Forum Discussion
Super UserYour Fabric compute session disconnected because the notebook session completed or timed out.
Ok checked and fixed:
with an FTL4 Capacity, you need to create a Spark Pool with the configurations below in the Workspace Settings → Data Engineering/Science section:
Then you need to create an Environment Artifact and add this new Spark Pool to the Environment Artifact:
Publish the changes and then in a notebook you need to use this new Environment Artifact that has this Small Spark Pool which fits in the capacity of FTL4:
Best,
Jacek
Community SupportHi jaryszek ,
Thank you for confirming. Based on your screenshot, the Job Management option does not appear to be available in your current Fabric Trial environment. Feature availability may differ depending on tenant configuration and rollout status, so documentation may reference features that are not yet accessible in all environments.
As you are the sole user on the Trial capacity, the error is unlikely due to another user consuming workspace resources. However, Trial capacities are managed by Microsoft and are shared, so Spark workloads may still face capacity constraints. This can result in a TooManyRequestsForCapacity error, even with only one user active.
To assist further, it would be helpful to know if the issue occurs consistently or only at certain times. Please let us know if the error appears when starting a new notebook session, attaching to Spark, or executing a specific operation. This information will help us determine whether the issue is due to temporary capacity limitations or something specific to the notebook workload.
Thank you.
Super UserThanks,
it is just occuring all the time. I can not run anything
Best Wishes,
Jacek
- v-tejrama
Hi jaryszek ,
Thank you for the update. Since the issue occurs every time and you are unable to start any Spark session, this appears to be more than a temporary capacity throttling event.
Given that you are the only user on the Trial capacity and the error is consistently returned whenever you try to run a notebook, I would recommend testing with a brand new notebook in the same workspace and, if possible, in a newly created workspace as well. If the same behavior persists across all notebooks, it would suggest that the issue is not related to a specific notebook or code but rather to the Spark environment available to your Trial capacity.
You can also check the Fabric Service Status page to see whether there are any ongoing incidents affecting Spark workloads in your region. If no service issues are reported and the problem continues across newly created notebooks, I recommend opening a Microsoft Fabric support ticket and including the Diagnostic ID, Instance ID, timestamp, and screenshots of the error. These details will help the support team investigate the capacity and Spark session provisioning associated with your tenant.
Based on the information shared so far, a scenario where every notebook fails to start a Spark session is not expected behavior, so this may require further investigation from the Microsoft Fabric support team.
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Thank you.