When working with Power BI reports, ensuring smooth deployment without disruptions is crucial. Have you ever made changes to a report, only for it to break in production, leading to a flood of messages asking, “Why isn’t my report working?” Fortunately, Microsoft Fabric Deployment Pipelines provide a structured approach to testing and deploying updates before they reach end-users.
Overview of Deployment Pipelines
Microsoft Fabric’s Deployment Pipelines provide a structured way to manage and synchronize Power BI content across multiple workspaces. By enabling users to test changes before they go live, these pipelines help maintain report integrity and minimize disruptions. A deployment pipeline can include anywhere from two to ten stages, with each stage linked to a dedicated workspace. Within these workspaces, items are paired, creating systematic associations across different pipeline stages. Pairing ensures that updates made in earlier stages are accurately propagated through subsequent environments.
How Pairing Works
- New Items: Items added after a workspace is assigned to a pipeline stage must be manually paired.
- Duplication: If an item is not paired, a duplicate copy is created instead of overwriting the existing one.
- Renamed Items: Once paired, items remain paired even if their names change.
This pairing mechanism ensures consistency and helps maintain a seamless deployment process.
Supported Items in Deployment Pipelines
Fabric’s deployment pipelines support a variety of Power BI and Fabric assets, including:
- Activator
- Dashboards
- Data Pipelines (Preview)
- Dataflows Gen2 (Preview)
- Datamarts (Preview)
- Environments (Preview)
- Eventhouse and KQL Databases
- EventStreams (Preview)
- KQL Querysets
- Lakehouses (Preview)
- Mirrored Databases (Preview)
- Notebooks
- Org Apps (Preview)
- Paginated Reports
- Power BI Dataflows
- Real-Time Dashboards
- Reports (based on supported semantic models)
- Semantic Models (originating from a .pbix file, not a PUSH dataset)
- SQL Databases (Preview)
- Warehouses (Preview)
By leveraging deployment pipelines, organizations can improve collaboration, reduce errors, and maintain version control, ensuring that Power BI reports remain stable and fully functional throughout their lifecycle.
Setting Up Deployment Pipelines
Here is a walkthrough of how you can setup your own Fabric deployment pipeline. In this scenario, we will be leveraging the deployment pipeline to promote a Power BI report.
Prerequisites
Before setting up your deployment pipeline, there are several prerequisites.:
- You have a Microsoft Fabric subscription
- You’re an admin of a Fabric workspace
Or
- You have one of the following licenses:
- You’re a Power BI Pro user, and you belong to an organization that has Premium capacity.
- Premium Per User (PPU).
- You’re an admin of a new workspace experience.
Pipeline Setup
In Power BI Service, setup an individual workspace for each stage you would like to create.
Once your workspaces are setup, click on “Deployment pipelines”.
Click on “New pipeline”.
Name your pipeline, then click “Next”.
By default, three stages (Development, Test, & Production) will be created. From here, you can rename stages or add additional stages. Once your stages are setup, click on “Create and continue”.
Now that the stages have been created, assign the created workspaces to their respective stages.
You have successfully created your deployment pipeline. Now we will review how to deploy items.
Deployment Process
In my current development workspace, I have two items. I have a semantic model and a sales report. These items currently do not exist in my test and production environments.
To deploy an item through stages, navigate to the deployment pipelines section.
Then click on the respective deployment pipeline.
Select the environment you would like to deploy to, the items you would like to deploy, and then click “Deploy”. You will also notice that the pipeline provides information comparing the items in their source and target environments.
Once deployed, you can follow these steps for the additional stages.
Real-World Application
In practice, when making changes, you should first apply them in your development environment. Once validated, you can promote these changes to the next environment, adding an extra layer of verification to ensure production-critical items remain unaffected.
Using the pipeline we created as an example, let’s say I update my sales report and have several users validate the changes. Once the updates are validated, I can promote them to the production stage, where end-users access their reports.
During this process, deployment pipelines provide insights into differences between environments and warn me before overwriting anything in the next stage.
Implementing a structured deployment pipeline ensures a smooth transition of changes from development to production while minimizing risks. By validating updates at each stage, you can catch potential issues early and prevent disruptions in critical environments. Additionally, deployment pipelines provide visibility into environment differences and safeguard against unintended overwrites. Following this approach enhances reliability, streamlines workflows, and ensures a seamless experience for end-users.
Sources
- Microsoft Learn: What is deployment pipelines?
- Microsoft Learn: Create and manage a Power BI deployment pipeline
- Microsoft Learn: Get started with deployment pipelines
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