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

I am trying to run with scale from zero k8s nodes for maximum cost savings. So a node should only be online if clearml actually runs a task. Waiting for the 2 hours timeout when running on expensive gpu instances for example is quite wasteful because the pipeline controller pod will keep the node online.

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

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

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

Thank you SmugDolphin23 I'll try it out.

TimelyMouse69 The pipeline task(s) end up in a sub project called ".pipelines" no matter how I configure the PipelineController project name and target project. This .pipelines project is not visible from the "PROJECTS" section of the UI. You can only get to it from the PIPELINES view by clicking on "Full details" on a step.

Please see attached images

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"

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

Sure thing 😁

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...

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.

GitHub Issue created: https://github.com/allegroai/clearml/issues/786

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

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?

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.

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.

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.

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.

I also experience that if a worker pod running a task is terminated, clearml does not fail/abort the task.

actually it does not because the pods logs show .

yes the pods are starting

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

works without the istio proxy

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

The error

Now for example the pod was killed because I had to replace the node. The task is stuck in "Running". Aborting from the UI says "experiment aborted successfully" but the state does not change.

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

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?

Thank you for the reply SmugDolphin23

Is there any possible workaround at the moment?