Distributed task queue
Companies using Celery
How Celery is being used
  • AppScale Systems

    #<User:0x00007fa4034778a0> AppScale Systems

    Implements the TaskQueue API.

  • Cloudify 3.0

    #<User:0x00007fa4034c9808> Cloudify 3.0

    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.

  • Brounie SA de CV

    #<User:0x00007fa40351aca8> Brounie SA de CV

    Task queues and cron jobs

  • #<User:0x00007fa403551aa0> MOCI

    백엔드, 어플리케이션 서버 모두 시간이 걸리는 작업들 및 주기적으로 수행해야 하는 작업들은 celery/celerybeat 을 통해 동작됩니다. 신뢰도가 아주 높으며, 유연합니다. gevent 로 동작시키면 더욱 깔끔한 관리가 가능합니다.

  • Kalibrr

    #<User:0x00007fa4035bb770> Kalibrr

    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.

  • dotmos

    #<User:0x00007fa403847c00> dotmos

    Automated distributed tasks.

  • Guoku

    #<User:0x00007fa4038e3a88> Guoku


  • Hypertrack

    #<User:0x00007fa403939280> Hypertrack

    For offloading CPU intensive tasks to separate workers instead of running them on our application server.


    background tasks.


    #<User:0x00007fa4039c8b10> TOMIS

    Background Django/Python tasks. Populated Redis with server cache