
DRNTU::Engineering::Electrical and electronic engineering
Koo, Joel Chong En.
Cloud service analytics
description Although Cloud Computing has been around for several years, only in recent years has its popularity risen globally. Amazon web services’ Elastic Cloud Compute (EC2) is one such service that has increased in its popularity, because of its ease of use and relatively cheap pricing. As with all services, Price and Performance are directly proportional to each other. As price increases, so does the performance. This dynamic relationship is even more apparent in EC2’s Spot Instances. Accordingly, how much money should be invested in to Cloud Services to achieve maximum performance? The primary objective of this project is to find methods to obtain the Spot Instance Prices and explore methods to advise EC2 Spot Instance users of the appropriate amount of money to invest. With the use of Google Chart Tools, a GUI was developed during this project to represent Spot Price information and advice users of optimum bids to ensure maximum performance from the services they are purchasing.
author2 Chan Chee Keong
author_facet Chan Chee Keong
Koo, Joel Chong En.
format Final Year Project
author Koo, Joel Chong En.
author_sort Koo, Joel Chong En.
title Cloud service analytics
title_short Cloud service analytics
title_full Cloud service analytics
title_fullStr Cloud service analytics
title_full_unstemmed Cloud service analytics
title_sort cloud service analytics
publishDate 2013
url http://hdl.handle.net/10356/54404
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