Table of Contents
FastAPI can handle 20,000+ requests per second - if implemented correctly. But async doesn't magically make everything faster. A bad FastAPI implementation can be slower than Flask. Here's how to hire developers who actually understand high-concurrency systems.
Must-Know FastAPI Concepts
A qualified FastAPI developer understands:
- ✦ Async/await fundamentals (the event loop, coroutines, tasks)
- ✦ Async database drivers (asyncpg, databases, SQLAlchemy async)
- ✦ Connection pooling (database connections, HTTP clients)
- ✦ Background tasks (BackgroundTasks vs Celery vs asyncio.create_task)
- ✦ Dependency injection (FastAPI's Depends system)
- ✦ Middleware and lifespan management
Evidence of Real Production Experience
Strong candidates can discuss:
- ✦ Load-testing methodologies and bottleneck analysis
- ✦ Database pool sizing decisions under traffic spikes
- ✦ Observability tooling such as Prometheus or OpenTelemetry
- ✦ Incident response during API outages
- ✦ Latency optimization strategies
- ✦ Capacity planning and scaling decisions
Common Async Mistakes That Kill Performance
Red flags in code review:
- ✦ Using sync database drivers in async endpoints (blocks the event loop)
- ✦ Not using connection pools (creates new connection per request)
- ✦ CPU-bound work in async endpoints (use async for I/O, sync for CPU)
- ✦ Forgetting to await (coroutine never runs)
- ✦ No timeout or retry logic for external calls
Interview Questions That Work
Use asyncio.gather for concurrent execution. Use async HTTP client (httpx, aiohttp) and async database driver. Set appropriate timeouts.
The event loop blocks. Use run_in_executor to offload to thread pool, or design CPU-bound work as separate background process.
Connection pool with min and max size. Monitor pool usage. Set connection timeouts. Use async database driver designed for high concurrency.
Practical Assessment Exercise
Ask candidates to:
- ✦ Build a FastAPI endpoint with async database access
- ✦ Implement retries and timeouts for external APIs
- ✦ Add request validation using Pydantic
- ✦ Instrument request timing metrics
- ✦ Identify and fix intentionally injected performance issues
Red Flags
Walk away if they:
- ✦ Use sync database drivers (psycopg2, pymongo) in async endpoints
- ✦ Can't explain the difference between sync and async database drivers
- ✦ Never load-tested a FastAPI application
- ✦ Don't understand connection pooling
- ✦ Use .result() or .wait() incorrectly (deadlocks)
Hiring Scorecard
Async Fundamentals
Weight:
25%
Database & Connection Management
Weight:
20%
System Design
Weight:
20%
Performance Optimization
Weight:
20%
Monitoring & Reliability
Weight:
15%
Hire for Production-Ready Async
Async is powerful but easy to get wrong. Offline Pixel pre-vets FastAPI developers who have built high-concurrency systems in production. Raise a request, talk to candidates, fund the project, and approve payment when you're satisfied.
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