Multi-Cloud Deployment and Performance Benchmarking of a Dockerized Fake News Detection Application

Jawahar, Roshan (2024) Multi-Cloud Deployment and Performance Benchmarking of a Dockerized Fake News Detection Application. Masters thesis, Dublin, National College of Ireland.

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Abstract

This Research project aims to address a prevalent issue of identifying any fabricated information being shared online to curb the widespread of any false information being shared online. To achieve this, a robust fake news classification application is developed using flask framework with an underlying advanced Machine learning model such as Hybrid Ensemble Classifier to analyse the textual news data and distinguish them as genuine or fake. A Docker image is created for this application along with its dependencies such as Flask, packed in the required format for improving scalability and simplifying deployment across various platforms for ease of access. The Application is tested with high concurrency loads generated by Locust and to combat any performance issues for dynamically scaling the computational resources based on demand. For this reason, it is essential that the metrics are collected and studied in detail. This project utilizes AWS CloudWatch and Azure Monitor cloud tools to collect different metrics of the application under study to organize a performance evaluation between AWS and Microsoft Azure to assess the application’s efficiency. This comparison is essential in aiding the decision that would have to be taken when choosing wither of these cloud platforms for a Dockerized application deployment of similar magnitude.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Siddiq, Abubakr 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 Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4150 Computer Network Resources > The Internet > World Wide Web > Websites > Online social networks T Technology > TK Electrical engineering. Electronics. Nuclear engineering > Telecommunications > The Internet > World Wide Web > Websites > Online social networks
Divisions:	School of Computing > Master of Science in Cloud Computing
Depositing User:	Ciara O'Brien
Date Deposited:	15 Jul 2025 11:43
Last Modified:	15 Jul 2025 11:43
URI:	https://norma.ncirl.ie/id/eprint/8107

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