Deployment Pipeline does not rebind Direct Lake semantic model to target Warehouse

[seblopezarteta]

Deployment Pipeline does not rebind Direct Lake semantic model to target Warehouse

Environment

• Microsoft Fabric

• Deployment Pipelines

• Semantic Model storage mode: Direct Lake

• Data source type: Warehouse

Scenario

DEV Workspace

Sandbox

Sandbox
 ├─ Warehouse
 └─ Semantic Model

TEST Workspace

Sandbox Test

Sandbox Test

Steps to reproduce

1. Create a new Deployment Pipeline.

2. Assign the DEV workspace (Sandbox).

3. Assign the TEST workspace (Sandbox Test).

4. Deploy both the Warehouse and the Semantic Model from DEV to TEST.

5. Verify the deployment status.

Result

Both artifacts show:

Warehouse -> Same as source
Semantic Model -> Same as source

The semantic model is successfully deployed to the TEST workspace.

However, when opening the semantic model and inspecting a table, the metadata shows:

Storage mode: Direct Lake
Data source type: Warehouse
Workspace: Sandbox

instead of:

Workspace: Sandbox Test

Additionally, the Lineage View shows that the Semantic Model located in the TEST workspace is still connected to the Warehouse located in the DEV workspace.

Expected behavior

After deployment, the Direct Lake semantic model in TEST should automatically bind to the Warehouse deployed in the TEST workspace:

Sandbox Test
 ├─ Warehouse
 └─ Semantic Model

Additional validation performed

• Created a completely new Deployment Pipeline.

• Created a completely new TEST workspace.

• Confirmed Warehouse deployment succeeded.

• Confirmed Warehouse status = "Same as source".

• Confirmed Semantic Model status = "Same as source".

• Refreshed the Semantic Model after deployment.

• Verified the Lineage View.

• Verified the table metadata inside the Semantic Model.

The issue persists.

Additional information

The Semantic Model was created directly in Microsoft Fabric from the Warehouse using Direct Lake mode. It was not published from Power BI Desktop.

Question

Is automatic rebinding of Direct Lake Semantic Models to the target Warehouse currently supported by Deployment Pipelines, or is manual rebinding required after deployment?

If manual rebinding is required, what is the recommended approach for DEV → TEST → PROD deployments?

[seblopezarteta · Accepted solution]

Hi @apturlov,

I wasn't able to update/create the deployment rule, guess it's because the SM connects to the WH via Direct Lake mode.

I finally did update the Shared Expression using Tabular Editor, pointing it to the Test WH. That worked as workaround to continue with the Test full deployment.

Thanks a lot anyway for your help!

Best!

[tayloramy]

Hi @seblopezarteta, 

This is expected. Directlake on OneLake models are not fully supported by deployment pipelines yet. I hope that one day soon they are. 

For now my workaround is very similar to what you did, editing the deployed semantic model to point to the new lakehouse/warehouse. I use VS Code and Fabric Studio for this, but tabular editor works just as well. 

THis limitation is outlined in the docs: The Microsoft Fabric deployment pipelines process - Microsoft Fabric | Microsoft Learn

Though the docs say to use datasource rules to rebind them, that only works for directlake on SQL, not directlake on OneLake. 

[seblopezarteta · Accepted solution]

Hi @tayloramy,

Thanks for your reply!

I also hope this will solved in a near future! In the meantime, we'll continue using the workaround, will have a look to you VSCode solution! Thanks for that!

[apturlov]

Hello @seblopezarteta, you are likely hitting one of the limitations of Fabric Deployment pipelines related to Semantic models. Please check this article for detailed list of Semantic model support limitations:

The Microsoft Fabric deployment pipelines process - Microsoft Fabric | Microsoft Learn

Specifically, the data source connection is not automatically changed in a Semantic model when it's deployed to another workspace. To make it happen you need to configure a deployment data source rule that will replace the data source connection. Read more about this here: The Microsoft Fabric deployment pipelines process - Microsoft Fabric | Microsoft Learn.

You can configure a deployment rule in the destination deployment stage, i.e. Test, only AFTER you deploy a Semantic model at least once. When you configure a rule, you can choose specific values related to the Warehouse SQL endpoint from the list of available. Keep in mind, that if you want to point your Semantic model to another Warehouse it must exist already before you can choose it and, of course, it has to have exactly the same schema.

Hope this information helps with your issue. If so, consider giving this answer kudos and mark as a solution for the benefit of other community members.

[seblopezarteta · Accepted solution]

Hi @apturlov,

I wasn't able to update/create the deployment rule, guess it's because the SM connects to the WH via Direct Lake mode.

I finally did update the Shared Expression using Tabular Editor, pointing it to the Test WH. That worked as workaround to continue with the Test full deployment.

Thanks a lot anyway for your help!

Best!

[v-nmadadi-msft]

Hi @seblopezarteta ,
Glad to know the issue has been resolved with the workaroud.
We really appreciate your efforts and for letting us know the update on the issue.
Please continue using fabric community forum for your further assistance.

Regards

[seblopezarteta]

Hi @apturlov,

Thanks for your fast reply.

I did try the deployment rule but I'm not able to update it:

I guess it's because the SM connects to Warehouse via Direct Lake mode.

Thanks anyway for your help!