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I have been receiving the below error in power bi service when trying to refresh a dataflow. This is only ocurring in our production environment. Dev and test work fine but when promoting to production it errors out. There is very little help in other forums about this. Any help would be greatly appreciated.
Error: PipelineException: Container unexpectedly exited. Exit code: 0xC000012D. PID: 7244 . RootActivityId = 96b0ad47-2ccb-4310-a0ff-a6ab3562b9c5.Param1 = PipelineException: Container unexpectedly exited. Exit code: 0xC000012D. PID: 7244 Request ID: d6ee2d40-3fcd-1db9-971c-fc7c669fce52.
hi, @cpmass28
There are many reasons for this error, from the error code you provided, you need to check it step by step and use it to determine what the current problem is, this is a process that requires patience, here is what I think you need to check:
1.Check for Environmental Differences:
Ensure that the production environment has the same configuration as the dev and test environments.
Check for any discrepancies in data sources, permissions, or network configurations between the environments.
Resource Allocation:
The error code 0xC000012D often relates to insufficient resources. Ensure that the production environment has adequate resources (CPU, memory) allocated for Power BI Service operations.
Check if there are any resource constraints or limits being hit in the production environment.
2.Dataflow Configuration:
Review the configuration of the dataflow in the production environment. Ensure that all the connections, credentials, and settings are correctly set up and match those in the dev and test environments.
3.Error Logs:
Check the detailed logs and trace files for the Power BI Service in the production environment. These logs may provide more detailed information about why the container is exiting unexpectedly.
Look for any patterns or commonalities in the logs that could point to a specific issue.
4.Network Issues:
Verify that there are no network issues or interruptions affecting the dataflow refresh process in the production environment.
Ensure that all required endpoints and data sources are accessible from the production environment.
5.Data Volume:
Compare the volume of data being processed in production versus dev/test. Larger data volumes can sometimes cause unexpected issues.
If the production environment handles significantly more data, consider breaking the dataflow into smaller chunks or optimizing the queries.
6.Update Power BI Gateway:
If you are using an on-premises data gateway, ensure that it is updated to the latest version. Older versions may have bugs or performance issues that have been resolved in newer releases.
hackcrr
If this post helps, then please consider Accept it as the solution and kudos to this post to help the other members find it more quickly
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