Deployment Pipeline Error from Test to Production

[Anonymous]

Hi all,

There was something wrong when I deployed using pipeline fron Test to Production. 

Everything was OK last time when I used the two workspaces. This time I just add two parameters to limit the rows of tables in dataset of Test workspace, and the parameters of data sources have nothing to change.  Before the deployment, the data of all the table has been freshed without any errors using the deployment rules of Production.  Moreover, everything worked OK in Test. But, I couldn't deployed my dataset from Test to Production.

I could think there's no problem that I added two parameters in Test but not in Production before the deployment, because I did the same thing successfully for another report in another Test and Production. 

If anyone knows the problem?

Please find the detail information of the error there.

*********************************

Can't complete the deployment

The artifact couldn't be deployed to the target workspace. Try deploying the content again.
{DatasetName}

Please check the technical details for more information. If you contact support, please provide these details.
Hide details
Operation IDb1a9dcb3-2781-45a3-bbcb-2af5eacad2a3
Correlation IDd5795142-ff96-fdc6-1fb4-fa369fdaea51
Request ID871b2793-5af1-30bf-2810-7deafc667f7b
Time4/18/2024, 7:01:45 PM
Service version13.0.23021.69
Client version2404.1.18702-train
Cluster URIhttps://9342ecc5b5494ec68528f4f97158a94c-api.analysis.chinacloudapi.cn/

[Anonymous · Accepted solution]

Try to re-deploy the report to Dev and as different name ReportNameTest with the parameters, then push that one to Test and then to Prod. At least this will tell you if it is something wrong with the original one in Test. 
If that one fails, try the same thing with one without the parameters. That could say if it is the parameters causing the issue.

To be clear, there is nothing wrong with using parameters and deployement pipelines, just trying to get you some debugging thinking.

[Anonymous · Accepted solution]

Hi, @Anonymous 
Thanks for the reply from @Anonymous , please allow me to provide another insight:

Ensure that the parameters you add in the Test workspace are correctly configured as deployment rules for your production environment. If the value or configuration of a parameter varies from environment to environment, the parameter can significantly impact the deployment. You can check the following link:

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

Review the unsupported items and properties to verify that the parameters you've added or any other changes you've made aren't in the unsupported deployment items or properties category. Some properties may not be replicated or supported during deployment. You can check the following link:

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

If your dataset uses incremental refresh policies, make sure that the parameters related to those policies are set correctly for your production environment. Incorrect configuration can cause the deployment to fail. You can check the following link:

Incremental refresh for semantic models and real-time data in Power BI - Power BI | Microsoft Learn

Ensure that the dataset in your production environment has no unresolved dependencies. If the dataset depends on other items that haven't been deployed or updated in production, it can cause the deployment to fail.

How to Get Your Question Answered Quickly 

Best Regards

Yongkang Hua

If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.

[Anonymous · Accepted solution]

Try to re-deploy the report to Dev and as different name ReportNameTest with the parameters, then push that one to Test and then to Prod. At least this will tell you if it is something wrong with the original one in Test. 
If that one fails, try the same thing with one without the parameters. That could say if it is the parameters causing the issue.

To be clear, there is nothing wrong with using parameters and deployement pipelines, just trying to get you some debugging thinking.