I took a stab at writing an automated trigger to handle this. The goal is: anytime a pipeline succeeds or fails, let AWS know so that the input records can be placed onto a retry queue (or not)

I'm trying to get a trigger to work in general, and then I'll add the more complex AWS logic. But I seem to be missing a step somewhere:

I wrote a file called set_triggers.py

from clearml.automation.trigger import TriggerScheduler

TRIGGER_SCHEDULER = TriggerScheduler()

from pprint import pprint

def log_status(task_id: str):
    print("REACTING TO EVENT!")
    pprint(task_id)

    # write this message to a file at /opt/clearml/logs/trigger.log
    with open("/opt/clearml/trigger.log", "a") as f:
        f.write("REACTING TO EVENT!")
        f.write(pprint(task_id))

TRIGGER_SCHEDULER.add_task_trigger(
    name="emit_sfn_success_signal",
    # trigger_name="emit_sfn_success_signal",
    trigger_on_status=["created", "in_progress", "stopped", "closed", "failed", "completed", "queued", "published",
            "publishing", "unknown"],
    schedule_function=log_status,
    schedule_queue="default",
)

And another called basic_task.py

from clearml import Task

TASK = Task.init(project_name="Trigger Project", task_name="Trigger Test")

print("I ran!")

When I run python set_triggers.py; python basic_task.py , they seem to execute, but I don't see any evidence of the trigger having been executed. Is there any documentation I could read about this process? I was going off of the docstrings in the TriggerScheduler class.