Auto-recovery and continuous disaster tolerance in Amazon Web Services instance using Autodeployer script automation tool

Pittandavida, Shinoj (2019) Auto-recovery and continuous disaster tolerance in Amazon Web Services instance using Autodeployer script automation tool. Masters thesis, Dublin, National College of Ireland.

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Abstract

As Cloud computing has evolved to a new level, every organization needs to adopt the changes to support the new technology and design an infrastructure that supports fault tolerance. Any organization uses virtualization technology for their infrastructure should develop a feature to support the reliable, fault-tolerant and high-available resources. We propose a new model named Autodeployer, to mitigate the failures of Amazon Web Services (AWS) Elastic Cloud Compute (EC2) instances with a batch process to reduce the launch time. The Autodeployer will help to recover the failed instances in seconds. The available tools in the market are either limited with instance creation or batch process and do not support auto-recovery for the batch of EC2 instances. They require additional licenses and more domain knowledge for the automation. Our approach is based on the Application Programming Interface (API) iteration process which greatly reduces the time of the manual process. This process is different from the method being used by AWS CloudWatch technic and saves more space for additional log files. The proposed Autodeployer model can make the batch process with failure recovery with 70 to 85 percent faster than the other services. It can optimize the additional time and effort needed to configure a large number of instances at once and loss of service availability issues. In this paper, we present the solution for mitigating the failures in the batch EC2 instance with auto recovery.

Item Type:	Thesis (Masters)
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Cloud computing Q Science > QA Mathematics > Electronic computers. Computer science > Computer Systems T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science > Computer Systems Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4150 Computer Network Resources > The Internet T Technology > TK Electrical engineering. Electronics. Nuclear engineering > Telecommunications > The Internet
Divisions:	School of Computing > Master of Science in Cloud Computing
Depositing User:	Dan English
Date Deposited:	04 Jun 2020 12:54
Last Modified:	04 Jun 2020 12:54
URI:	https://norma.ncirl.ie/id/eprint/4247

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