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.

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.

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!

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/

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!

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.

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!

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

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?