Azure Data Factory ALERTS

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Azure Data Factory ALERTS

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

  1. Alert Rules: Alerts are based on rules that you configure in Azure Monitor, which is integrated with ADF. These rules define the conditions under which you want to be notified.
  2. Metrics: Alerts can be triggered by metrics. Metrics give you high-level views of performance.
  3. Action Groups: When an alert is triggered, it can initiate actions defined in Action Groups. These actions might include sending emails, SMS messages.

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

  1. Alert Rule Name is a required field. You must provide a name of your choice, or you can use the default name “NewAlert.”
  2. Description field is optional. If you want to include additional details about your alert, you can add it here.
  3. Severity is a required field. Severity is used to categorize the importance or impact of an alert. Severity levels help you prioritize how to address issues that arise during the execution of data pipelines and activities.
    Azure Monitor Alert Severity Levels
    Sev 0 = Critical
    Sev 1 = Error
    Sev 2 = Warning
    Sev 3 = Informational
    Sev 4 = Verbose
  4. Add criteria
    Select metrics: Choose the metrics for which you want an alert. Metrics are quantitative measurements, such as the number of failed pipelines runs.
    In the below screenshot, I am choosing the Failed Activity runs metrics


    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.

  5. Configure Notification: You will create a new action group or use the existing action group.
    Add notification: Enter an action name and choose the notification type, such as email, SMS, voice, or Azure app push notification. Provide the necessary details based on your chosen notification type.
    In the screenshot below, I selected an email notification


    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

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