Advocate I

3 months ago

Fabric CLI: Command Your Data Platform Like a Pro

Introduction

There's a moment every data engineer knows well: you've got a dozen Fabric workspaces to manage, pipelines to trigger, files to move into OneLake, and deployments to ship — all before standup. Clicking through the Fabric portal is fine for exploration, but when speed, repeatability, and automation matter, you need something sharper.

Meet Fabric CLI (fab) — Microsoft's official open-source command-line interface for Microsoft Fabric. It brings your entire data platform to the terminal, letting you navigate workspaces, run pipelines, manage items, upload data, and wire everything into CI/CD pipelines — all without touching a browser.

This post covers everything you need to get up and running: what Fabric CLI is, why it matters, how to install it, and real command examples you can use today.

What Is the Fabric CLI?

Fabric CLI (fab) is a cross-platform, open-source command-line tool built by Microsoft that gives you direct access to Microsoft Fabric from your terminal. Think of it as a shell that speaks fluent Fabric — it exposes workspaces, lakehouses, pipelines, semantic models, notebooks, and more as a navigable, scriptable file system.

Released as Generally Available (v1.5+), it is fully supported for production use and backed by Microsoft's SLA. It works on:

Windows Terminal
macOS Terminal
Linux shells
GitHub Actions, Azure DevOps Pipelines, and any CI/CD environment

At its core, fab does two things brilliantly: it mirrors familiar shell UX (think ls, cd, cp, rm) applied to Fabric resources, and it exposes automation-ready commands for running and deploying Fabric items at scale.

Why Does Fabric CLI Matter?

1. Speed and Efficiency

Portal navigation is built for discovery. CLI is built for execution. Once you know what you want to do, fab gets you there in a single command.

2. Automation-First Design

Every fab command works identically in your local terminal and in a CI/CD YAML pipeline. There's no "portal-only" escape hatch — everything is scriptable.

3. DevOps Integration

Fabric CLI bridges the gap between data engineering and modern DevOps practices. You can trigger pipelines, promote deployments, and manage Git-backed workspaces directly inside your GitHub Actions or Azure DevOps workflows.

4. Open Source and Extensible

The CLI is open-source on GitHub (microsoft/fabric-cli), meaning the community can contribute, audit, and extend it.

5. Broad Item Coverage

Fabric CLI supports a wide range of Fabric item types: Lakehouses, Notebooks, Data Pipelines, Semantic Models, Warehouses, Dataflows, GraphQL APIs, CosmosDB Databases, SQL Databases, Variable Libraries, Copy Jobs, Power BI Reports, and more.

Installation

Fabric CLI is distributed via PyPI and requires Python 3.8+.

pip install ms-fabric-cli

Verify your installation:

fab --version

You should see output like:

fab version 1.5.x

Tip: If you're using a virtual environment, activate it before installing to keep dependencies clean.

Authentication

Before running any commands, you need to authenticate. Fabric CLI supports three authentication modes.

Interactive Login (Developer / Local)

fab auth login

This opens a browser window for Microsoft Entra ID (Azure AD) sign-in — perfect for day-to-day local use.

Service Principal (CI/CD / Automation)

fab auth login \
  -u $CLIENT_ID \
  -p $CLIENT_SECRET \
  --tenant $TENANT_ID

Use this in GitHub Actions or Azure DevOps secrets for unattended runs.

Managed Identity (Azure-Hosted Runners)

When running on an Azure-hosted machine with a managed identity, authentication is handled automatically — no credentials to manage.

Navigating Your Fabric Environment

Fabric CLI models your Fabric tenant as a navigable file system. If you've used a Unix shell, this will feel immediately natural.

List All Workspaces

fab ls

Output:

Sales Analytics.Workspace
Marketing Data.Workspace
Finance Reporting.Workspace
DevOps Sandbox.Workspace

Explore a Workspace

fab ls "Sales Analytics.Workspace"

Output:

SalesLakehouse.Lakehouse
DailyIngest.DataPipeline
SalesModel.SemanticModel
SalesReport.Report

Detailed Listing

fab ls -l "Sales Analytics.Workspace"

Type              Name                    Modified
----------------- ----------------------- -------------------
Lakehouse         SalesLakehouse          2026-04-28 09:12
DataPipeline      DailyIngest             2026-05-01 14:45
SemanticModel     SalesModel              2026-05-02 08:30
Report            SalesReport             2026-05-02 08:35

Change Working Context

fab cd "Sales Analytics.Workspace"
fab ls

Once you cd into a workspace, all relative paths are scoped to it.

Running Data Pipelines

One of the most powerful everyday uses of Fabric CLI is triggering and monitoring Data Pipelines.

Run a Pipeline

fab run "Sales Analytics.Workspace/DailyIngest.DataPipeline"

Output:

Pipeline run started: run_id=abc123
Status: Running...
Status: Succeeded ✓  (elapsed: 4m 32s)

Run with Input Parameters

fab run "Sales Analytics.Workspace/DailyIngest.DataPipeline" \
  -i '{"param_date": "2026-05-10", "env": "production"}'

Schedule a Pipeline Run

fab job run-sch DailyIngest.datapipeline \
  --type daily \
  --interval "06:00"

Working with Files and OneLake

Fabric CLI makes it trivial to move data between your local machine and OneLake storage inside a Lakehouse.

