• 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