The problems with (Python's) Celery

Hatchet, co-founded by the author, is an open-source task queue designed to replace Celery for Python-based web apps, addressing several limitations found in Celery. While Celery is a popular distributed task queue that integrates well with Python frameworks and supports various brokers and backends, it has shortcomings such as lack of asyncio support, absence of global rate limiting, no first-class dead-lettering, and inadequate task-level concurrency settings. These issues can complicate the use of Celery in modern Python stacks, especially for I/O-bound tasks and multi-tenant queues. Furthermore, Celery's defaults, such as early task acknowledgment and high worker prefetch counts, can lead to performance issues and unreliable task execution. Observability is another challenge with Celery, with existing monitoring tools like Flower and Prometheus lacking comprehensive capabilities for high-load scenarios. In contrast, Hatchet aims to overcome these problems by incorporating a central engine and Postgres for result persistence, enabling better rate limits, worker management, and enhanced observability with dashboards and alerting, while still being an early-stage project with ongoing development of new features.

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