Skip to content
datastudyguides

DP-600 · 1.2.3 · Maintain a data analytics solution

Deployment pipelines

Create and configure deployment pipelines

Move Fabric item definitions through Development, Test, and Production while adapt each target environment.

The core idea

Fabric deployment pipeline moving item definitions from Development to Test to Production, with deployment rules for data sources, parameters, and notebook default lakehouses.

A promotes Fabric items through stage workspaces, usually Development, Test, and Production. Deployments copy item definitions and metadata, not the underlying data or environment-specific credentials.

belong to the target stage. Use them to switch data sources, parameter values, or a 's default .

Fabric pairs matching items across stages. Missing dependencies can block deployment, while unpaired look-alike items can create duplicates.

Key points

  • Stages: each stage maps to its own workspace
  • Deploy: item definitions move to the adjacent stage
  • Rules: target stages can swap sources, parameters, or
  • Data: permissions, credentials, schedules, and data are not copied

Click an underlined term for a one-line explanation, or see them all in the glossary .

Exam trap

A new changes nothing until the next deployment to that stage, and it cannot be created in the Development stage.

Sources · 3 Microsoft Learn pages Show ▾

Checked on October 4, 2026. Report a problem

Go deeper on Microsoft Learn

Checked against Microsoft Learn on October 4, 2026. Report a problem with this card

How well do you know this?