Date of Award

3-2025

Document Type

Thesis

Degree Name

Master of Science in Cost Analysis

Department

Department of Systems Engineering and Management

First Advisor

Brandon M. Lucas, PhD

Abstract

As modern warfare evolves with rapid technological advancements, cloud computing plays a critical role in managing the vast amounts of data required for real-time decision making, as well as enabling seamless organizational access to mission-critical programs and information from around the globe. Recognizing its importance, the Department of Defense (DoD) identified cloud computing as essential for maintaining the military’s technological edge. However, despite cloud computing’s strategic significance, the DoD faces challenges in successfully implementing department-wide cloud computing. In contrast, the Air Force’s cloud computing environment, Cloud One, is fully operational and has already integrated over 145 systems into its platform. Previous research related to Cloud One has generated some qualitative insights into potential problems and areas of improvement, but quantitative insights have proven difficult. This study aimed to use Source Lines of Code (SLOC) related variables to change this. Our research strongly suggests that Cloud One systems take longer than planned to migrate. Furthermore, efforts should focus on reducing schedule deviations in the Build Refactor phase in absolute terms of schedule deviation, while in relative terms of schedule deviation, it should be the Deploying to Production phase. The four major migration parameters of Organization, Impact Level (IL), Cloud Service Provider (CSP), and Migration as a Service (MaaS), had no significant impact on total schedule duration. A new variable, the Dominant Language Percentage, was created as a proxy for complexity, and was defined as the percentage of total SLOC written in the most used programming language within the given system. Subsequently, it was shown to be a consistent predictor of migration duration. Lastly, the duration of the first phase, Build Refactor, was shown to be a significant predictor of overall migration duration, potentially serving as a useful midpoint estimate of a program’s total duration during its migration process.

AFIT Designator

AFIT-ENV-MS-25-M-075

Comments

An embargo was observed for this posting.

Distribution A: Approved for public release, Distribution Unlimited. PA case number 88ABW-2025-0368

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