u/Otherwise-Whole-1977

Fabric runtime sunset timeline clarity

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!

reddit.com
u/Otherwise-Whole-1977 — 10 days ago

return value for Fabric python API: run_on_demand_notebook

You may recall I previously posted about the Fabric REST API here:

https://www.reddit.com/r/MicrosoftFabric/comments/1t3q78i/help_running_notebook_as_a_background_job_via/

(Only linking because there may be a bit more context on what I'm doing for those interested)

I didn't know where else to post about this - this python package is not in an open source repo (yet?) so I can't just create an issue. Anyways, this function, microsoft_fabric_api.FabricClient.notebook.background_jobs.run_on_demand_notebook, has an unfortunate return value of None.

That means you can start a notebook job run, but you can't poll it. With the REST API you get Retry-After and Location in the response headers. That enables directly tying a job start to job polling.

With the python API wrapper you basically have to use FabricClient.core.job_scheduler.list_item_job_instances but then there is ambiguity if the notebook could be started by multiple processes.

I think the return value should be updated to actually return NotebookJobInstance which already has attributes like status ("NotStarted, "InProgress", ...).

The point of this post: can this feedback be raised with the python API devs? Thanks!

reddit.com
u/Otherwise-Whole-1977 — 4 months ago

I have a few different use-cases for running notebooks (with my own credentials or as a service principal) via API (from outside of Fabric).

I've tried following the API docs and also with the (unannounced? - I can't actually find any documentation) python wrapper around the API, also referred to here: https://www.reddit.com/r/MicrosoftFabric/comments/1qqdwio/new_python_sdk_for_fabric_rest_apis_can_we_use_in/

Does anyone have an example of this API call? I tried a lot of different stuff, even had Copilot pore through the available docs and it couldn't figure it out either.

The main error I get, when calling (with the python sdk):

resp = fabric_client.notebook.background_jobs.run_on_demand_notebook(
    workspace_id="...",
    notebook_id="...",
    beta=False,
)
azure.core.exceptions.HttpResponseError: (None) The requested job type is invalid
u/Otherwise-Whole-1977 — 5 months ago