In this lab you see how to monitor the machine learning endpoints we deployed in the previous labs.
Azure Machine Learning integrates with Application Insights that is a feature of Azure Monitor. So, with this, you can monitor your application (in our case the API 😁) and collect useful insights and logs of endpoint's usage.
To know more please take a look in this link.
The following Azure services will be used in this lab. If you need further training resources or access to technical documentation please find in the table below links to Microsoft Learn and to each service's Technical Documentation.
| Azure Service | Microsoft Learn | Technical Documentation |
|---|---|---|
| Azure Machine Learning | Monitor models with Azure Machine Learning | Monitor and collect data from ML web service endpoints |
| Azure Monitor | Analyze your Azure infrastructure by using Azure Monitor logs | Azure Monitor Technical Documentation |
| Step | Description |
|---|---|
 |
Enable Application Insights in your endpoint |
 |
Display custom logs |
| IMPORTANT |
|---|
| Take a look in this notebook. |
You can also import this notebook to your own workspace. Just right-click on the blank space below your username and choose Import -> File and put the path of the file. You can download to your local machine and upload to Databricks Workspace as well.