Visually monitor Azure data factories

Azure Data Factory is a cloud-based data integration service. You can use it to create data-driven workflows in the cloud for orchestrating and automating data movement and data transformation. By using Azure Data Factory, you can:

  • Create and schedule data-driven workflows (called pipelines) that can ingest data from disparate data stores.
  • Process/transform the data by using compute services such as Azure HDInsight Hadoop, Spark, Azure Data Lake Analytics, and Azure Machine Learning.
  • Publish output data to data stores such as Azure SQL Data Warehouse for business intelligence (BI) applications to consume.

In this quickstart, you learn how to visually monitor Data Factory pipelines without writing a single line of code.

If you don't have an Azure subscription, create a free account before you begin.

Monitor Data Factory pipelines

Monitor pipeline and activity runs with a simple list-view interface. All the runs are displayed in the browser's local time zone. If you change the time zone, all the date/time fields snap to the one that you selected.

  1. Start Microsoft Edge or Google Chrome. Currently, the Data Factory UI is supported only in those two web browsers.
  2. Sign in to the Azure portal.
  3. Go to the blade for the created data factory in the Azure portal. Select the Monitor & Manage tile to start the Data Factory visual monitoring experience.

Monitor pipeline runs

The list view shows each pipeline run for your Data Factory pipelines. It includes these columns:

Column name Description
Pipeline Name Name of the pipeline
Actions Single action available to view activity runs
Run Start Start date and time for the pipeline run (MM/DD/YYYY, HH:MM:SS AM/PM)
Duration Run duration (HH:MM:SS)
Triggered By Manual trigger or scheduled trigger
Status Failed, Succeeded, or In Progress
Parameters Parameters for the pipeline run (name/value pairs)
Error Pipeline run error (if any)
Run ID ID of the pipeline run

List view for monitoring pipeline runs

Monitor activity runs

The list view shows activity runs that correspond to each pipeline run. To view activity runs for each pipeline run, select the Activity Runs icon under the Actions column. The list view includes these columns:

Column name Description
Activity Name Name of the activity inside the pipeline
Activity Type Type of the activity, such as Copy, HDInsightSpark, or HDInsightHive
Run Start Start date and time for the activity run (MM/DD/YYYY, HH:MM:SS AM/PM)
Duration Run duration (HH:MM:SS)
Status Failed, Succeeded, or In Progress
Input JSON array that describes the activity inputs
Output JSON array that describes the activity outputs
Error Activity run error (if any)

List view for monitoring activity runs


You need to select the Refresh button at the top to refresh the list of pipeline and activity runs. Auto-refresh is currently not supported.

Refresh button

Select a data factory to monitor

Hover over the Data Factory icon on the upper left. Select the arrow icon to see a list of azure subscriptions and data factories that you can monitor.

Select the data factory

Configure the list view

Apply rich ordering and filtering

Order pipeline runs in DESC/ASC according to the run start time. Filter pipeline runs by using the following columns:

Column name Description
Pipeline Name Name of the pipeline. Options include quick filters for Last 24 hours, Last week, and Last 30 days. Or select a custom date and time.
Run Start Start date and time for the pipeline run.
Run Status Filter runs by status: Succeeded, Failed, or In Progress.

Options for filtering

Add or remove columns

Right-click the list view header and choose columns that you want to appear in the list view.

Options for columns

Adjust column widths

Increase and decrease the column widths in the list view by hovering over the column header.

Promote user properties to monitor

You can promote any pipeline activity property as a user property so that it becomes an entity that you can monitor. For example, you can promote the Source and Destination properties of the copy activity in your pipeline as user properties. You can also select Auto Generate to generate the Source and Destination user properties for a copy activity.

Create user properties


You can only promote up to five pipeline activity properties as user properties.

After you create the user properties, you can monitor them in the monitoring list views. If the source for the copy activity is a table name, you can monitor the source table name as a column in the list view for activity runs.

Activity runs list without user properties

Add columns for user properties to the activity runs list

Activity runs list with columns for user properties

Rerun activities inside a pipeline

You can now rerun activities inside a pipeline. Select View activity runs, and then select the activity in your pipeline from which point you want to rerun your pipeline.

View activity runs

Select an activity run

View rerun history

You can view the rerun history for all the pipeline runs in the list view.

View history

You can also view rerun history for a particular pipeline run.

View history for a pipeline run

Gantt views

Use Gantt views to quickly visualize your pipelines and activity runs. You can look at the Gantt view per pipeline or group by annotations/tags that you have created on your pipelines.

Example of a Gantt chart

Gantt chart annotations

The length of the bar informs the duration of the pipeline. You can also select the bar to see more details.

Gantt chart duration

Guided tours

Select the Information icon on the lower left. Then select Guided Tours to get step-by-step instructions on how to monitor your pipeline and activity runs.

Guided tours


Select the Feedback icon to give us feedback on various features or any issues that you might be facing.



You can raise alerts on supported metrics in Data Factory. Select Monitor > Alerts & Metrics on the Data Factory monitoring page to get started.

Data factory Monitor page

For a seven-minute introduction and demonstration of this feature, watch the following video:

Create alerts

  1. Select New Alert Rule to create a new alert.

    New Alert Rule button

  2. Specify the rule name and select the alert severity.

    Boxes for rule name and severity

  3. Select the alert criteria.

    Box for target criteria

    List of criteria

  4. Configure the alert logic. You can create an alert for the selected metric for all pipelines and corresponding activities. You can also select a particular activity type, activity name, pipeline name, or failure type.

    Options for configuring alert logic

  5. Configure email, SMS, push, and voice notifications for the alert. Create an action group, or choose an existing one, for the alert notifications.

    Options for configuring notifications

    Options for adding a notification

  6. Create the alert rule.

    Options for creating an alert rule

Next steps

To learn about monitoring and managing pipelines, see the Monitor and manage pipelines programmatically article.