Celery is a widely used distributed task queue framework for Python applications. Celery handles distributing background tasks to worker processes or nodes, manages their execution reliably, and can scale to hundreds or thousands of jobs per second in production environments.

Celery is especially popular in the Python ecosystem because it fits naturally with the language's syntax and its commonly used in frameworks like Django or Flask. Celery uses familiar concepts — decorators for tasks, Python data structures for messages — and integrates easily with Python's logging, error handling, and testing tools. Its configuration is also Python-based, avoiding the need to learn an entirely separate domain-specific language.

Lastly, Celery's architecture is highly flexible. It works with different message brokers such as RabbitMQ (which we will use in this tutorial), Redis, or Amazon SQS, letting the developer pick a broker that best suits their workload and infrastructure.