i have two systemd service
one handles my celery workers(10 queue for different tasks) and one handles celery beat
after deploying new code i restart celery worker service to get new tasks and update celery jobs
Should i restart celery beat with celery worker service too?
or it gets new tasks automatically ?
It depends on what type of scheduler you're using.
If it's default PersistentScheduler then yes, you need to restart beat daemon to allow it to pick up new configuration from the beat_schedule setting.
But if you're using something like django-celery-beat which allows managing periodic tasks at runtime then you don't have to restart celery beat.
Related
I have seen celery documentation that its advisable to run celery as daemon process. In my case each celery worker is a docker container whose sole purpose is to execute celery tasks. In that scnario also, is it recommended to execute as daemon process?
No, if Celery worker runs inside a container there is no need to run it as daemon.
Can I know what does celery daemonization mean? Also, I would like to start running both celery worker and celery beat using single command. Anyway to do it (one way I can think of is using supervisor module for worker and beat and then writing the starting scripts for those in a separate .sh file and running that script..any other way?)
In other terms, I can start the worker and beat process as background process manually even..right? So, daemonization in celery just runs the processes as background processes or is there anything else?
I have a Kubernetes cluster running Django, Celery, RabbitMq and Celery Beat. I have several periodic tasks spaced out throughout the day (so as to keep server load down). There are only a few hours when no tasks are running, and I want to limit my rolling-updates to those times, without having to track it manually. So I'm looking for a solution that will allow me to fire off a script or task of some sort that will monitor the Celery server, and trigger a rolling update once there's a window in which no tasks are actively running. There are two possible ways I thought of doing this, but I'm not sure which is best, nor how to implement either one.
Run a script (bash or otherwise) that checks up on the Celery server every few minutes, and initiates the rolling-update if the server is inactive
Increment the celery app name before each update (in the Beat run command, the Celery run command, and in the celery.py config file), create a new Celery pod, rolling-update the Beat pod, and then delete the old Celery 12 hours later (a reasonable time span for all running tasks to finish)
Any thoughts would be greatly appreciated.
I'm having issues with a celery beat worker not sending out tasks to celery. Celery runs on three servers with a RabbitMQ cluster behind HAProxy as a backend.
Celery beat is used to schedule a task every day at 9AM. When I start the worker, usually the first task succeeds, but after that it seems like the following tasks are never sent to rabbitmq. In the celery beat log file (celery beat is run with the -l debug option), I see messages such as: Scheduler: Sending due task my-task (tasks.myTask), but no sign of the task being received by any celery worker.
I also tried logging messages in rabbitmq via the rabbitmq_tracing plugin, which only confirmed that the task never reached rabbitmq.
Any idea what could be happening? Thanks!
I am running celery 3.0.19 with mongodb as backend and broker. I would like to use queues in sub-tasks but it does not work. Here is how to reproduce the problem from the example add task.
Start a celery worker with the command
celery -A tasks worker --loglevel=info --queue=foo
Then create a task that never gets done like that
from tasks import add
sub_task = add.s(queue="foo")
sub_task_async_result = sub_task.apply_async((2,2))
note the following task will get executed normally.
async_result = add.apply_async((2,2), queue="foo")
what do I do wrong?
Thanks!