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JacobJoo
New Member

Issue with Deployment movement from QA to Prod

Hello Community,

We’re currently facing challenges while moving artifacts from lower environments to higher environments (QA to Prod). We tried using deployment pipelines, but it became quite messy and feels risky—especially since we only need to move around 20–30 pipelines.

At the moment, we’re handling this manually by downloading the JSON files and recreating the pipelines in the higher environment using the same templates.

Could you please suggest a better and safer approach for handling these deployments?

 

Thank you in advance.

1 ACCEPTED SOLUTION
deborshi_nag
Community Champion
Community Champion

Hello @JacobJoo 

 

The challenges you’re encountering with deployment on Fabric are quite typical. While your current approach is effective, it does involve additional manual effort.

 

I suggest implementing GIT integration for your workspaces, with only the Dev environment set to writable and QA and Prod configured as read-only from their respective GIT branches.

 

Additionally, be sure to parameterise all environment-specific variables and references, such as Lakehouse names, Warehouses, and SQL endpoints.

 

For promoting to higher environments, it is preferable to use Pull Requests rather than deployment pipelines.

 

I trust this will be helpful. If you found this guidance useful, you are welcome to acknowledge with a Kudos or by marking it as a Solution.

View solution in original post

5 REPLIES 5
v-nmadadi-msft
Community Support
Community Support

Hi @JacobJoo 

May I check if this issue has been resolved? If not, Please feel free to contact us if you have any further questions.


Thank you

v-nmadadi-msft
Community Support
Community Support

Hi @JacobJoo 

I wanted to check if you had the opportunity to review the valuable information provided by @AntoineW , @chetanhiwale , @deborshi_nag . Please feel free to contact us if you have any further questions.
Thank you.

AntoineW
Super User
Super User

If you have harcoded parameters in pipelines, you could use : Variable Library to specify sources and destination for copy data to different lakehouse in your different workspace, it automate all this process.

 

Check this reference :

- https://learn.microsoft.com/en-us/fabric/data-factory/variable-library-integration-with-data-pipelin...

https://learn.microsoft.com/en-us/fabric/cicd/variable-library/get-started-variable-libraries?tabs=h...

 

chetanhiwale
Resolver I
Resolver I

Hi @JacobJoo , 
There are two ways you can approach here. 
1. Deployment pipelines. 
As you mentioned you have atleast 20 pipelines which might grow later, you can still use the pipeline by selectung the master pipeline and then selecting the related items button. This should select all other pipelines related to it. We have tried this method when we need to move/copy pipelines from one to another workspace. 

2. Git.
Most standard method is to use Git integration only. Have different branches for both workspaces and follow the regular git process. Although there is no staging here we need to commit directly. So first commit, then get it approved then push it another higher env and at last sync the higher env workspace.


If you need quick fix and need to move items/artifacts in linear fashion , deployment pipeline still works. But it not track who is done what and when. It is the limation which comes by Deployment pipelines. Otherwise use git integration. It is most efficeint way till now. 


Hope this helps. Let me know if you have any doubt, we can discuss.

deborshi_nag
Community Champion
Community Champion

Hello @JacobJoo 

 

The challenges you’re encountering with deployment on Fabric are quite typical. While your current approach is effective, it does involve additional manual effort.

 

I suggest implementing GIT integration for your workspaces, with only the Dev environment set to writable and QA and Prod configured as read-only from their respective GIT branches.

 

Additionally, be sure to parameterise all environment-specific variables and references, such as Lakehouse names, Warehouses, and SQL endpoints.

 

For promoting to higher environments, it is preferable to use Pull Requests rather than deployment pipelines.

 

I trust this will be helpful. If you found this guidance useful, you are welcome to acknowledge with a Kudos or by marking it as a Solution.

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