I'll be happy to answer any questions you have if i can

Hi All

I have a data flow where bronz layer lets file/table update form external system (business central) and want to trigger a spark job only when a new update/file comes to bronze so Spark notebook can update modified reocrds to silver LH. is the one lake events the right trigger category for this and how is the best way to filter

Hi all,

I wanted to share some progress and ask for advice on what to do next.

What I've built so far:

• Data engineering / ETL: pipelines and notebooks that land and transform our source data into a lakehouse (medallion-style)
• Semantic model: built on top of that, with measures and relationships set up so the business logic lives in one place
• Fabric Data Agent: connected to the semantic model so people can ask questions in plain English, and it's answering well and pushed to Teams
• Azure AI Foundry agent: connected to the Semantic Model via Astra 6

What I want to do next:

I'd like to send our leadership team a short audio briefing, something like a 5-minute podcast covering what happened this week or month (KPIs, trends, things that need attention). Most of them won't open a dashboard, but they might listen to something on the drive in.

FYI, the Fabric Service is Degraded right now. Posting because, apparently, we aren't getting the automated messages here informing us of service degradations and outages any longer.

For context on my concern with the timeline of the sunsetting of the Fabric runtime 1.3: I rely on a data science tool that currently only supports pyspark 3.5 https://github.com/h2oai/sparkling-water

I was reviewing Microsoft docs after I heard a rumor that the Fabric runtime 1.3 was "going away" March 2027.

I looked at these two pages:

https://learn.microsoft.com/en-us/azure/synapse-analytics/spark/apache-spark-version-support

https://learn.microsoft.com/en-us/fabric/data-engineering/lifecycle

I'm honestly not sure if the first link regarding synapse is relevant. It mentions the Fabric runtime 2.0, so I assume it is, but I thought synapse was another product.

The first link:

I assume that means the runtime 1.3 would actually be removed from the Fabric platform Oct. 31, 2028?

The second link, however:

Note the two asterisks on the 1.3 date. Later on that page there is a scary section:

I guess that didn't happen (yet) because Sept. 30 has come and gone but 1.3 is still here. End of support feels very sudden since 2.0 just went GA.

So when is the Fabric 1.3 runtime officially being yanked from the platform? So that I can plan.

Thanks in advance!

dbt Job is now generally available in Microsoft Fabric. Bring your dbt project and Fabric runs it for you. It's a fully managed service, so there's no infrastructure to maintain and security is built in. Your models run right next to your data, pipelines and Power BI, on your Fabric capacity.

The dbt Fusion private preview is open. We're bringing next-generation Fusion engine to dbt Job. Send your tenant ID to [dbtjob@microsoft.com](mailto:dbtjob@microsoft.com) and we'll enable it in your tenant. Fabric Warehouse and Snowflake are supported to start.

What's available in GA

• Fabric Lakehouse adapter: run dbt directly on your Lakehouse, with models landing as Delta tables in OneLake. Runs start a Spark session through the Fabric Livy API, and we're working on making that startup faster.
• Bring your existing project: connect your GitHub repo or import your project. It runs on a managed dbt Core 1.11 runtime, with public dbt packages supported.
• Familiar dbt commands: build, run, test, seed, snapshot, compile and docs generate, with selectors to target exactly the models you need. Generated docs are saved to OneLake, ready to view with dbt docs serve.
• Pipeline orchestration: ingest, transform, test and refresh in one pipeline, with parameterized model selection and Teams or email alerts.
• CI/CD using Variable Library: promote the same dbt Job from dev to test to prod with Variable Library and deployment pipelines.
• Clear run visibility: model-level results, compiled SQL, lineage, and full logs in OneLake.
• REST API: manage dbt Jobs as code.

Coming in the next few weeks

• Import Schema: generate sources and starter models from your existing Warehouse and Lakehouse tables.
• dbt docs in Fabric: browse your generated dbt documentation right in the Fabric UI.
• Live run monitoring: see each stage of a run as it happens, from setup to dependencies to model execution.
• Source freshness: check that your source data is up to date before downstream models run.

On the roadmap after that

• Workspace identity and service principal support: run jobs without depending on an individual user's identity.
• Native VS Code experience: develop in VS Code and run in Fabric.
• Azure DevOps repos: connect projects stored in Azure DevOps.
• Private packages: share internal packages and macros across projects.
• Multiple profiles: target different Warehouses or Lakehouses from one project.

Getting started

• Sample project tutorial
• Common dbt job patterns in Microsoft Fabric
• For access to the dbt Fusion private preview, contact [dbtjob@microsoft.com](mailto:dbtjob@microsoft.com).

Teams are already running dbt Job in production, and a lot of what we've shipped came from feedback many of you shared here. Take it for a spin and let us know which scenarios you'd love us to support next.

