Improving FinOps Procedures with Automation Tools and Framework Changes for a Cloud Environment

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master_Burke_Daniel_2024.pdf (1.37 MB)

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School of Electrical Engineering | Master's thesis
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Date

2024-09-27

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Major/Subject

Cloud and Network Infrastructures

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Degree programme

Master's Programme in ICT Innovation

Language

en

Pages

92

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Abstract

As organizations increasingly adopt cloud services, managing cloud expenditures effectively has become a critical challenge. The discipline of FinOps has emerged to address these challenges by promoting collaboration between financial, operational, and engineering teams to optimize cloud spending. However, as cloud environments grow in complexity, traditional FinOps practices are often insufficient, leading to significant resource waste and inefficiencies. This research investigates how the integration of automation tools and framework changes can improve FinOps processes, enhancing cost management, resource allocation, and financial governance to cloud environments. Based on qualitative and quantitative research analysis and interviews, a FinOps automation tool was developed to address key inefficiencies, focusing on real-time resource tracking, automated cost allocation, and proactive decommissioning of underutilized resources. The system was designed to reduce cloud waste, improve accountability, and optimize resource utilization across cloud environments. The thesis explores how automation can significantly improve the efficiency and effectiveness of FinOps processes. By integrating automation into existing frameworks, organizations can achieve greater cost savings, reduce manual overhead, and better manage their cloud investments. This research provides a practical roadmap for FinOps teams seeking to enhance their cloud financial operations through the strategic use of automation.

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Supervisor

Manner, Jukka

Thesis advisor

Hart, Robert
Ilici, Georgiana

Keywords

FinOps, automation, cloud computing, cloud environment, operational efficiency, framework integration

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https://urn.fi/URN:NBN:fi:aalto-202411217270

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[dipl] Sähkötekniikan korkeakoulu / ELEC