- First, sign up to hawkflow for free: https://hawkflow.ai/ and get an API key
- Install the pip package
pip install hawkflowairflow - Add this to the top of your DAG
from hawkflowairflow import hawkflow_callbacks hawkflow_callbacks.HF_API_KEY = "YOUR_HAWKFLOW_API_KEY_HERE"
- Add these two lines to default_args in your DAG:
default_args={
"on_success_callback": hawkflow_callbacks.hawkflow_success_callback,
"on_execute_callback": hawkflow_callbacks.hawkflow_start_callback
}
All done. Now when your DAG runs, you will see the output in the HawkFlow UI. https://app.hawkflow.ai/login
Known Issues
If you are on an ARM mac and notice that your DAG is just hanging. You may need to put this at the top of your DAG. Airflow is running as a different user on your mac, and the security is blocking outgoing requests.
import os
os.environ['NO_PROXY'] = '*'
More examples
More examples: HawkFlow.ai Python examples
Read the docs: HawkFlow.ai documentation
What is HawkFlow.ai?
HawkFlow.ai is a new monitoring platform that makes it easier than ever to make monitoring part of your development process. Whether you are an Engineer, a Data Scientist, an Analyst, or anyone else that writes code, HawkFlow.ai helps you and your team take ownership of monitoring.