Evidently integrations
Overview of the available Evidently integrations.
Evidently is a Python library, and can be easily integrated with other tools to fit into the existing workflows.
Below are a few specific examples of how to integrate Evidently with other tools in the ML lifecycle. You can adapt them for other workflow management, visualization, tracking and other tools.
Tool | Description | Guide or example |
---|---|---|
Notebook environments (Jupyter, Colab, etc.) | Render visual Evidently Reports and Test Suites. | |
Streamlit | Create a web app with Evidently Reports. | |
MLflow | Log metrics calculated by Evidently to MLflow. | |
Airflow | Run data and ML model checks as part of an Airflow DAG. | |
Metaflow | Run data and ML model checks as part of a Metaflow Flow. | |
Grafana, PostgreSQL, and Prefect | Run ML monitoring jobs with Prefect and visualize metrics in Grafana. | |
AWS SES | Send email alerts with attached Evidently Reports (Community contribution). | |
Grafana | Real-time ML monitoring with Grafana. (Old API). |
Last modified 13d ago