Upload a Local File to OneLake

fab cp ./data/sales_may.csv \
  "Sales Analytics.Workspace/SalesLakehouse.Lakehouse/Files/sales_may.csv"

Download from OneLake to Local

fab cp \
  "Sales Analytics.Workspace/SalesLakehouse.Lakehouse/Files/sales_may.csv" \
  ./local/downloads/

Sync an Entire Local Folder

fab cp ./reports/ \
  "Sales Analytics.Workspace/SalesLakehouse.Lakehouse/Files/reports/" \
  --recursive

List Files Inside a Lakehouse

fab ls "Sales Analytics.Workspace/SalesLakehouse.Lakehouse/Files/"

Managing Workspaces and Items

Create a New Workspace

fab mkdir "New Project.Workspace"

Delete an Item

fab rm "Sales Analytics.Workspace/OldPipeline.DataPipeline"

Copy an Item Between Workspaces

fab cp \
  "Sales Analytics.Workspace/SalesReport.Report" \
  "Finance Reporting.Workspace/SalesReport.Report"

Deployment with fab deploy

Introduced in v1.5, the deploy command enables one-command deployments across environments — perfect for promoting from dev to staging to production.

Simple Deployment

fab deploy \
  --source "DevOps Sandbox.Workspace" \
  --target "Finance Reporting.Workspace"

Deploy with a Config File

You can define your deployment rules in a deploy.yml:

# deploy.yml
source: DevOps Sandbox.Workspace
target: Finance Reporting.Workspace
items:
  - DailyIngest.DataPipeline
  - SalesModel.SemanticModel
  - SalesReport.Report

Then run:

fab deploy --config deploy.yml

This is especially powerful inside CI/CD pipelines — the same command works locally and in automation.

Power BI Scenarios (New in v1.5)

Fabric CLI v1.5 extended first-class support for Power BI operations.

Rebind a Report to a Different Semantic Model

fab rebind \
  "Finance Reporting.Workspace/SalesReport.Report" \
  --model "Finance Reporting.Workspace/FinanceModel.SemanticModel"

Refresh a Semantic Model

fab refresh \
  "Sales Analytics.Workspace/SalesModel.SemanticModel"

Update Report Properties

fab set \
  "Sales Analytics.Workspace/SalesReport.Report" \
  --property "description" \
  --value "Updated May 2026 sales metrics"

CI/CD Integration

Where Fabric CLI truly shines is in automated pipelines. Here's a complete GitHub Actions workflow that authenticates, runs a pipeline, and deploys on merge to main.

# .github/workflows/fabric-deploy.yml

name: Fabric Deploy

on:
  push:
    branches:
      - main

jobs:
  deploy-fabric:
    runs-on: ubuntu-latest

    steps:
      - name: Checkout code
        uses: actions/checkout@v4

      - name: Install Fabric CLI
        run: pip install ms-fabric-cli

      - name: Authenticate with Service Principal
        run: |
          fab auth login \
            -u ${{ secrets.FABRIC_CLIENT_ID }} \
            -p ${{ secrets.FABRIC_CLIENT_SECRET }} \
            --tenant ${{ secrets.FABRIC_TENANT_ID }}

      - name: Run data ingest pipeline
        run: |
          fab run "Sales Analytics.Workspace/DailyIngest.DataPipeline"

      - name: Deploy to Production workspace
        run: |
          fab deploy --config deploy.yml

And the equivalent in Azure DevOps Pipelines:

# azure-pipelines.yml

trigger:
  branches:
    include:
      - main

pool:
  vmImage: ubuntu-latest

steps:
  - script: pip install ms-fabric-cli
    displayName: Install Fabric CLI

  - script: |
      fab auth login \
        -u $(FABRIC_CLIENT_ID) \
        -p $(FABRIC_CLIENT_SECRET) \
        --tenant $(FABRIC_TENANT_ID)
    displayName: Authenticate

  - script: |
      fab run "Sales Analytics.Workspace/DailyIngest.DataPipeline"
    displayName: Run Pipeline

  - script: |
      fab deploy --config deploy.yml
    displayName: Deploy to Production

Configuration and Debugging

Enable Debug Logging

When something goes wrong, verbose output is your best friend:

fab config set debug_enabled true

Now all CLI commands will output detailed request/response information.

Set a Default Capacity

If you're always working against the same capacity, set it once:

fab config set default_capacity "My Production Capacity"

Dry-Run Mode

Preview what a command will do before executing it:

fab run "Sales Analytics.Workspace/DailyIngest.DataPipeline" --dry-run

This is invaluable for validating automation scripts before they touch production.

Check Current Auth Status

fab auth status

When to Use Fabric CLI vs. the Portal

The portal and CLI are complementary. Start in the portal when exploring; switch to the CLI when you need speed, repeatability, or automation.

Getting Started Checklist

pip install ms-fabric-cli — install the CLI
fab auth login — authenticate with your Microsoft account
fab ls — explore your workspaces
fab ls -l "Your Workspace.Workspace" — inspect a workspace in detail
fab run "Your Workspace.Workspace/YourPipeline.DataPipeline" — trigger your first pipeline
Store credentials as secrets and add fab to your CI/CD pipeline

Resources

General