Scalable Infrastructure for Ed-Tech Platforms: A Serverless Approach using Firebase for the C2C System

Abstract

The increasing demand for digitized career guidance in higher education has exposed significant limitations in traditional, server-dependent ed-tech platforms — including high infrastructure costs, poor scalability, and prohibitive maintenance overhead. Existing career guidance systems frequently fail to adapt to fluctuating user loads, particularly during peak periods such as placement seasons or academic year transitions.

This paper presents Code to Career (C2C), a career guidance and skill-building platform for students that addresses these limitations through a fully serverless architecture powered by Google Firebase. C2C eliminates the need for dedicated backend server management by leveraging Firebase's Backend-as-a-Service (BaaS) capabilities — specifically Cloud Firestore for real-time NoSQL data persistence and Firebase Authentication for secure identity management. The platform is developed using HTML, CSS, and vanilla JavaScript on the frontend, with Cloudinary integrated for media and file storage. The entire system operates with zero server-side provisioning.

The serverless model enables C2C to scale automatically from a single user to thousands of concurrent users without manual intervention, while maintaining sub-second response times and significantly reducing operational expenditure. This paper details the system architecture, event- driven data flow, and a comparative evaluation of serverless versus traditional monolithic deployment strategies. Results demonstrate that the Firebase-based serverless approach reduces deployment time by over 80% and eliminates recurring server maintenance costs, making it a viable and superior infrastructure model for resource-constrained ed-tech projects.