r/MicrosoftFabric

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 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.

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?

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:

Runtime name	Release date	Release stage	End of support announcement date	End of support effective date
Azure Synapse Runtime for Apache Spark 3.5	Oct 13, 2025	GA; LTS beginning Nov 1, 2027	Oct 31, 2027	Oct 31, 2028

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

The second link, however:

Runtime name	Release stage	End of Support date
Runtime 2.0 based on Apache Spark 4.1	GA	August 31, 2028
Runtime 1.3 based on Apache Spark 3.5	EOSA	September 30, 2026**

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

Runtime removed	Once the runtime reaches the unsupported phase, all environments using this runtime are eliminated. All backend-related components associated with this runtime are also removed.	A few days after the end of support date

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!