Visually monitor Azure Data Factory

APPLIES TO: yesAzure Data Factory noAzure Synapse Analytics (Preview)

Once you've created and published a pipeline in Azure Data Factory, you can associate it with a trigger or manually kick off an ad hoc run. You can monitor all of your pipeline runs natively in the Azure Data Factory user experience. To open the monitoring experience, select the Monitor & Manage tile in the data factory blade of the Azure portal. If you're already in the ADF UX, click on the Monitor icon on the left sidebar.

All data factory 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.

Monitor pipeline runs

The default monitoring view is list of pipeline runs in the selected time period. The following columns are displayed:

Column name Description
Pipeline Name Name of the pipeline
Actions Icons that allow you to view activity details, cancel, or rerun the pipeline
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 The name of the trigger that started the pipeline
Status Failed, Succeeded, In Progress, Canceled, or Queued
Annotations Filterable tags associated with a pipeline
Parameters Parameters for the pipeline run (name/value pairs)
Error If the pipeline failed, the run error
Run ID ID of the pipeline run

List view for monitoring pipeline runs

You need to manually select the Refresh button to refresh the list of pipeline and activity runs. Autorefresh is currently not supported.

Refresh button

Monitor activity runs

To view activity runs for each pipeline run, select the View activity runs icon under the Actions column. The list view shows activity runs that correspond to each pipeline run.

Column name Description
Activity Name Name of the activity inside the pipeline
Activity Type Type of the activity, such as Copy, ExecuteDataFlow, or AzureMLExecutePipeline
Actions Icons that allow you to see JSON input information, JSON output information, or detailed activity-specific monitoring experiences
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, In Progress, or Canceled
Integration Runtime Which Integration Runtime the activity was run on
User Properties User-defined properties of the activity
Error If the activity failed, the run error
Run ID ID of the activity run

List view for monitoring activity runs

Promote user properties to monitor

Promote any pipeline activity property as a user property so that it becomes an entity that you monitor. For example, you can promote the Source and Destination properties of the copy activity in your pipeline as user properties. 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

Configure the list view

Order and filter

Toggle whether pipeline runs will be in descending or ascending according to the run start time. Filter pipeline runs by using the following columns:

Column name Description
Pipeline Name Filter by the name of the pipeline.
Run Start Determine the time range of the pipeline runs displayed. Options include quick filters for Last 24 hours, Last week, and Last 30 days or to select a custom date and time.
Run Status Filter runs by status: Succeeded, Failed, Queued, Canceled, or In Progress.
Annotations Filter by tags applied to each pipeline
Runs Filter whether you want to see reran pipelines

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.

Rerun activities inside a pipeline

You can 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

Rerun from failed activity

If an activity fails, times out, or is canceled, you can rerun the pipeline from that failed activity by selecting Rerun from failed activity.

Rerun failed activity

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

Monitor consumption

You can see the resources consumed by a pipeline run by clicking the consumption icon next to the run.

Monitor consumption

Clicking the icon opens a consumption report of resources used by that pipeline run.

Monitor consumption

You can plug these values into the Azure pricing calculator to estimate the cost of the pipeline run. For more information on Azure Data Factory pricing, see Understanding pricing.


These values returned by the pricing calculator is an estimate. It doesn't reflect the exact amount you will be billed by Azure Data Factory

Gantt views

Use Gantt views to quickly visualize your pipelines and activity runs.

Example of a Gantt chart

You can look at the Gantt view per pipeline or group by annotations/tags that you've created on your pipelines.

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


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

    List of criteria

    You can create alerts on various metrics, including those for ADF entity count/size, activity/pipeline/trigger runs, Integration Runtime (IR) CPU utilization/memory/node count/queue, as well as for SSIS package executions and SSIS IR start/stop operations.

  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.