Modern Social Media Backend + Real-time Chat – Scalable, Fast, and Beginner-Friendly
A fully async, non-blocking social media backend built to handle thousands of concurrent connections without breaking a sweat. The stack is designed around FastAPI, async SQLAlchemy, PostgreSQL, Redis, WebSockets, RabbitMQ, Celery, LGTM Stack for observability k6, and pytest so every layer has a clear job: API requests stay fast, database access stays async, background work stays off the request path, and observability stays visible. Production-grade, real-time, and built for scale.
This API packs a lot. For the full breakdown of every feature — async architecture, chat, caching, DevOps, and more — see docs/FEATURES.md.
Want to run the API, test it, or make your own changes? Start with docs/SETUP.md to clone the repository and set up the environment in your machine.
Now that your setup is running, Check out docs/API_GUIDE.md for a detailed walkthrough of all 60+ REST endpoints and the real-time WebSocket chat system.
Want to know how this project runs in the Azure cloud? Read docs/AZURE_DEPLOYMENT.md for the Azure VM, PostgreSQL, Blob Storage, Redis, and CI/CD setup behind the live deployment.
Ready to verify everything works? Check out docs/TESTS.md for a complete guide on running the test suite.
All tests use a separate test database—your dev data stays safe! 🛡️
Real benchmark evidence for the deployed app, with charts + clear conclusions docs/BENCHMARK.md.
Want to observe app raw performance and run synthetic traffic on API? Start with docs/MONITORING_AND_LOAD_TESTING.md for Grafana and k6 setup with app performance reuslts.
Backend developer? Frontend developer? Either, there's a clear path for you. See CONTRIBUTING.md.
From Anits Engineering College
$ claude mcp add Social-Media-Api \
-- python -m otcore.mcp_server <graph>