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    Data Factory
    • 05 Aug 2026
    • 4 Minutes to read
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    Contents

    Data Factory

    • Updated on 05 Aug 2026
    • 4 Minutes to read
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      Light
    • Download PDF
    Article summary

    Overview

    Data Factory is a cloud-based data integration service that lets you build data-driven workflows to orchestrate and automate the movement and transformation of data. Once a Data Factory resource is associated with a Turbo360 Business Application, you can manage its triggers, monitor activity, and track integration runtimes directly from Turbo360.

    Business value

    Managing triggers, monitoring runs, and tracking integration runtime health from Turbo360 removes the need to switch between the Azure portal and your operations console, helping you respond to pipeline failures faster.

    How it works

    • Turbo360 surfaces all triggers configured for the Data Factory resource, along with their run history and status.
    • Trigger runs can be filtered by status to quickly isolate failures or pending runs.
    • Linked integration runtimes are listed with their current status, so you can confirm compute availability before troubleshooting pipeline issues.

    Permissions

    Access to Data Factory actions in Turbo360 is controlled through role-based access control (RBAC). When adding a role, enable the Data Factory resource type and assign one or both of the following permission levels:

    PermissionGrants
    ReadView triggers, trigger runs, integration runtimes, and the resource dashboard.
    ManageStart and stop triggers, in addition to all Read capabilities.

    Operations

    Turbo360 lets you start and stop Data Factory triggers directly, so you can manage trigger state without switching to the Azure portal during incident response or planned maintenance.

    Start and stop triggers

    • Start trigger — activates a stopped trigger. Use this when a trigger was paused and pipeline runs need to resume.
    • Stop trigger — deactivates a running trigger. Use this when you need to pause scheduled runs, for example during a maintenance window.
    1. Open the Data Factory resource and go to Triggers.
    2. Select the trigger, then click Start or Stop.

    Triggers.png

    Click a trigger to view its details, including description, end time, and annotation when available in the Azure portal.

    Trigger details.png

    image.png

    Field values such as Description, End Time, and Annotation are displayed in trigger details only when available in the Azure portal.

    Trigger runs

    View all trigger runs, including the trigger type and execution time, and filter them by status: Waiting, Running, Succeeded, Failed, Waiting on Dependency, or Cancelled. Use this when investigating why a pipeline didn't run as expected.

    Trigger runs.png

    Trigger status.png

    Integration runtimes

    View and filter linked integration runtimes by status — Online, Access Denied, Initial, Limited, Need Registration, Offline, Started, Starting, Stopped, or Stopping. Use this when confirming compute availability before troubleshooting a pipeline failure.

    Integration runtimes.png

    Resource dashboard

    The Data Factory dashboard surfaces pipeline and trigger health at a glance, helping you spot failed runs and capacity issues without opening individual triggers.

    WidgetWhat it shows
    Failed Pipeline RunsCount of pipeline runs that failed, for quick triage.
    Failed-Cancelled-Succeeded Activity RunsBreakdown of activity run outcomes across the Data Factory.
    Trigger Runs SummaryAggregate view of trigger run volume and outcomes.
    Total Entities CountNumber of entities (pipelines, datasets, etc.) in the Data Factory.
    Factory DetailsKey metadata about the Data Factory resource.
    SSIS SummarySummary of SSIS package execution activity.

    You can add, remove, or reconfigure widgets to focus on the metrics most relevant to your support scenario.

    Data factory-dashboard.png

    Metrics

    The Metrics tab lets you chart any Azure metric for your Data Factory directly in Turbo360, without switching to the Azure portal. Use it to track failed pipeline runs, activity run outcomes, and trigger run volumes over time — complementing your dashboard widgets with flexible time-range charts to identify failure patterns and peak processing periods.

    Use the following controls to build your chart:

    ControlDescription
    Select metricChoose the Azure metric to visualize (e.g. Failed Pipeline Runs, Succeeded Pipeline Runs, Failed Activity Runs, Trigger Runs Succeeded, Integration Runtime CPU Utilization).
    AggregationSet the aggregation method: Average, Min, Max, Total, or Count.
    Time rangeSet the time window for the data (e.g. Last 24 hours, Last 7 days).
    GranularitySet the data point resolution (e.g. 1 minute, 1 hour).
    Chart typeChoose the visualization type: Line or Bar.

    Click Apply to render the chart.

    Data factory-metrics.png

    Monitoring

    Data Factory supports Availability status and Metric monitoring rules, configured from Data Factory > Monitoring.

    Monitoring rules are saved per resource, and the monitoring state is reflected after every monitoring cycle.

    Availability status monitoring

    Tracks the resource health status of the Data Factory. Use this when you need an early signal that the resource itself is unreachable or degraded.

    1. Configure the Availability status rule with the desired threshold.
    2. Click Save.

    Availability status.png

    Metric monitoring

    Tracks specific Data Factory metrics against a configured threshold. Use this when you want to be alerted as soon as a metric — such as failed pipeline runs — crosses an operational limit.

    1. Select the monitoring metrics and configure the threshold values. Any metric name can be used; the rule is violated once the configured threshold is met.
    2. Click Save.

    Metric monitoring.png

    Troubleshooting

    1. Trigger status doesn't update in Turbo360 after starting or stopping it in the Azure portal.
      Cause: Turbo360 reflects trigger state from the next sync cycle, not in real time.
      Fix: Wait for the next sync cycle, or refresh the resource page.

    2. Trigger or pipeline run details show blank fields such as Description or End Time.
      Cause: These fields are only populated when a value exists in the Azure portal.
      Fix: Set the field in the Azure portal; Turbo360 will display it once available.

    3. Start or Stop action is unavailable for a trigger.
      Cause: The signed-in role only has Read permission on the Data Factory resource.
      Fix: Request Manage permission for Data Factory from your administrator.

    4. Monitoring rule shows no violation despite an apparent issue.
      Cause: The monitoring state updates only after a full monitoring cycle completes.
      Fix: Wait for the next monitoring cycle, or verify the configured threshold value.

    5. Dashboard widgets show no data.
      Cause: The Data Factory resource may not yet be fully synced, or the metric has no recent activity.
      Fix: Confirm the resource sync status, and check back after the next sync cycle.

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