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Solanki, Anuja Mahendrasingh (2024) Automated Drift Detection and Remediation in Infrastructure-as-Code (IaC) Deployments. Masters thesis, Dublin, National College of Ireland.
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Abstract
This study looks into the fundamental problem of infrastructure drift in Infrastructure-as-Code (IaC) controlled cloud settings, with a focus on Amazon Web Services CloudFormation. IaC is becoming more and more important for reliable and consistent infrastructure provisioning. Drift detection has become a major issue that affects security, compliance, and organizational stability. The study uses AWS Lambda to automatically find drift across three different CloudFormation stacks. The goal is to quickly find and fix deviations from stated infrastructure states. The project combines more than just CloudFormation and Lambda to provide a complete setting for handling and controlling how infrastructure is aligned. This study looks into automated rollback and setting synchronization as ways to fix problems. It helps to improve IaC practices and keep cloud resources safe, legal, and useful.
| Item Type: | Thesis (Masters) |
|---|---|
| Supervisors: | Name Email Heeney, Sean UNSPECIFIED |
| 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 > Computer software > Computer Security T Technology > T Technology (General) > Information Technology > Computer software > Computer Security |
| Divisions: | School of Computing > Master of Science in Cloud Computing |
| Depositing User: | Ciara O'Brien |
| Date Deposited: | 03 Jun 2025 14:28 |
| Last Modified: | 03 Jun 2025 14:28 |
| URI: | https://norma.ncirl.ie/id/eprint/7730 |
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