What causes Fabric Pipeline Error 4111?

The linked service referenced in the activity points to a different Azure Machine Learning workspace than the one containing the target published pipeline. The linked service was updated to point to a new workspace or subscription without updating all pipeline activities that depend on it. A wrong linked service was selected during pipeline authoring, either manually or through a template with pre-filled defaults. Environment promotion (e.g., dev to production) resulted in a linked service mismatch where a development workspace reference remains in a production pipeline

How do I fix Fabric Pipeline Error 4111?

Step 1: Open the pipeline in Fabric Data Factory and locate the AzureMLExecutePipeline activity returning Error 4111.. Step 2: Inspect the linked service currently referenced in the activity and note the Azure Machine Learning workspace it points to.. Step 3: Confirm the correct target workspace by verifying the `mlPipelineId` or experiment name used in the activity against the Azure Machine Learning Studio for each workspace.. Step 4: Update the activity's linked service reference to point to the correct Azure ML workspace linked service, creating a new linked service if one does not already exist for the target workspace.. Step 5: Save and validate the pipeline, then trigger a test run to confirm the activity successfully connects to the correct Azure ML workspace.

High severityconfigurationMicrosoft Fabric →

Power BI Refresh Error:
Fabric Pipeline Error 4111

What does this error mean?

The `AzureMLExecutePipeline` activity references a linked service that is incorrect or incompatible with the Azure Machine Learning workspace required for this pipeline run. The activity cannot connect to the target ML workspace using the specified linked service.

Common causes

1The linked service referenced in the activity points to a different Azure Machine Learning workspace than the one containing the target published pipeline
2The linked service was updated to point to a new workspace or subscription without updating all pipeline activities that depend on it
3A wrong linked service was selected during pipeline authoring, either manually or through a template with pre-filled defaults
4Environment promotion (e.g., dev to production) resulted in a linked service mismatch where a development workspace reference remains in a production pipeline

How to fix it

1Step 1: Open the pipeline in Fabric Data Factory and locate the AzureMLExecutePipeline activity returning Error 4111.
2Step 2: Inspect the linked service currently referenced in the activity and note the Azure Machine Learning workspace it points to.
3Step 3: Confirm the correct target workspace by verifying the `mlPipelineId` or experiment name used in the activity against the Azure Machine Learning Studio for each workspace.
4Step 4: Update the activity's linked service reference to point to the correct Azure ML workspace linked service, creating a new linked service if one does not already exist for the target workspace.
5Step 5: Save and validate the pipeline, then trigger a test run to confirm the activity successfully connects to the correct Azure ML workspace.

Frequently asked questions

How can I tell which Azure ML workspace my linked service is pointing to?

In Fabric, go to Manage > Linked Services, open the relevant Azure ML linked service, and review the workspace URL or resource ID configured in the connection settings. Cross-check this against the Azure Machine Learning Studio URL for your intended workspace.

Is it possible for Error 4111 to occur intermittently rather than on every run?

Error 4111 is typically consistent because it reflects a static misconfiguration in the linked service reference. If the error appears intermittently, suspect dynamic expressions resolving to different linked service names across runs, which should be investigated in the activity's expression logic.