- 4 minutes to read

Manage Azure Data Factory Monitoring with Nodinite

Take control of your Azure Data Factory monitoring with Nodinite. This guide shows you how to empower your teams to securely manage, monitor, and take action on Data Factory and Pipelines—without direct Azure Portal access.

✅ Proactively monitor Data Factory and pipelines for issues
✅ Enable secure, role-based self-service for business and support teams
✅ Access actionable details and remote actions from a single interface

Nodinite lets you delegate management and insights for selected Data Factory resources in Azure. Your support and maintenance teams gain deep insights for root cause analysis—while you minimize risk by limiting direct Azure Portal access. This approach reduces potential attack vectors and safeguards mission-critical services from accidental disruption.

graph LR subgraph "Nodinite Azure Data Factory Monitoring" roA[fal:fa-monitor-waveform Azure Agent] ---- roM(fal:fa-watch-fitness Monitoring) end subgraph "Azure" roSub[fal:fa-credit-card Subscription] roPL[fal:fa-industry-windows Data Factory] roPLs(fal:fa-bars Pipelines ) end roM --- |0..*| roSub roSub --- |0..*| roPL roPL --- |0..*|roPLs

Diagram: High-level overview of how Nodinite monitors and manages Azure Data Factory and Pipelines.

Application Management Team IT Operations Business
Empower your AM team to proactively manage Data Factory without disrupting IT operations Maintain full control and visibility over all actions Deliver actionable insights and self-service for business solutions built on Data Factory

Management Features

For Resources in Role-based Monitor Views with Remote Actions privileges, you can:

Category Monitoring Actions Metrics/Statistics
Data Factory ✅ Details -
Pipelines ✅ Details
Edit		 -

As an Administrator with access to Configuration for Monitoring Agents, you can:

Monitoring Remote Configuration
Monitoring Data Factory
  • Enable and disable monitoring as specified
Monitoring Data Factory Pipelines
  • Enable and disable monitoring as specified
  • Manage thresholds
    • Lookback period
    • Min Execution count
    • Max Execution count
    • Duration

Data Factory
Example: Nodinite Monitor View with Data Factory resources.

Data Factory

The 'Data Factory' Category provides one Resource for each Data Factory found using the configuration, with the specified display name as the Resource name.

Data Factory
Example: Monitor View with a list of 'Data Factory'.

The Data Factory category provides Resources that display the evaluated monitored state according to built-in rules.

You can perform the following Remote Actions for the Data Factory Category:

Data Factory Remote Actions
Example: Remote Actions for Data Factory.

Data Factory Details

To view details about the selected Data Factory Resource, click the Action button and select Details from the 'Control Center' menu.
Details Menu Action
Use the 'Details' action to open the details modal for the selected Data Factory.

Next, select the option to present the modal.
Data Factory Details
Example: Details for the selected Data Factory.

Nodinite lists the Pipelines available within the selected Data Factory in the Pipelines accordion at the bottom of the modal:
Data Factory Pipelines
Example: Existing pipelines within the selected Data Factory.

Pipelines

The 'Data Factory Pipeline' Category provides one Resource for each pipeline per Data Factory found using the configuration, with the deployed name as the Resource name.
Data Factory Pipelines
Example: Monitor View with a list of 'Data Factory Pipelines'.

The Data Factory Pipeline category provides Resources that display the evaluated monitored state according to built-in rules. Review the Monitoring Data Factory user guide for details.

You can perform the following Remote Actions for the Data Factory Pipeline Category:

Data Factory Pipelines Remote Actions
Example: Data Factory Remote Actions.

Pipeline Details

To view details about the selected Data Factory Pipeline Resource, click the Action button and select Details from the 'Control Center' menu.
Details Menu Action
Use the 'Details' action to open the details modal for the selected Data Factory Pipeline.

Next, select the option to present the modal.
Data Factory Pipeline Details
Example: Details about selected Data Factory Pipeline.

Edit Pipeline thresholds

You can edit the monitoring thresholds by clicking the Action button and selecting the Edit menu item within the 'Control Center' section.
Action to Edit thresholds
Example: Edit thresholds Action button menu item.

Next, select the option to present the modal.
Edit thresholds modal
Example: Editing monitoring thresholds for selected 'Data Factory Pipeline'.

You can manage the following monitoring properties:

  • Use global thresholds – When checked, monitoring thresholds use the global settings
  • Lookback period – How far back in time to look for problems. Monitoring evaluation uses this value if the current time is higher than the last clear date-time + the lookback period
  • Min Execution count – Min execution count (Warning)
  • Min execution count (Error) – Enter the monitoring thresholds for the count-based evaluation. -1 means that the check is disabled (default)
  • Max Execution count – Max execution count (Warning)
  • Max execution count (Error) – Enter the monitoring thresholds for the count-based evaluation. -1 means that the check is disabled (default)
    • Duration (ms) – Set the threshold for the maximum duration
    • Warning
    • Error
  • Warning – Number of days before Data Factory expires to trigger the Warning alert
  • Error – Number of days before Data Factory expires to trigger the Error alert
  • Description – The user-friendly description of this specific Data Factory monitoring configuration

Click the Save button to persist changes.
Save button
Save button.

Next Step

Monitoring Data Factory

Azure Logging and Monitoring Overview
Prerequisites for Azure Agent