- 3 minutes to read

Nodinite Monitoring of the Data Factory service and related Pipelines in Azure

Gain full visibility and control over your Azure Data Factory and pipelines with Nodinite. This page shows you how to monitor Data Factory resources, receive proactive alerts, and take action—without ever needing direct Azure Portal access.

✅ Get instant alerts for Data Factory and pipeline issues
✅ Monitor and manage thresholds for Data Factory pipelines
✅ Access actionable details and Remote Actions from a single interface

Nodinite empowers your integration and support teams to detect, analyze, and resolve issues quickly. You can securely share access to Data Factory resources using Role-based Monitor Views. This approach streamlines troubleshooting, reduces risk, and keeps your business running smoothly.

Data Factory as Resources
Example: List of monitored Data Factory resources in a Nodinite Monitor View.

Monitoring Features

  • State Evaluation – Nodinite evaluates state according to pre-defined policy.

    If Nodinite can't check your Data Factory items' state, chances are no one else can use them either.

  • Automatic Discovery – The Nodinite Azure Agent uses the Azure Rest API to automatically discover Data Factory resources.
  • Category-based monitoring – Nodinite groups monitored Resources by Categories.
  • Role-based access – You can share access to individual items using one or more role-based Monitor Views.

State evaluation

Nodinite presents each Data Factory and related pipeline as a Resource. For example, if you have three Data Factories with two pipelines each, Nodinite displays nine resources.

  • The Resources name matches the deployed Data Factory name.
  • Monitored Data Factory resources belong to the 'Data Factory' Category.

Many other Azure-related Categories exist—see the Azure Logging and Monitoring Overview.

  • The Application name uses the pattern: Configuration name/Resource Group Name

Each item (presented as a Resource) evaluates with a state (OK, Warning, Error, Unavailable).

You can override the evaluation process by configuring the Expected State option for any Nodinite Resource.

Data Factory

For Data Factory Resources, Nodinite evaluates state as follows:

State Status Description Actions
Unavailable Resource not available
  • Nodinite cannot evaluate the 'Data Factory' due to network or security issues
 Review prerequisites
Error Error threshold breached Not implemented -
Warning Warning threshold breached Not implemented -
OK Within user-defined thresholds Details

Data Factory Pipeline

For Data Factory Pipeline Resources, Nodinite evaluates state as follows:

State Status Description Actions
Unavailable Resource not available
  • Nodinite cannot evaluate the 'Data Factory Pipeline' due to network or security issues
 Review prerequisites
Error Error threshold breached Within the lookback period, one or more Pipeline runs:
  • Did not run the minimum expected number of times
  • Ran more times than the maximum expected number of times
  • Took too long to execute according to user-defined threshold
 Edit
Warning Warning threshold breached Within the lookback period, one or more Pipeline runs:
  • Did not run the minimum expected number of times
  • Ran more times than the maximum expected number of times
  • Took too long to execute according to user-defined threshold
 Edit
OK Within user-defined thresholds Details

Alert history for Data Factory

Nodinite enables you to analyze alert history for Data Factory resources. When you troubleshoot, you can search for historical state changes for any time span—either for all Data Factories or for individual resources. See the Add or manage Monitor View page for more details.

Search Resource history
Search for alert history for all resources in the Monitor View
Alert history for the selected Data Factory item

Frequently asked questions

Use the troubleshooting guide to find answers to common questions and known issues.

Next step