airflow-metrics 0.1.0

Airflow plugin for automatically sending metrics from Airflow to Datadog

airflow-metrics

airflow-metrics is an Airflow plugin for automatically sending metrics from Airflow to Datadog.

Installation

pip install airflow-metrics

Setup

airflow-metrics will report all metrics to Datadog, so create an airflow connection with your Datadog api key.

airflow connections --add --conn_id datadog_default --conn_type HTTP --conn_extr '{"api_key": "<your api key>"}'

Note: If you skip this step, your airflow installation should still work but no metrics will be reported.

Usage

That's it! airflow-metrics will now begin sending metrics from Airflow to Datadog automatically.

Configuration

By default, airflow-metrics will begin extracting metrics from Airflow as you run your DAGs and send them to overflow. You can opt out of it entirely or opt out of a subset of the metrics by setting these configurations in your airflow.cfg

[airflow_metrics]

airflow_metrics_enabled = True
airflow_metrics_tasks_enabled = True
airflow_metrics_bq_enabled = True
airflow_metrics_gcs_to_bq_enabled = True
airflow_metrics_requests_enabled = True
airflow_metrics_thread_enabled = True`

Limitations

airflow-metrics starts a thread to report some metrics, and is not supported when using sqlite as your database.

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Getting Started

Set up your virtual environment for python3 however you like.

pip install -e .
airflow initdb
airflow connections --add --conn_id datadog_default --conn_type HTTP --conn_extr '{"api_key": ""}'

Note: The last step is necessary, otherwise the plugin will not initialize correctly and will not collect metrics. But you are free to add a dummy key for development purposes.

Running Tests

pip install -r requirements-dev.txt
pytest