DocumentCode :
3650302
Title :
Cloud Incident Data: An Empirical Analysis
Author :
Lance Fiondella;Swapna S. Gokhale;Veena B. Mendiratta
Author_Institution :
Univ. of Connecticut, Storrs, CT, USA
fYear :
2013
fDate :
3/1/2013 12:00:00 AM
Firstpage :
241
Lastpage :
249
Abstract :
This paper presents an empirical analysis of cloud incidents reported in the Cloutage.org database. The trend, causes, and impact of three types of incidents, namely, Outage, Vulnerability, and, failure during automatic updates (Auto Fail) were examined. Service availability was also analyzed based on the outage duration data. The analysis suggested that: (i) Outages and Vulnerabilities grow exponentially, while Auto Fail incidents show only a linear increase, (ii) Outages are caused by various sources of failures, Vulnerabilities primarily due to the lack of filtering inputs and most Auto Fail incidents are false positives, (iii) Many outages affected multiple, related services, some cascaded into additional ones during resolution, and the impact of some transcended organizational boundaries, and (iv) Availability of cloud services is less than 99%, and for free services such as Email it could be as low as 84%. The paper concludes with a summary of key observations and offers recommendations along three dimensions to avoid and alleviate the impact of cloud incidents.
Keywords :
"Organizations","Polynomials","Google","Mathematical model","Market research","Computer hacking","Analytical models"
Publisher :
ieee
Conference_Titel :
Cloud Engineering (IC2E), 2013 IEEE International Conference on
Print_ISBN :
978-1-4673-6473-7
Type :
conf
DOI :
10.1109/IC2E.2013.28
Filename :
6529290
Link To Document :
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