System-driven Interactive Design Support for Cloud Architecture: A Qualitative User Experience Study with Novice Engineers

TL;DR

This study explores how system-driven guidance tools assist novice engineers in cloud architecture design, improving engagement, understanding, and decision-making, with insights into benefits and areas for enhancement.

Contribution

It provides qualitative evidence on the effectiveness of structured, proactive system guidance in supporting novices during cloud architecture design.

Findings

System guidance improves novice engagement and task completion.

Simulation and comparison features deepen understanding of trade-offs.

Participants see educational and practical value in system-driven support.

Abstract

Cloud architecture design presents significant challenges due to the necessity of clarifying ambiguous requirements and systematically addressing complex trade-offs, especially for novice engineers with limited cloud experience. While recent advances in the use of AI tools have broadened available options, system-driven approaches that offer explicit guidance and step-by-step information management may be especially effective in supporting novices during the design process. This study qualitatively examines the experiences of 60 novice engineers using such a system-driven cloud design support tool. The findings indicate that structured and proactive system guidance helps novices engage more effectively in architectural design, especially when addressing tasks where knowledge and experience gaps are most critical. For example, participants found it easier to create initial architectures and did not need to craft prompts themselves. In addition, participants reported that the ability to simulate and compare multiple architecture options enabled them to deepen their understanding of cloud design principles and trade-offs, demonstrating the educational value of system-driven support. The study also identifies areas for improvement, including more adaptive information delivery tailored to user expertise, mechanisms for validating system outputs, and better integration with implementation workflows such as infrastructure-as-code generation and deployment guidance. Addressing these aspects can further enhance the educational and practical value of system-driven support tools for cloud architecture design.