Hello ClearML,

I am curious to know how does the clearml PipelineController know the ip of the ClearML server? It seems it knows the right IP of the task server when it register a pipeline, but I am not sure how.

` # create the pipeline controller
pipe = PipelineController(
project='rudolf',
name='Pipeline functions as pipelines',
version='1.1',
add_pipeline_tags=False,
)

set the default execution queue to be used (per step we can override the execution)

pipe.set_default_execution_queue('rudolf')

add pipeline components

pipe.add_parameter(
name='url',
description='url to pickle file',
default=' '
)
pipe.add_function_step(
name='step_one',
function=step_one,
function_kwargs=dict(pickle_data_url='${pipeline.url}'),
function_return=['data_frame'],
cache_executed_step=True,
)
pipe.add_function_step(
name='step_two',
# parents=['step_one'], # the pipeline will automatically detect the dependencies based on the kwargs inputs
function=step_two,
function_kwargs=dict(data_frame='${step_one.data_frame}'),
function_return=['processed_data'],
cache_executed_step=False,
)
pipe.add_function_step(
name='step_three',
# parents=['step_two'], # the pipeline will automatically detect the dependencies based on the kwargs inputs
function=step_three,
function_kwargs=dict(data='${step_two.processed_data}'),
function_return=['model'],
cache_executed_step=True,
)

For debugging purposes run on the pipeline on current machine

Use run_pipeline_steps_locally=True to further execute the pipeline component Tasks as subprocesses.

pipe.start_locally(run_pipeline_steps_locally=False)

Start the pipeline on the services queue (remote machine, default on the clearml-server)

pipe.start(queue="rudolf")

print('pipeline completed') `