Hi WackyRabbit7 . Take a look at https://clear.ml/docs/latest/docs/references/sdk/task#taskget_task

I believe it describes your use case as example.

Sure thing 😁

If I right click on the initial pipeline Draft and hit "Run" from there, the new run wizard is populated with the default parameters value and uses "set_default_execution_queue" as the queue under "Advanced configuration".

JuicyFox94 since I have you, the connection issue might be caused by the istio proxy. In order to disable the istio sidecar injection I must add an annotation to the pod.
https://github.com/allegroai/clearml-helm-charts/blob/main/charts/clearml-agent/templates/agentk8sglue-configmap.yaml#L8

Unfortunately there does not seem to be any field for that in the values file.

Ah I did not think to look for that option in the user's settings. That should do it. Thank you for the help 🙂

yes the pods are starting

But the pre_execute_callback from the pipe.add_function_step needs to be fixed, it does run before the task is executed but the Node does not have any attributes set besides the name.

AgitatedDove14 Thank you for the info. I will try it out.

So it seems it starts on the queue I specify and then it gets moved to the k8s_scheduler queue.

So the experiment starts with the status "Running" and then once moved to the k8s_scheduler queue it stays in "Pending"

Thank you for the reply SmugDolphin23

Is there any possible workaround at the moment?

The error

The alternative I can think of is to implement a clearml Monitor

Hi SmugDolphin23 . I have tried to access node.job with a pre_execute_callback but the node object does not have the job attribute set as you can see above.

yes that is possible but I do use istio for the clearml server components. I can move the agents to a separate namespace. I will try that

works without the istio proxy

ok, i'll try to fix the connection issue. Thank you for the help 🙂

Alright. I will keep it in mind. Thank you for the confirmation 🙂

What I would like to be able to do is basically get rid of the ".pipelines" project that gets created automatically

Hello CostlyOstrich36 I solved it by using a .sh script locally when I want to create/update the trigger. The sh script will chain 2 py scripts together. The first py script will take care of deleting the existing running trigger task and the second py script will be the one that will recreate the trigger task with the updated code.

It just seems strange to me that you could have 2 triggers that do different things but using the same name. Nothing that can't be worked around but for automa...

AgitatedDove14
I do believe triggers should be unique somehow because I find them way too easy to mishandle. Especially if used with schedule_function which is defined in the same script. Updating that function requires deleting the existing trigger task first and recreating it. If not done like this you just end up with 2 trigger tasks with the same name which I assume will respond to the same event(s) but do something slightly different in response. I assume it might work like this...

For a bit more context. Let's say I have 2 experiments in "Project MLOps" called "Exp 1" and "Exp 2". When I publish "Exp 2" I want this trigger to pick up that event and start another task in some other project. But this task would need some information about "Exp 2" like it's name, id or maybe config object etc.

Does the trigger pass any context to the task which will be executed?

actually it does not because the pods logs show .

No problem SmugDolphin23 and thank you. I am really quite stuck with this 😄

Not sure, I have not tried it myself. Give it a go and see how it behaves.

Another parameter for when the task is deleted might also be useful

SmugDolphin23 ok so pipe.start with step_task_completed_callback does indeed work because step_task_completed_callback runs before the task is executed. step_task_created_callback seems to run after the task is executed however so the naming seems to be reversed.

This is what I tried and it does not work because plot is no longer a data frame object, it is now a styler . The error comes from the fact that logger.report_table wants do to fillna on the data frame object. I can't seem to find a way to have the hyperlinks embedded on the data frame object. Any suggestions?

SuccessfulKoala55 So this is the intended behavior? To always have to select the queue from "Advanced configuration" on the pipeline run window even though the "set_default_execution_queue" is set to the "default" queue?

Besides the fact that tasks will always have "k8s_scheduler" as the queue in the info tab so looking back at a task you will not be able to tell to which queue it was assigned.

That would match what add_dataset_trigger and add_model_trigger already have so it would be good

Hi AgitatedDove14 yes exactly