Wait but I don't want to execute it

and in the UI configuration I didn't understand where does permission management came into play

😄

Continuing on this discussion... What is the relationship between configuring files_server and all the rest we just talked about and the the default_output_uri ?

AgitatedDove14

Does it mean that if it is set to False I need an agent but if I set it to True I don't need one?

Yes very much

awesome this will help a lot with debugging

AgitatedDove14

moreover, in each pipeline I have 10 different settings of task A -> Task b (and then task C), each run 1-2 fails randomly

we did execute locally

awesome martin, thanks

Okay Jake, so that basically means I don't have to touch any server configuration regarding the file-server on the trains server. It will simply get ignored and all I/O initiated by clients with the right configuration will cover for that?

Maybe the case is that after start / start_locally the reference to the pipeline task disappears somehow? O_O

what is the difference betwee nfalse and true?

I did, but I only find task name, I'm looking to filter by the project

Not sure I understand, if i run pipe.start_locally(run_pipeline_steps_locally=True|False) what is the difference betwee ntrue and false? assuming I want to execute locally

if I called .start_locally

we are running the agent on the same machine AgitatedDove14 , it worked before upgrading the clearml... we never set these credentials

I understand it starts locally... what does it mean to run the steps locally?

Hahahah thanks for the help SuccessfulKoala55 & CostlyOstrich36

I really do feel it would be a nice to have the ability to easily configure the Cleanup Service to cleanup only specific projects / tasks as its a common use case to have a project dedicated for debugging and alike

the link to manual model registry doesn't work

I know tasks have a name and an ID - but projects?

💪

CostlyOstrich36 ?

For example I have a DATA_DIR environment variable which points to the directory where disk-data is stored

Martin: In your trains.conf, change the value
files_server: ' s3://ip :port/bucket'

Isn't this a client configuration ( trains-init )? Shouldn't be any change to the server configuration ( /opt/trains/config... )?

later today or tomorrow, I'll update

And yes, it makes perfect sense, thanks for the answer

I just tried setting the conf in the section Martin said, it works perfectly