Forum Discussion
Fabric Monitor to KQL Database
I'm trying to get the data from Fabric Monitor and stream it into a KQL database for reporting and alerting. Ideally, it would be something like an EventStream to connect to something like Azure Log Analytics. Log Analytics has ADF pipeline info, but I don't see any Fabric data there. Thank you for your help.
I don't think we are able to directly access the Kusto database which is behind the Fabric capacity metrics app (FCMA).
I think we would need to query the data from the Fabric capacity metrics app's semantic model (using the DAX query API or semantic link), and save it in our own storage (e.g. Lakehouse or KQL). There are some solutions on the web that shows examples of how to do this. Please note, the schema of the FCMA semantic model may change, so such a solution would need to be adjusted on your side if the semantic model is changed by Microsoft.
Fabric Workspace Monitoring is another monitoring tool (currently in preview) which creates a Kusto dabase in each workspace it gets activated in. This one is easily to connect to. But at the moment it only captures Semantic model, Eventhouse and GraphQL events.
7 Replies
- lbendlin
Super User
The Fabric Monitoring app is already fed from Kusto. You want to move data from one Kusto instance into another?!?
- todd-wilsonFrequent Visitor
Thanks for the reply. I only need to know where the data is (which Kusto database). Would this be something hidden to non-admins?
- lbendlin
Super User
It's hidden and Microsoft are extremely tight-lipped about it. They are also not answering any questions about the atrocious 8 minute delay of their "real time" data.
- todd-wilsonFrequent Visitor
Thanks again for your answer. I have a feeling it may be in the Admin Workspace. Really helps knowing that it's a Kusto database.
- AnonymousNot applicable
Hi todd-wilson ,
Did the above suggestions help with your scenario? if that is the case, you can consider Kudo or Accept the helpful suggestions to help others who faced similar requirements.
Regards,
Xiaoxin Sheng