Fabric: Trigger Data Pipeline after Deployment

[Rocco_Praelexis]

Hi,

I'm still getting to grips with Fabric, trying to figure out what functionality is supported and what isn't.

In my current use-case, I have two workspaces, namely dev and prod. I have configured a deployment pipeline, without a testing phase, from dev to prod. Each workspace contains the same lakehouses (which were originally generated in prod by the deployment pipeline). From my understanding, data contained within lakehouses are not copied to the prod workspace, and that this is intentional. However, for my purposes, I would very much like the data from dev to be in prod.

I've found that I can copy the data using a data pipeline that sources from the dev workspace lakehouse and uses the analogous prod workspace lakehouse as the destination. This is working. So the question is: is there any way to automate the running of the data pipeline which copies the data after deployment in the deployment pipeline between the workspaces?

Additionally, if there is more obvious, pragmatic, or best practices way to solve this issues than what I'm currently doing, please let me know!

Regards

[Anonymous · Accepted solution]

Hi @Rocco_Praelexis ,

Thanks for using Fabric Community.
As I understand you are using Deployment Pipeline to move changes from Dev Workspace to Prod Workspace.
Currently there is no way to trigger or schedule a Deployment Pipeline, expect for Power BI related items.

Automate your deployment pipeline by using APIs and Azure DevOps - Microsoft Fabric | Microsoft Lear...

And coming to you ask - " is there any way to automate the running of the data pipeline which copies the data after deployment in the deployment pipeline between the workspaces? "

Unfortunately we cannot do this in fabric right now. 

However if you want this feature to be enable please provide your feedback.

Appreciate if you can provide feedback: Microsoft Idea  on our feedback channel. Which would be open for the user community to upvote & comment on. This allows our product teams to effectively prioritize your request against our existing feature backlog and gives insight into the potential impact of implementing the suggested feature.

At present we cannot automate this, you need to perform a manual trigger to data pipeline after completion of deployment pipeline.

I hope this information helps. Please do let us know if you have any further questions.

[Anonymous]

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