Am I missing something with deployment pipelines? They seem to work with very few objects in Fabric. I am developing a Fabric environment with a Lakehouse, Warehouse, Copy Jobs, Pipelines, mirrored databases, etc. and when I try to promote from my dev to test (and prod) workspaces I end up having to manually recreate everything. Very few things actually deploy nicely. Other than the built in "comparison" screen, which is nice, it seems like a waste of time.

Hey everyone! Have you been keeping up-to-date with the latest generation of AI models? If you HAVEN'T, then I recommend checking them out - they are insane to be honest - I'm talking Claude Opus 4.5, Gemini 3.0, GPT 5.1 etc. Has huge implications for how we will work in the future. I'm just figuring out the best workflows for implementing these models in Fabric workflows, I'll share more of my thinking and research in the following weeks/ months, but I'm interested - have you been keeping up-to-date with the LLM updates? Have you been thinking about how to integrate into Fabric - let me know what you've found so far!

I've noticed that if I an edit has been made to a notebook, which can be accidental when opening a notebook in developer mode, Fabric caches the users changes when the browser is closed. If an update occurs from version control (pull request or an undo) these intended updates get overwritten by the cached version when the notebook is reopened in the browser! This was unexpected. One must then click on a popup warning and choose to accept the other version to ditched this cached version.

Hi all, I'm running into an intermittent issue of notebooks failing to run. The error that crops us is: InvalidHttpRequestToLivy: [TooManyRequestsForCapacity] This spark job can't be run because you have hit a spark compute or API rate limit. To run this spark job, cancel an active Spark job through the Monitoring hub, choose a larger capacity SKU, or try again later. HTTP status code: 430 {Learn more} HTTP status code: 430. This error will come and go randomly without any input from me. I'm really only testing notebooks on a small scale so I'm not certain how it could be a capacity issue. Any help in figuring this out would be greatly appreciated 🙂

Hi all I am facing the problem, that there is no way (Or I do not Know) to sort the short Month in the correct timeline order within a PowerBI Report (Jan, Feb, Mar,...). I have a Column representing Year-Month with format 'yyyy-MM', a second one with the short Month name format 'MMM' and a third one with the numeric values. The columns are in a Materialized view of a Semantic Model in Microsoft Fabric. In the Report I see the alphabetical sorting using the Short Month column, which is logical to me. When Using the Year-Month column it is in the correct timeline sorting. All I want is showing the Short Month column in the correct timeline sorting. Using PowerBI and a local Data-Model I am able to change the Sorting within the column Options. But with the Semantic Model created in MS Fabric this option is not available. Even non sorting could help as the data of the Materialized View is in correct sorting. Any solutions on this? Thanks a lot for your Help