Steps

Compile a KFP pipeline to YAML with compiler.Compiler().compile(pipeline_func=my_pipeline, package_path='pipeline.yaml')
Create a PipelineJob object: job = aip.PipelineJob(display_name='my-pipeline', template_path='pipeline.yaml', parameter_values={'learning_rate': 0.01}, pipeline_root='gs://your-bucket/pipeline-root')
Create a recurring schedule with job.create_schedule(display_name='weekly-run', cron='0 0 * * 0', max_concurrent_run_count=1, max_run_count=None) — cron uses UTC
List active schedules with aip.PipelineJobSchedule.list(filter='state=ACTIVE') to confirm creation
Pause a schedule: schedule.pause(); resume with schedule.resume() without recreating it
Delete a schedule when it is no longer needed: schedule.delete()

Known gotchas

The cron expression uses UTC — local timezone offsets must be applied manually when setting the schedule time
max_concurrent_run_count defaults to 1; if a run is still active when the next cron trigger fires, the new run is skipped unless you increase this value
PipelineJob.create_schedule() requires the Vertex AI Pipelines Scheduler API to be enabled on the project; if not enabled the call returns a 403 permission error

cloud.google.com/vertex-ai/docs · 5 steps · unrated

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Schedule Vertex AI Pipelines (KFP) runs

Steps

Known gotchas

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