Tracking Celery Task Failures in Python

Celery background tasks often fail silently — retries can mask repeated exceptions that never surface unless you dig through worker logs. This walkthrough demonstrates how Celery handles task failures and retries using a deliberately unstable task, then shows how AppSignal instruments Celery workers to automatically capture exceptions with full tracebacks, retry counts, task arguments, and execution metadata. Key failure patterns to watch for include retry storms, slow tasks blocking queues, and external dependency errors. The post also covers alerting strategies for error rate spikes, new exception types, and task duration anomalies, with a practical payment processing debugging example.