System Architecture Diagram
Backend Engineering • REST API • System Architecture
A scalable backend platform for tournament management built with FastAPI, designed around clean architecture, modular services, and RESTful APIs.
This project is a pure backend engineering effort — an API-first tournament management platform built with FastAPI. It serves as the foundational layer responsible for authentication, tournament orchestration, player registration, real-time statistics computation, and all business logic, while remaining completely independent of any frontend implementation.
The architecture prioritizes clean separation of concerns, maintainability, and scalability through a layered design: API routers handle HTTP concerns, service modules encapsulate business rules, and SQLAlchemy models abstract database interactions. This modular approach ensures the backend can evolve independently and integrate seamlessly with web, mobile, or third-party clients.
Design endpoints that handle complex tournament logic efficiently.
Routers, services, models, and schemas each have distinct responsibilities.
Encapsulate tournament and match logic for use across multiple endpoints.
Organize endpoints by domain for clarity and independent development.
JWT-based auth with role validation and refresh token support.
Frontend-agnostic design allowing any client to consume the API.
The backend follows a layered architecture with clear boundaries between the presentation, business logic, and data access layers. API routers handle HTTP requests and delegate to service modules, which contain all business rules. SQLAlchemy models define the database schema, while Pydantic schemas validate incoming and outgoing data.
Dependency injection is used extensively — database sessions, current user context, and configuration are injected into route handlers, keeping code testable and decoupled. Background tasks handle asynchronous operations like statistics recalculation.
Presentation → Business Logic → Data Access layers
Routers, services, models, schemas organization
Module dependencies and injection flow
HTTP request → middleware → router → service → database
The API follows REST conventions with resource-based endpoints, consistent JSON responses, and proper HTTP status codes. All endpoints are documented automatically via OpenAPI (Swagger) using FastAPI's built-in support. Request and response validation is handled by Pydantic schemas, ensuring data integrity at the API boundary.
Standardized envelope with status, data, and error fields across all endpoints.
Cursor and offset-based pagination with query parameter filtering.
Global exception handlers return structured error responses with actionable messages.
Swagger UI and ReDoc generated from Pydantic schemas and route decorators.
The database uses PostgreSQL with a normalized relational schema. SQLAlchemy ORM models map Python classes to database tables, while Alembic handles schema migrations with version control. Foreign keys, unique constraints, and indexes are applied thoughtfully to maintain data integrity and query performance.
Tournaments, players, matches, and statistics relationships
Alembic revision history and upgrade/downgrade paths
Table definitions, constraints, and index strategy
Foreign key connections across domain models
JWT issuance, refresh, and role validation.
Registration, profiles, and tournament history.
Team creation, roster management, and statistics.
Creation, format configuration, and lifecycle.
Scheduling, scoring, and state management.
Aggregation, rankings, and performance analytics.
Event-driven alerts for match updates.
Role-based access for organizers and players.
FastAPI was selected for its native async support, automatic OpenAPI documentation via Pydantic, and excellent performance. Its dependency injection system enables clean, testable code by decoupling route handlers from infrastructure concerns like database sessions.
SQLAlchemy provides a mature ORM with both high-level and low-level query capabilities. Its session management integrates naturally with FastAPI's dependency injection, and its relationship mapping handles complex tournament data models elegantly.
Database migrations need to be version-controlled and reproducible. Alembic auto-generates migration scripts from SQLAlchemy model changes, making schema evolution safe and trackable across development and production environments.
Pydantic schemas provide runtime validation with clear error messages. FastAPI uses them to validate request bodies, query parameters, and path parameters automatically — reducing boilerplate and catching invalid data before it reaches business logic.
FastAPI's dependency system allows database sessions, configuration, and user context to be injected directly into route handlers. This promotes loose coupling and simplifies unit testing by making dependencies swappable.
Separating routers, services, models, and schemas ensures that each layer has a single responsibility. Business logic lives in services — not in route handlers — making it reusable across different API versions or background tasks.
Security is implemented through JWT-based authentication with access and refresh tokens. Passwords are hashed using bcrypt. Authorization checks are enforced via dependency injection — protected routes verify the user's role before executing. Input validation at the Pydantic layer prevents malformed data from reaching the database, while SQLAlchemy's parameterized queries protect against injection attacks.
Stateless tokens with configurable expiration and refresh rotation.
Bcrypt hashing with salt for secure credential storage.
Organizer, referee, and player roles with scoped permissions.
Pydantic schemas validate all incoming data at the API boundary.
Balancing RESTful conventions with the complexity of tournament logic required careful endpoint design — each resource needed to support nested operations without creating overly deep URL structures.
Tournament entities — players, teams, matches, brackets — have deeply interconnected relationships. SQLAlchemy's relationship loading strategies required tuning to avoid N+1 query problems while keeping the code readable.
As features grew, resisting the temptation to couple services was challenging. Regular refactoring and adherence to the service-layer pattern kept modules independent and testable.
Ensuring that services don't depend on HTTP concepts (request objects, status codes) was critical for reuse. Business logic returns domain objects and raises domain exceptions — the API layer translates these into HTTP responses.
Real-time match updates and live scoring via WebSocket connections.
Cache frequently accessed tournament data and leaderboard results.
Offload statistics computation and notification dispatch to task queues.
Multi-container orchestration for API, database, and cache services.
Automated testing, linting, and deployment workflow.
Production deployment on AWS with load balancing and monitoring.
This project reflects my passion for backend engineering and designing systems that are scalable, maintainable, and easy to extend. The focus was never simply on building API endpoints — it was on creating a solid architectural foundation capable of supporting complex tournament applications over time.
Every layer — from the API routers to the service modules to the database models — was designed with future growth in mind. The modular structure, clean dependency injection, and comprehensive validation ensure the codebase remains approachable as features expand.
I'm deeply interested in software architecture, backend engineering, system design, and building reliable infrastructure for modern applications — because great user experiences are built on great backends.