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Founded in Fall 2024, the AWS Cloud Club at Florida State University bridges computer science fundamentals and real-world applications, currently empowering a growing community of 50 members. The club’s mission is to broaden access to cloud education by providing FSU students with the technical knowledge required to navigate modern AWS environments.
This semester, the organization launched a new initiative designed to immerse students in professional software engineering workflows, modern technologies, and the ecosystem of Amazon Web Services. The AWS Cloud Club encourages high-level collaboration and technical rigor, leaving members proficient in coding and also prepared for the collaborative demands of the global workforce.
The semester culminated in a nine-week project that mirrored a professional production environment and the development of SmartGallery, a serverless image recognition and management web application. Orchestrated by seven Project Managers and 40 developers, spanning many different majors, divided into 5 teams. The development was driven by a series of technical milestones, including three meetings and a final demonstration. By utilizing GitHub for version control and task-based issue tracking, the project provided a hands-on experience for students to explore automated deployment and scalable architecture.
For this project, we focused on cost-effective, serverless solutions for media management. This project demonstrates how serverless technology can reduce overhead and increase accessibility for small-scale applications. The goal of this project was to transform the student experience, turning academic curiosity into tangible career capital. By mastering AWS services and enterprise-grade software engineering practices, our members graduate as ready-to-hire professionals capable of solving complex, real-world problems.
SmartGallery operates as an intelligent photo gallery. When a user uploads an image, the system triggers an automated process that leverages cloud-based computer vision to generate descriptive tags to be stored in a database. Users can subsequently view their entire collection on a gallery page and utilize these AI-generated tags to filter and locate specific images instantaneously.
While built as an educational milestone for FSU students, the logic behind the application is highly versatile. It can be used as a:
- Personal Photo Manager: For individuals needing to organize large volumes of personal photos without manual tagging.
- Educational Template: For aspiring cloud engineers to study event-driven architecture and AWS service integration.
- Searchable Archive: For small organizations or hobbyist groups that require a categorized repository of visual data.
To mirror enterprise-grade standards, the project adheres to the Principle of Least Privilege (PoLP). We utilize specific IAM Roles to ensure that each component only possesses the exact permissions required to perform its task, preventing unauthorized access across the stack. Additionally, all user assets are stored in Private S3 Buckets, ensuring that image data is never exposed to the public internet and is only accessible through authenticated application logic.