Cloud Computing Pricing and Deployment Efforts

Navigating Cloud Computing Pricing and Deployment Efforts: Exploring the Public-Private Landscape

Abstract

The expanding adoption of cloud computing services by businesses has transformed IT infrastructure and data management in the computing space. Cloud computing offers advantages such as availability, scalability, and costeffectiveness, making it a favored choice for businesses of all sizes. The aim of this thesis is to compare private and public cloud computing services in terms of pricing and implementation effort as well as comparing the cloud providers to each other. The top three cloud providers that will be examined are Google GCP, Microsoft Azure, and Amazon AWS. The study examines different pricing models and evaluates their effectiveness in different business scenarios. In addition, the thesis also discusses the challenges associated with building and maintaining private infrastructure and the deployment of applications to cloud computing service are examined. The research methodology involves data collection, analysis, and a case study of developing and deploying a ticketing system application on different cloud platforms. The ticket system helps to provide a realistic example and investigation of the cloud providers. The findings will help companies make informed decisions regarding the selection of the most appropriate cloud computing service based on pricing models and implementation efforts. The thesis provides valuable information on private and public cloud computing and recommends appropriate pricing models for different scenarios. This study adds to existing knowledge by analyzing current pricing models and deployment concepts in cloud computing. The thesis does not propose new solutions but follows a structured format compiling information on private, and public cloud computing and a comprehensive review of cloud computing pricing models and marketing efforts.

Key Achievements

1. Conducted in-depth analysis: Conducted thorough research and data collection on private and public cloud computing services, examining pricing models and deployment strategies.

2. Case study development: Developed and executed a case study involving developing and deploying a ticketing system application. The case study was deployed across cloud platforms, including Amazon AWS, Google GCP, and Microsoft Azure. This practical approach provided valuable insights into the capabilities and effectiveness of each cloud provider and gave real-world data.

3. Data analysis and recommendations: Analyzed the collected data, pricing models, and implementation efforts to compare the performance and suitability of the cloud providers. Based on the findings, they provided practical recommendations to help businesses make informed decisions when selecting the most appropriate cloud computing service based on pricing models and implementation efforts.

Keywords

Cloud computing, Private cloud, Public cloud, Cloud computing services, Cost-effectiveness, Implementation effort, Google GCP, Microsoft Azure, Amazon AWS, Pricing models, Cloud adoption, Cloud cost management, Cloud migration, Instance computing, Serverless computing, Data storage