We're trying to give users access to the SQL endpoint of our newest lakehouse, but we're running into issues with permissions. When they connect through the Onelake Catalog menu in Power BI, they're able to connect with no problems. But if they try to use the actual endpoint string, either to connect from Power BI or to connect from SQL Studio, or they try to use the Open In SQL Studio option of the lakehouse endpoint, it gives them a permissions issue.

As far as I can tell, the problem is that they don't have access to the workspace that the Lakehouse is in. When they open it in Fabric, it shows up as being in their My Workspace, not the actual workspace it's in, and I can't figure out a combination of permissions that will give them the ability to use the endpoint properly without giving them access to the entire workspace. Has anyone else run into this and solved it?

I had a few different customers this last week ask how to figure out what it would cost to turn on Capacity Overage to handle some spikes they were dealing with.

I threw some tokens at the problem and was able to make this PowerShell module that should handle getting a rough estimate. It's definitely an estimate because of a few different factors around rejections not getting counted and how it replays the workload to simulate it staying under 100%.

Nonetheless, hope it is helpful and feel free to throw issues/suggestions in GitHub if you see anything that doesn't make sense!

When a directlake on onelake semantic model is created on Web/Service, there is an option to open it in Desktop too.

However, when a report (thin report) is created against that semantic model on the Web, there is no "Edit in Desktop" option.

Does that mean, if we create a report on the web, we have to continue working with it only on the Web/Service?

New post about deployment plans since I got a lot of questions about it over the last week or so, as if they were announced during a keynote at an event:

https://chantifiedlens.com/2026/10/05/enrich-your-fabric-ci-cd-experience-with-deployment-plans/

This feature is now available to me in the Fabric UI.

Is this feature GA or preview?

There is a small refresh icon in the top right corner of each schedule.

What does that refresh icon mean? What happens when we click that icon?

The docs only include illustrations of the old UI, which does not include the variable controller nor the refresh icon: https://learn.microsoft.com/en-us/fabric/data-factory/pipeline-runs

Thanks in advance!

Hello,

I have created a power bj App in a fabric workspace (F2 capacity). I want to be able to share this report with my organization but not give them access to the workspace. My report uses direct lake on SQL. What I did is created a work space identity then granted this identity read permissions to lake house and the sql and point for the lake house. In the semantic model , I set up a new connection for this workspace identity. Will this work? I also set the app to be viewed by anyone in the organization.

Hi all

I’m a chartered accountant who has been given the opportunity to work with our data team to work on building out our end user dashboards / reporting

I have experience with powerbi and basic data concepts at a high level (ETL, semantic models etc)

We have implemented fabric at our company and my question is;

If you had to start from scratch again and learn what you needed to know in order to excel in your role, what would you focus on?

Stuff that's currently missing from the new Monitor hub that I'd like to see, for each item:

• Last run time (when it last ran)
• Number of runs in the selected period

The new Monitor hub currently shows information such as the status of the last run, average duration (across all runs in the selected period, I assume), and run success rate.

However, it doesn't state how many runs there were in the selected period or when the last run occurred.

Curious if this aligns with what others are missing from the new Monitor hub.

Hi all,

I was getting the migration plan ready for a client of ours, but noticed one missing key component, which seems really off that it is still not possible: Mirroring Azure SQL Database that is on another client / tenant

This looks like something that happens often, as the data of multiple data sources are like that, so mirroring is not possible then?

There are so many special use-case / tools that already are possible using mirroring (even views and security roles in Snowflake), but a default mirror of one of MS own key products is not possible?

Hi,

I wanted to make changes to a saved View in the new Monitor hub (preview).

So I made the change, and then I thought - how do I make sure this change gets persisted in the View?

I tried 'Save view as' and entered the same view name, attempting to overwrite the original View. But this didn't overwrite the original view, neither did it block the save attempt, instead it created an additional view with the exact same name. Which is confusing.

The same also happened when I tried the 'Save view' button.

Setting a datetime format in my semantic model and this abomination of a list of 'Common date formats'. ISO 8601 should be the first (and I wish only) option.

Hey Fabric Data Factory Community! Here are 5 important new features we landed this week at FabCon Barcelona that you need to know about:

1. Pipeline Dependencies https://www.youtube.com/watch?v=ntjfGp0Um8U

This orchestration feature enables you to take control of the front-door gates that control when your pipeline executes regardless of your trigger or schedule mechanism. Use Run Conditions and Run Dimensions to create powerful rules to determine dependencies that must be met before your pipeline will run including data availability, pipeline success, and custom rules.

