How One Developer Migrated Blocking FastAPI Endpoints to Async Jobs with arq and Redis

A developer refactored a FastAPI PDF ingestion endpoint that was blocking HTTP requests for minutes due to heavy OCR and LLM processing. The synchronous endpoint was replaced with an asynchronous job queue using arq and Redis, allowing the API to immediately return a job ID instead of waiting for processing to complete. The arq worker pool was integrated into FastAPI's lifespan context manager so it persists across requests and degrades gracefully if Redis is unavailable. A shared dependency in deps.py was added to keep individual route handlers clean while returning a 503 error when the Redis pool is not reachable. Clients can now poll a dedicated status endpoint to track job progress through states such as queued, in-progress, and complete.