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Evaluated the cost-effectiveness of IaaS and PaaS by assessing setup costs, operational expenses, scalability, and deployment complexities. Deployed a recruiting system on AWS, Azure, Heroku, and GCP, and conducted performance tests with Locust. Findings guide businesses on choosing between IaaS and PaaS for optimal cloud deployment.

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Assessing Cloud Cost Effectiveness: A Comparative Analysis of IaaS and PaaS in Cloud Computing

Abstract

Cloud computing has become an integral part of modern Information Technology (IT) infrastructure, offering cost-effective and scalable solutions to businesses and organizations of all sizes. As reliance on cloud services grows, understanding the cost-effectiveness of different deployment models is crucial. This thesis project investigates the cost-effectiveness of two prominent cloud service models: Infrastructure as a Service (IaaS) and Platform as a Service (PaaS), with a specific focus on deployment complexities as a critical parameter.

The research involves a comprehensive comparative analysis of cost factors associated with IaaS and PaaS deployment models, including initial setup costs, operational expenses, scalability, resource utilization efficiency, and deployment complexities. The methodology encompasses data collection, analysis, and a case study involving the deployment of a recruiting system on various cloud platforms, followed by load tests to evaluate performance.

By assessing the cost-effectiveness of IaaS and PaaS through a real-world case study, this research aims to inform decision-making processes to maximize cost efficiency while achieving business objectives. The findings indicate that IaaS provides greater control over infrastructure, while PaaS emphasizes ease of development, reducing the need for infrastructure management. The choice between IaaS and PaaS depends on available resources, expertise, and preference for control versus simplicity. This thesis offers valuable insights into cloud computing and recommends appropriate models for various circumstances.

The research builds on existing knowledge of cloud computing and deployment strategies, following a structured approach that combines insights into cloud computing models with a thorough review of current pricing structures, without proposing new solutions.

Keywords

Cloud Computing, Infrastructure as a Service (IaaS), Platform as a Service (PaaS), Deployment Complexities, Pricing Models, Scalability, Virtualization, Resource Management, Performance Optimization, Cost effectiveness, Cloud Service Providers, Load Testing, Data Analytics.

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Evaluated the cost-effectiveness of IaaS and PaaS by assessing setup costs, operational expenses, scalability, and deployment complexities. Deployed a recruiting system on AWS, Azure, Heroku, and GCP, and conducted performance tests with Locust. Findings guide businesses on choosing between IaaS and PaaS for optimal cloud deployment.

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