Airflow plugin to export dag and task based metrics to Prometheus.
Exposes dag and task based metrics from Airflow to a Prometheus compatible endpoint.
Current version is compatible with Airflow 2.0+
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.
Version v0.5.4 is compatible
pip install airflow-exporter
That's it. You're done.
It is possible to add extra labels to DAG-related metrics by providing labels
dict to DAG params
.
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 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 DAGValue: 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
.
Distributed under the BSD license. See LICENSE for more information.