DeenQuest

Tech Stack
Overview
Problem Solved
Solution
Workflow
- Registration: Users create profiles and select their learning track
- Learning Paths: Browse structured courses divided into bite-sized lessons
- Quizzes & Challenges: Test knowledge through interactive quizzes with instant feedback
- Gamification: Earn XP, unlock badges, and climb the global leaderboard
- Progress Sync: Learning state is persisted across devices via the backend
- Admin Oversight: Content moderators manage lessons, review reports, and analyze engagement
- Personalization: ML-driven recommendations suggest the next best lesson based on performance
Technical Highlights
- Architecture: Go microservices with API Gateway pattern for routing and auth
- Communication: REST APIs for service interaction, Kafka for event-driven async messaging
- Events: Apache Kafka for reliable inter-service event streaming
- Caching: Redis for leaderboards, sessions, and frequently accessed content
- Database: MongoDB for flexible document storage of user profiles and lessons
- DevOps: Fully Dockerized with Docker Compose for reproducible environments
Key Takeaways
Features
Gamified learning paths with XP and badges
Microservices architecture for scalability
Real-time leaderboards with Redis caching
Event-driven messaging with Apache Kafka
Admin panel for content and user management
Progress tracking and personalized recommendations
Dockerized services for consistent environments
Architecture
DeenQuest is built on a microservices architecture. The API Gateway routes requests to domain-specific services (Auth, Content, Gamification, Progress). Each service is a Go binary exposing REST APIs, with asynchronous inter-service communication handled by Apache Kafka. Redis caches leaderboards and sessions. MongoDB stores user data and content. Docker Compose orchestrates local development.
API & System Flow
Client requests hit the API Gateway → Gateway authenticates via Auth Service (JWT) → Routes to appropriate microservice → Services publish domain events to Kafka → Other services consume events to update their read models → Redis caches hot data → MongoDB persists authoritative state.
Challenges & Solutions
Implemented an event-sourcing pattern with Kafka as the event bus, ensuring eventual consistency and audit trails for all state changes.
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