How Gradoo Migrated From a Legacy App to a Scalable Django Backend

Gradoo serves the education and graduation services market - a space where user inquiries spike predictably around graduation season and support quality directly impacts customer satisfaction. Their support team handles thousands of tickets each cycle, answering questions about yearbook orders, delivery timelines, and account issues.

The problem was their backend. Built years earlier as a monolithic application, the legacy system was slow to query, difficult to maintain, and impossible to extend. Support agents couldn't search ticket history efficiently. Loading a user's profile took multiple seconds. Adding new features required navigating a codebase that few developers understood.

As Gradoo's user base grew, the legacy system's limitations became operational risks. During peak graduation periods, ticket volume surged and the backend couldn't keep up. Response times increased. The support team spent more time fighting the tool than helping users. And Gradoo's own mobile development team - building the customer-facing app in React Native - needed a backend API that was fast, documented, and reliable.

Gradoo needed a complete backend migration: a modern, scalable platform that could handle growing ticket volumes, power fast search across user data, and provide clean API endpoints for the mobile app.

Gradoo evaluated the migration options carefully. They could rebuild the backend in-house, but their engineering team was focused on the mobile app and couldn't absorb a backend rewrite. They needed an external partner with Python and Django expertise, experience building support-focused backends, and the ability to integrate with a React Native mobile application.

easy.bi's team brought production experience with Django, ElasticSearch, and API-driven architectures. The team's approach - building the backend as a service layer that the mobile app consumed via clean APIs - aligned with Gradoo's architecture. And easy.bi's track record with search-heavy applications meant ElasticSearch integration was a proven capability, not an experiment.

easy.bi focused the migration on one principle: every design decision should make the support team faster. The backend wasn't a generic platform - it was purpose-built for support operations.

Django backend with clean API layer. The new backend was built using Python and Django, chosen for their maturity, developer ecosystem, and suitability for data-heavy applications. Every feature was exposed through well-documented REST APIs that Gradoo's mobile team consumed directly. The architecture separated concerns cleanly: the backend handled data, business logic, and search. The mobile app handled user experience.

ElasticSearch for instant ticket and user lookup. The legacy system's biggest bottleneck was search. Finding a user's ticket history required database queries that took seconds. ElasticSearch replaced those queries with sub-second full-text search across tickets, user profiles, and order data. Support agents could type a name, order number, or keyword and see results instantly.

Integration support for the React Native mobile app. While Gradoo's team built the mobile application entirely in-house, easy.bi ensured the backend APIs met the mobile app's performance and data requirements. Endpoints were optimized for mobile consumption - returning only the data the app needed, in the format it expected, with response times that worked on cellular connections.

Migration without disruption. The migration from legacy to Django happened incrementally. Data was migrated in stages, with validation checks at each step. The support team transitioned to the new backend over a controlled period, with both systems running in parallel until the new platform was fully validated.