Original celery beat doesn't support multiple node deployment, multiple beat will send multiple tasks and make worker duplicate execution, celerybeat-redis use a redis lock to deal with it. This package provides synchronized scheduler class. Retrieve task result by id in Celery. Set your python path with the source or you can just install in editable mode using. RedBeat uses a distributed lock to prevent multiple instances running. Take a look at the celery.beat.Scheduler class, specifically the reserve() function. By default `redis` backend used, but developers are free too use their own based on package primitives. celery multi [OPTIONS] ... Start shell session with convenient access to celery symbols. CHAPTER 2 Configuration pip install -e . # Installation ```#bash pip install celery-redundant-scheduler Support multiple instance by Active-Standby model ( not tested) Installation. celery. $ celery beat -S celerybeatredis.schedulers.RedisScheduler Configuration class celery.beat.Scheduler (app, schedule = None, max_interval = None, Producer = None, lazy = False, sync_every_tasks = None, ** kwargs) [source] ¶ Scheduler for periodic tasks. 5.Prevent accidentally running multiple Beat servers 1.2Getting Started Install with pip: pip install celery-redbeat ... You can also quickly fire up a sample Beat instance with: celery beat--config exampleconf 2 Chapter 1. I can see that having two instances of celery beat running on the same host would be useful for testing failover between them, but for real redundancy you probably want celery beat running on multiple hosts. and specify the scheduler when running Celery Beat, e.g. $ celery -A proj worker --loglevel=INFO --concurrency=2 In the above example there's one worker which will be able to spawn 2 child processes. celery beat [OPTIONS] Options ... Start multiple worker instances. Introduction. Configure RedBeat settings in your Celery configuration file: redbeat_redis_url = "redis://localhost:6379/1" Then specify the scheduler when running Celery Beat: celery beat -S redbeat.RedBeatScheduler. RedBeat uses a distributed lock to prevent multiple instances running. celerybeat - multiple instances & monitoring, To answer your 2 questions: If you run several celerybeat instances you get duplicated tasks, so afaik you should have only single celerybeat You may run multiple instances of celery beat and tasks will not be duplicated. - chord, group, chain, chunks, The following symbols will be added to the main globals: - celery: the current application. Then specify the scheduler when running Celery Beat: celery beat -S redbeat.RedBeatScheduler. The celery beat program may instantiate this class multiple times for introspection purposes, but then with the lazy argument set. It works using AsyncResult. pip install celery-redbeat. Celery beat multiple instances. Running multiple `celerybeat` instances results multiple scheduled tasks queuing. To disable this feature, set: redbeat_lock_key = None. 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