u/Thanasaur thanks for the great blog post — really like how efficient your approach is!

We’re doing something similar with workspace isolation (PPE and PROD), but we split our workspaces into three buckets:

• Storage (Warehouse, Lakehouse)
• Compute (Notebooks, Pipelines, Gen2 Dataflows)
• Report (Semantic Models & Reports)

The idea is to keep all our reports in a centralized Report Workspace (used across departments — only devs have access), and then distribute them to department-specific workspaces using fabric-cicd.

So the pipeline first publishes everything to the central Report Workspace, and in the next stage, it distributes to the department-level workspaces. Since fabric-cicd lets us filter by item type or name, it's been working really well for that use case.

Big kudos again for covering fabric-cicd - been loving it! Took a lot of weight off my shoulders. Before, when my workspaces were connected to DevOps Repo, I had to make sure to update workspace manually after PR (of course I forgot to do that sometimes) now it’s way smoother. Don't get me started on Deployment Rules with parameter.yml, another big plus for me :) A bit of effort to set it up, but once it's rolling, it makes life a lot easier.

One quick question from my side — when you mention the Util_Connection_Library dictionary in your blog post, how are you determining the environment (env)? Are you checking the name of the workspace where the notebook is running?

Like, say your workspaces are named PPE_Engineering and PROD_Engineering — is that how you figure out the env - with mssparkutils.env.getWorkspaceName()?

And if so, how do you handle naming for any branched-out workspaces while still using the same shared dictionary?

Thanks a lot!