Hey PanickyMoth78
Here is an easy to reproduce, working example. Mind the multi_instance_support=True parameter in the pipeline itself. This code launches 3 pipelines for me just as it should 🙂
` from clearml.automation.controller import PipelineDecorator
import time

PipelineDecorator.set_default_execution_queue("default")

@PipelineDecorator.component()
def step_one():
time.sleep(2)

@PipelineDecorator.component()
def step_two():
time.sleep(2)

@PipelineDecorator.pipeline(name='custom pipeline logic', project='examples', version='0.2', multi_instance_support=True)
def executing_pipeline(_):
# Use the pipeline argument to start the pipeline and pass it ot the first step
print('launch step one')
step_one()

print('launch step two')
step_two()

if name == 'main':
# Start the pipeline execution logic.
for i_dataset in [0, 1, 2]:
executing_pipeline(i_dataset)

print('process completed') `