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Airflow plugin to export dag and task based metrics to Prometheus.

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Airflow prometheus exporter

Exposes dag and task based metrics from Airflow to a Prometheus compatible endpoint.

Compatibility with Airflow versions

>=2.0

Current version is compatible with Airflow 2.0+

<=1.10.14, >=1.10.3

Version v1.3.2 is compatible

Note: Airflow 1.10.14 with Python 3.8 users

You should install importlib-metadata package in order for plugin to be loaded. See #85 for details.

<1.10.3

Version v0.5.4 is compatible

Install

pip install airflow-exporter

That's it. You're done.

Exporting extra labels to Prometheus

It is possible to add extra labels to DAG-related metrics by providing labels dict to DAG params.

Example

dag = DAG(
    'dummy_dag',
    schedule_interval=timedelta(hours=5),
    default_args=default_args,
    catchup=False,
    params={
        'labels': {
            'env': 'test'
        }
    }
)

Label env with value test will be added to all metrics related to dummy_dag:

airflow_dag_status{dag_id="dummy_dag",env="test",owner="owner",status="running"} 12.0

Metrics

Metrics will be available at

http://<your_airflow_host_and_port>/admin/metrics/

airflow_task_status

Labels:

  • dag_id
  • task_id
  • owner
  • status

Value: number of tasks in a specific status.

airflow_dag_status

Labels:

  • dag_id
  • owner
  • status

Value: number of dags in a specific status.

airflow_dag_run_duration

Labels:

  • dag_id: unique identifier for a given DAG

Value: duration in seconds of the longest DAG Run for given DAG. This metric is not available for DAGs that have already finished.

airflow_dag_last_status

Labels:

  • dag_id
  • owner
  • status

Value: 0 or 1 depending on wherever the current state of each dag_id is status.

License

Distributed under the BSD license. See LICENSE for more information.

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Airflow plugin to export dag and task based metrics to Prometheus.

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