Forum Discussion
LAKEHOUSE I/O WRITE DELAY MITIGATION
If the following problem keeps giving you a headache and causing you to have to add all sorts of unnecessary runtime checks to your pipeline and guessing how long to pause the pipeline execution for, then please vote for this idea: LAKEHOUSE I/O WRITE DELAY MITIGATION - Microsoft Fabric Community
The issue is that, after a data write to a lakehouse, the lakehouse is out of sync while your pipeline execution is just running along faster than the lakehouse can signal that the new data has been successfully committed, and causing pipeline failures unless you slap down a Wait activity set to pause the whole process for like 10 mins or more, which is just insane to even consider this as a remotely acceptable solution.
Multiple solutions to force a metadata refresh, be it a Script running some T-SQL, or doing the same from a Notebook (as supplied by support itself) does not work.
Therefore, please vote for this idea where I suggest 2 possible solutions, which IMHO I think are more elegant and simple (considering here the inexperienced user population) than having to mess around with configuring and testing a REST API endpoint call, which is the upcoming Q2 workaround by Microsoft:
LAKEHOUSE I/O WRITE DELAY MITIGATION - Microsoft Fabric Community
Hi Element115
Thank you once again for your continued engagement and for raising these important points.
I apologize for the delayed response. It is entirely reasonable to expect a high level of quality, stability, and trust from any generally available (GA) product. Although Microsoft Fabric has been in GA since 2023, it is common for certain scenarios or edge cases to surface only after wider adoption.your feedback highlights a critical area for improvement. Since you have already submitted your idea, I have upvoted it as well. With increased visibility and community support, it has a better chance of being prioritized for review by the relevant product teams. Microsoft will continue to evaluate and enhance the platform to meet the stability and experience that users rightfully expect.
If you Accept this post, it will be helpful for others to find more easily and will address these kinds of issues and resolve them soon.
Regards,
Karpurapu D,
Microsoft Fabric – Community Support Team.
7 Replies
Hi Element115
Thank you for highlighting the issue of Lakehouse I/O write synchronization within Fabric pipelines.This is a valid and recurring concern, particularly regarding the delay between a write operation to a Lakehouse and the availability of that data for subsequent pipeline activities, especially when new tables are created or data is freshly ingested.
This lag can lead to premature downstream operations encountering errors due to the Lakehouse not yet reflecting the committed data or table, resulting in failed executions or the need to manually insert delay mechanisms.
Your suggestions to improve this behavior by introducing:
- An optional wait flag within the Copy Data activity to await confirmation of data commit before proceeding,
or - A dedicated "Wait for I/O Commit" activity that explicitly pauses pipeline execution until the lakehouse signals readiness,
Both suggestions are simple, and user-friendly enhancements that would significantly improve pipeline reliability and usability, particularly for users less familiar with configuring retry logic or API polling workarounds.
we encourage other community members to upvote your idea on theLAKEHOUSE I/O WRITE DELAY MITIGATION - Microsoft Fabric Community to bring further visibility to this matter.
Once again, thank you for your valuable input and for driving constructive suggestions that help improve the community forum for all users.
Best regards,
Karpurapud.
Microsoft Community Support.
Here is a workaround originally shared by Mark Pryce-Maher, the
Microsoft PM responsible for the synchronisation between lakehouse and SQL endpoint. As he says: "the following solution is unofficial, unsupported, undocumented, and frankly unwise!"
However, I would not call this a solution since it is unofficial, unsupported, undocumented, and unwise. Anything that is unofficial, unsupported, undocumented, is precisely unwise because it could change at any time without any notice to the user, who will be much bewildered when stuff suddenly breaks for no apparent reason.
Mark's original Python code: Workaround for delays in the automatically generated schema in the SQL analytics endpoint of the Lakehouse in Fabric | by Mark Pryce-Maher | Medium
An improved version of this code by Andre Fomin: Fix SQL Analytics Endpoint Sync Issues in Microsoft Fabric – Data Not Showing? Here's the Solution! — obvience
For now, this Python script seems to work and the problem I had due to the sync issue has not manifested itself... yet.
Hi Element115
Thanks for the update and sorry for the inconvenience. We are pleased to hear that you have found a workaround but You're absolutely right in highlighting the inherent risks of relying on unofficial, unsupported, and undocumented solutions. Hope your issue gets resolved soon by your idea (in ideas forum) getting implemented.
Thank you.
- An optional wait flag within the Copy Data activity to await confirmation of data commit before proceeding,
