Celery

1 / Async Task Processing

Celery handled background task processing in Foundry, where heavy multi-agent evaluation routines could not run synchronously within the Django request-response cycle. Agent evaluation tasks were dispatched to Celery worker clusters backed by Redis broker queues, allowing the web application to remain responsive while evaluation workflows ran asynchronously.

2 / Task Architecture

The integration followed a clean separation: Django views handled user interactions and task dispatching, while Celery workers consumed evaluation tasks from Redis queues and wrote results back to PostgreSQL. Task scheduling and retry logic were configured through Celery's decorator-based API, with dead-letter queues catching permanently failed tasks rather than silently losing them.

3 / Honest Scope

My Celery experience is limited to Foundry's evaluation pipeline. The pattern — async task offloading through a message broker — is a general distributed systems concept that I understand well from building Shard and Cairn, but my direct Celery usage is concentrated in a single project.