All of our background jobs (e.g., image resizing, file uploading, email and SMS sending) are done through Celery (using Redis as its broker). Celery's scheduling and retrying features are especially useful for error-prone tasks, such as email and SMS sending.

For orchestrating the creation of the correct number of instances, managing errors and retries, and finally managing the deallocation of resources we use RabbitMQ in conjunction with the Celery Project framework, along with a self-developed workflow engine.

We maintain a fork of Celery 3 that adds HTTPS support for Redis brokers. The Winning Model currently uses Celery 3 because Celery 4 dropped support for Windows.

We plan on migrating to Celery 4 once Azure ASE supports Linux apps

We used celery, in combination with RabbitMQ and celery-beat, to run periodic tasks, as well as some user-initiated long-running tasks on the server.

Using Celery, the web service creates tasks that are executed by a background worker. Celery uses a RabbitMQ instance as a task queue.

Remote broker and local client for incoming data feeds. Local broker for republishing data feeds to other systems.