Module 1: The Pre-API Era & Monolithic Architecture
Learn the origins of APIs, monolithic architectures challenges, third-party database integration risks, and why API connections decoupling is necessary.
Day 1
The Pre-API Era and Monolithic Architecture
Why this matters
Monolithic Architecture: Monoliths couple UI, logic, and data — APIs decouple clients from backends for scale and partner access.
Early applications were monoliths: one codebase contained UI, business logic, database access, and ML utilities. Scaling and partner integrations became painful.
- Partners could not safely access internal databases.
- Mobile, web, and third-party clients duplicated validation logic.
- One heavy ML job could starve the entire server.
Solution: Expose a stable HTTP API layer so clients request data through defined contracts, not raw DB access.
Common mistakes
- Blocking the event loop with heavy sync code in async routes.
- Returning wrong HTTP status codes (200 on validation failure).
- Shipping without request/response models for ML endpoints.
Interview checkpoints
- Q: Explain monolithic architecture in one minute. A: Definition + ML deployment angle.
- Q: One FastAPI pitfall? A: Validation, async blocking, or wrong status code.
Practice
- Basic: Define Monolithic Architecture and give an example.
- Intermediate: Implement a minimal snippet for Monolithic Architecture.
- Advanced: Break it and read the OpenAPI / error response.
Recap
- You can explain monolithic architecture clearly.
- You know one mistake to avoid.
- You see how this connects to the next lesson.
Next: API Analogy
Day 2
How APIs Solve the Problem: The Restaurant Analogy
Why this matters
API Analogy: The waiter/API pattern explains why clients never touch the kitchen/database directly.
An API is the contract between client and server — like a waiter who takes orders and brings food without letting customers into the kitchen.
The Restaurant API Analogy
| Restaurant | Software |
|---|---|
| Customer | Frontend / mobile app |
| Menu | API documentation (OpenAPI) |
| Waiter | API gateway / FastAPI routes |
| Kitchen | Backend + database + ML pipeline |
Common mistakes
- Blocking the event loop with heavy sync code in async routes.
- Returning wrong HTTP status codes (200 on validation failure).
- Shipping without request/response models for ML endpoints.
Interview checkpoints
- Q: Explain api analogy in one minute. A: Definition + ML deployment angle.
- Q: One FastAPI pitfall? A: Validation, async blocking, or wrong status code.
Practice
- Basic: Define API Analogy and give an example.
- Intermediate: Implement a minimal snippet for API Analogy.
- Advanced: Break it and read the OpenAPI / error response.
Recap
- You can explain api analogy clearly.
- You know one mistake to avoid.
- You see how this connects to the next lesson.
Next: FastAPI Stack