airflow-systemd

Run and monitor systemd-managed jobs from Apache Airflow.

from airflow import DAG
from airflow_systemd import ServiceConfiguration, ServiceUnitConfiguration, Systemd, SystemdAirflowConfiguration

dag = DAG(dag_id="nightly-systemd", schedule="@daily")
config = SystemdAirflowConfiguration(
    scope="user",
    service={
        "nightly": ServiceUnitConfiguration(
            service=ServiceConfiguration(type="exec", exec_start="/opt/jobs/nightly")
        )
    },
)
Systemd(dag=dag, cfg=config)

The generated task lifecycle writes unit files, starts services, monitors state with airflow-ha, handles retriggers, stops services, and optionally removes the generated configuration. SystemdSSH applies the same lifecycle remotely.

Documentation

• Tutorial: run a systemd job from Airflow

• How-to guides

• Why Airflow owns the schedule

• API reference

Published documentation is available at airflow-laminar.github.io/airflow-systemd.

Ecosystem

• systemd-pydantic supplies unit models and the systemctl client.

• supervisor-pydantic and cron-pydantic model alternative runtimes.

• airflow-supervisor provides the analogous supervisord lifecycle.

• airflow-cron converts cron jobs into ordinary Airflow tasks.

• airflow-pydantic supplies declarative task and connection models.

• airflow-config produces YAML-driven DAGs.

Note

This library was generated using copier from the Base Python Project Template repository.