Beel - Music Streaming Platform
Comprehensive music streaming service built with microservices architecture, consisting of 9 independent services for catalog management, user authentication, streaming, playlists, payments, and notifications.
Key Highlights
- ▹ Architected 9 independent microservices with event-driven RabbitMQ communication
- ▹ Led backend team with 2 junior developers, making architectural decisions
- ▹ Built complete authentication system with JWT, LDAP integration, and multi-device session management
- ▹ Implemented efficient audio streaming with range request support and MinIO object storage
- ▹ Established comprehensive test suites with pytest-asyncio and GitLab CI pipelines
Tech Stack
Overview
Beel is a comprehensive music streaming service that I led as the backend developer. The platform handles catalog management, user authentication, audio streaming, playlist management, payments, and notifications through a microservices architecture.
Leadership Experience
As Lead Backend Developer, I had several developers reporting directly to me. My responsibilities included:
- Planning work for the backend team
- Making most architectural decisions for the project
- Mentoring 2 junior developers through code reviews and pair programming sessions
Key Leadership Lesson: One developer initially ignored advice and preferred doing things their own way. I adapted my approach by sitting down to demonstrate the reasoning through practical examples. The key insight: show, don’t just tell - practical demonstrations are more effective than verbal advice alone.
Technical Highlights
Microservices Architecture
Implemented 9 independent, loosely-coupled microservices with event-driven RabbitMQ communication handling 30,000 monthly active users.
User Management
Built full authentication system with JWT tokens, LDAP integration, multi-device session management, and role-based access control.
Music Catalog System
Developed complete catalog management with search functionality, favorites, and many-to-many relationships for songs, artists, albums, and genres.
Playlist Engine
Created dynamic playlist management with user playlists, system playlists, top charts, trending calculations, and Celery-based background tasks.
Streaming Service
Implemented efficient audio streaming with range request support, MinIO object storage integration, and stream analytics.
Quality & Testing
Established comprehensive test suites with pytest-asyncio, GitLab CI pipelines with automated linting, SonarQube integration, and Grafana + Loki monitoring.
Contribution Breakdown
- User Management: 236 commits
- Playlists Service: 148 commits
- Catalog Service: 84 commits
- Streaming Service: 47 commits