Schedule a pipeline

Learn how to set, pause and stop a schedule for pipelines.

Schedules don't work for all orchestrators. Here is a list of all supported orchestrators.

Orchestrator	Scheduling Support
AirflowOrchestrator	✅
AzureMLOrchestrator	✅
DatabricksOrchestrator	✅
HyperAIOrchestrator	✅
KubeflowOrchestrator	✅
KubernetesOrchestrator	✅
LocalOrchestrator	⛔️
LocalDockerOrchestrator	⛔️
SagemakerOrchestrator	⛔️
SkypilotAWSOrchestrator	⛔️
SkypilotAzureOrchestrator	⛔️
SkypilotGCPOrchestrator	⛔️
SkypilotLambdaOrchestrator	⛔️
TektonOrchestrator	⛔️
VertexOrchestrator	✅

Set a schedule

from zenml.config.schedule import Schedule
from zenml import pipeline
from datetime import datetime

@pipeline()
def my_pipeline(...):
    ...

# Use cron expressions
schedule = Schedule(cron_expression="5 14 * * 3")
# or alternatively use human-readable notations
schedule = Schedule(start_time=datetime.now(), interval_second=1800)

my_pipeline = my_pipeline.with_options(schedule=schedule)
my_pipeline()

Check out our SDK docs to learn more about the different scheduling options.

Pause/Stop a schedule

The way pipelines are scheduled depends on the orchestrator you are using. For example, if you are using Kubeflow, you can use the Kubeflow UI to stop or pause a scheduled run. However, the exact steps for stopping or pausing a scheduled run may vary depending on the orchestrator you are using. We recommend consulting the documentation for your orchestrator to learn the current method for stopping or pausing a scheduled run.

Note that ZenML only gets involved to schedule a run, but maintaining the lifecycle of the schedule (as explained above) is the responsibility of the user. If you run a pipeline containing a schedule two times, two scheduled pipelines (with different/unique names) will be created.

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See Also:

Schedules rely on remote orchestrators, learn about those here