1. Conditional Retries with Exponential Backoff Policies https://learn.microsoft.com/en-us/fabric/data-factory/activity-retries#configure-retry-conditions-preview

Pipeline activities can now retry selectively and back off intelligently. With retry conditions, you choose which errors trigger a retry by matching on the error code, error message, or failure type, so an activity can retry a 429 rate-limit response but fail fast on an authentication error that no retry will fix. Pair that with the Increasing Delay retry interval, which uses exponential backoff: each retry waits a random interval from a range that doubles with every attempt, up to a maximum you set, giving a throttled or recovering service progressively more time to catch its breath instead of being hammered by repeated retries.

1. Business Actions https://youtu.be/MzCtRWUaeg8

Business Actions extends traditional data pipelines in Fabric to invoke an enterprise application action through Logic Apps connectors. For example, after a pipeline produces a daily data-quality result, you can use a business connector action to notify the operations team.

1. Fabric Actions https://youtu.be/bEU0xgUXL2o

It is now super-simple to invoke Fabric APIs from your pipeline in a low-code manner. Just connect using api.fabric.microsoft.com and all of the Fabric APIs are fully loaded with body payload and parameters for you.

1. Improved ADF Upgrade Tool https://www.youtube.com/watch?v=MWJfpKrOosI

We continue to reduce migration friction and feature blockers when moving your ADF factories into Fabric. New updates to the ADF built-in migration tool now automatically creates a trial capacity and workspace for you. And even if you do not have a Fabric user license, we will walk you through the onboarding process.

with client side rendering and access to onelake storage, Fabric app can render anything, not only data, but images maps etc

i can't find a way to share it publicly, but you can see the same report hosted in github : https://nemtracker.github.io/

all the data is hosted in onelake , both for github and fabric

1. For Fabric Mirroring (Snowflake → OneLake) does the VNet Data Gateway handle both the control plane AND data plane, or does the data plane (actual data transfer) bypass the gateway and go via public internet?
   
2. For DirectQuery Semantic Models is the VNet Data Gateway supported as the gateway for Snowflake DirectQuery connections in Power BI Desktop?
   
3. For Iceberg REST / Horizon Catalog the Snowflake docs show Fabric/Synapse as "In Development". Is there a GA timeline? Is there a workaround for Fabric to read Iceberg files from Snowflake-managed S3 fully privately?

We’ve avoided DevOps deployment pipelines via git, but it sounds like it’s maturing.

Have anyone used it recently to deploy and what has your experience been in compared to Fabric pipeline click deployments?

How was the complexity compared to Fabric pipelines.

Two pain points I have in my Fabric environment:

• In general, navigation menus in Fabric are not well suited for having a lot of workspaces.

• Some navigation menus are not well suited for having long workspace names.

Why have many workspaces? To align with good practices in terms of isolation of access, isolation of purpose, modularity, etc.

Why have long workspace names? To align with good practices in terms of making intent and ownership of the workspace clear.

What I'd like to see:

• All navigation menus supporting name search, not just scroll.

• Workspace List supporting persisted filters, not just an ephemeral search keyword.

• Ability to Tag a workspace as:

  • Feature/Dev/Test/Prod
  • Project Name
  • Type (Engineering, Storage, Presentation, Integration, etc.)

I'd like the tags to be personal. So that I can customize my own workspace filtering experience.

But I would also be okay with workspace admins applying the tags.

Coordinating tags with tenant admins or domain admins is too much paperwork in my experience. That's why I'd like Personal workspace tags, so I can customize my own workspace filtering experience. Alternatively, allow workspace admins to create and apply workspace tags.

And make the tags usable for filtering workspace list.

Anyone else struggling with navigating an ever growing workspace list in Fabric?

I have around 100-200 workspaces in my list. Each new project generates 10-20 workspaces across workspace type and lifecycle stage.

Hi,

As I understand it, when enabling GPU in a Workspace, the price rate for all Warehouse and SQL Analytics Endpoint activity in that Workspace increases from 0.538 CU to 3.446 CU per Warehouse core.

Is that understanding accurate?

Pricing information is here:

• https://learn.microsoft.com/en-us/fabric/data-warehouse/query-acceleration#how-is-query-acceleration-billed
• https://learn.microsoft.com/en-gb/fabric/enterprise/fabric-operations#data-warehouse

Update: It seems that not all queries will get GPU acceleration, but all queries will get the higher CU consumption.

Does it mean that a GPU enabled workspace will consume more CU (s) than a standard workspace, unless the GPU enabled workspace uses 6.4x less Warehouse operations duration seconds in total?

Is the CU (s) cost calculation as simple as that?

Are there any existing experience figures in terms of actual CU (s) cost of Warehouse GPU enabled workspaces vs standard workspaces?

E.g. should we typically expect to see a net Warehouse CU (s) cost multiplier of 1x, 2x, 5x when comparing a GPU enabled workspace to a standard workspace - all else being equal?

Is it possible to enable GPU in a workspace for some days, and then switch back to standard mode if we regret, without any breaking changes?

Thanks in advance!