Mixing reliability with Celery for delicious async tasks

Celery is an essential tool for asynchronous task queues in Python, particularly for Django projects. However, ensuring high reliability with Celery tasks presents challenges, including tricky settings, potential task loss, opaque task code limitations, and non-trivial monitoring. This talk shares lessons learned from years of production experience to build reliable Celery projects. It covers risks of task loss between different components of the Celery infrastructure (web process, broker, worker processes), strategies for handling task failures, and the importance of designing idempotent tasks. The presentation also explores alternatives to Celery for complex workflows and data-heavy pipelines, recommending tools like Prefect, Temporal, Airflow, Dagster, and Mage for specific use cases. It emphasizes the need for proper error handling, retries, and considerations during deployments to maintain reliability.