Azure Data Factory supports alerts that allow you to monitor both the success and failures of the pipelines and perform a specific action based on it. While alerts are commonly used to notify the failures, they can also be configured to notify the success. Using success metrics in alerts within Azure Data Factory is essential for monitoring and validating the successful execution of your data pipelines and activities. These alerts notify you about the status and performance of your pipelines and activities. To create an alert rule, you combine the resource you want to monitor, the data from that resource, and the conditions that should trigger the alert.
Data Factory supports integration to Azure Monitor, where you can set up alerts based on metrics and get notifications based on predefined conditions. Azure Data Factory supports various metrics related to pipeline executions, data integration, and data processing. These metrics can help you identify issues and optimize performance.
How Alerts via metrics will Work in ADF
How to create Alert rules in Azure data factory to monitor your pipeline runs?
In the Azure portal Monitoring section, you can find ‘Alerts & Metrics’, where you can create a new alert rule.
When creating a new alert rule, you need to provide details such as the alert rule name, description, severity, criteria and action groups
Configure Alert Logic: Select the dimension values for the alert. For example, if you choose the “Failed Activity Runs” metric, the available dimensions are ActivityType, ActivityName, PipelineName, and FailureType. The dimensions will vary depending on the metric you choose.
Alert logic: select the condition, time aggregation and threshold count
In the below screenshot, when the activity failure is greater than 0 then send the alert.
Evaluate based on: The ‘Evaluate based on’ setting defines how the alert rule analyzes the data to determine whether an alert should be triggered.
In the below screenshot, it checks the pipeline activities from the last 5 minutes pipelines and updates every 1 minute.
In the Azure portal Monitor alerts section, you can view the alert you created, including its condition, target scope, severity, and action group name.
Conclusion: Alerts in Azure Data Factory are essential for effective monitoring and management of your data pipelines. They enable you to track the success or failure of pipelines and activities based on specific conditions. By configuring alerts, you will receive notifications about issues through email, SMS, or other notification types. This approach helps you quickly address any problems, optimize pipeline performance, and ensure that data operations run smoothly and efficiently. Using alerts allows for timely intervention, reducing downtime.
Chandana R L