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Quantifying Change Risk in Cloud Computing Environments.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Quantifying Change Risk in Cloud Computing Environments./
作者:	Alfred, Andre O.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2022,
面頁冊數:	132 p.
附註:	Source: Dissertations Abstracts International, Volume: 83-06, Section: B.
Contained By:	Dissertations Abstracts International83-06B.
標題:	Information technology. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28864343
ISBN:	9798759946373

Quantifying Change Risk in Cloud Computing Environments.
Alfred, Andre O.

Quantifying Change Risk in Cloud Computing Environments. - Ann Arbor : ProQuest Dissertations & Theses, 2022 - 132 p.

Source: Dissertations Abstracts International, Volume: 83-06, Section: B.

Thesis (D.Engr.)--The George Washington University, 2022.

This item must not be sold to any third party vendors.

This research introduces a System Dynamics model that engineers can use to simulate the expected value of economic damage to cloud customers if a change fails. As cloud adoption rapidly increases, the revenue loss potential of cloud customers due to human error can be significant. The model's parameters enables an engineer to incorporate a quantitatively derived worst-case impact from the customer's perspective. Typical technical change management processes in organizations are qualitative technical judgments of risk and implications based on the engineer's knowledge of making the change. It is unlikely that the engineer working on infrastructure components has any visibility of the change's economic risk. The practical application of this model focuses on simulating the probability of technical human errors relating to the compute portion of a typical cloud architecture. Engineers can quickly adapt the model for any layer of the cloud and any class of errors. .

ISBN: 9798759946373Subjects--Topical Terms:

532993
Information technology.
Subjects--Index Terms:

Worst-case impact

Quantifying Change Risk in Cloud Computing Environments.
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502 $a Thesis (D.Engr.)--The George Washington University, 2022.
506 $a This item must not be sold to any third party vendors.
520 $a This research introduces a System Dynamics model that engineers can use to simulate the expected value of economic damage to cloud customers if a change fails. As cloud adoption rapidly increases, the revenue loss potential of cloud customers due to human error can be significant. The model's parameters enables an engineer to incorporate a quantitatively derived worst-case impact from the customer's perspective. Typical technical change management processes in organizations are qualitative technical judgments of risk and implications based on the engineer's knowledge of making the change. It is unlikely that the engineer working on infrastructure components has any visibility of the change's economic risk. The practical application of this model focuses on simulating the probability of technical human errors relating to the compute portion of a typical cloud architecture. Engineers can quickly adapt the model for any layer of the cloud and any class of errors. .
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650 4 $a Industrial engineering. $3 526216
650 4 $a Systems science. $3 3168411
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653 $a Economic damage
653 $a Cloud architecture
653 $a Change management
653 $a Human error
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690 $a 0546
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