FastAPI backends that scale past the demo.
Async Python where it matters: streaming AI responses, long-running jobs, OpenAPI docs your frontend can consume directly. Postgres, Redis, Celery, the works.
What's included
Production-grade FastAPI backend development that ships, not theater.
- Async-native FastAPI with SQLAlchemy 2.0
- OpenAPI auto-docs your frontend can codegen against
- Postgres + Redis + Celery for jobs
- Streaming responses (SSE, WebSockets)
- Sentry + OpenTelemetry observability
- Containerized deploy (Fly, Render, Cloud Run)
What you walk away with
Deliverables you keep — code, infrastructure, and the runbook.
- Deployed FastAPI service
- OpenAPI client codegen for frontend
- Background job system
- Monitoring + alerting setup
Frequently asked
When should I pick FastAPI over Node/Go?+
FastAPI when AI/ML is core (Python ecosystem) or your team is Python-fluent. Node when JS/TS frontend pairing matters most. Go when raw throughput per dollar is the constraint.
How do you handle long-running AI jobs?+
Short tasks stream over SSE/WebSockets. Long jobs go to Celery with Redis backend, status polled by frontend, results delivered async. Time and cost shown live to the user.
What about observability and debugging?+
Sentry for errors, OpenTelemetry for traces (LLM calls instrumented), structured logging. You can trace a user's request from frontend through queue through model and back.
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Email me what you're building. I'll respond with a quote, scope questions, and a clear next step.