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Microsoft Fabric is rapidly evolving as the unified data platform of choice for analytics, engineering, and reporting. But provisioning Fabric infrastructure—workspaces, capacities, lakehouses, and access controls—can become complex and error-prone without automation.

This blog introduces a fully automated Infrastructure-as-Code (IaC) solution built with Terraform and Azure DevOps. Whether you’re a cloud engineer, platform admin, or DevOps lead, this setup empowers you to deploy scalable, secure, and production-ready Fabric infrastructure through reusable modules and CI/CD pipelines.

✅ The Challenge

While Microsoft Fabric provides robust data and analytics capabilities, it currently lacks native automation tooling for setting up infrastructure consistently across environments such as Development, Test, and Production.

Manual deployment introduces:

• Inconsistencies across environments


• Security and access control misconfigurations


• Lack of versioning and reproducibility


• Increased time-to-deploy for new teams or projects

🔧 The Solution — Terraform Modules + Azure DevOps

To address these challenges, we built a modular, Terraform-based solution integrated with Azure DevOps pipelines. The entire setup is declarative, environment-specific, and repeatable—everything as code.

All infrastructure logic is centralized in Terraform modules, stored in a Git repo, and deployed via Azure DevOps CI/CD pipelines, offering full traceability and automation.

🔑 Key Advantages & How This Helps You

🧩 Core Features

1️⃣ Fabric Workspace Provisioning – Automated creation and configuration using Terraform modules
2️⃣ Capacity Assignment – Dynamically map workspaces to assigned capacities
3️⃣ Role-Based Access Control (RBAC) – Grant admin/contributor/viewer roles as per access matrix
4️⃣ Lakehouses & Spark Pools – Provision compute and storage with configurable settings
5️⃣ Modular Architecture – Built with reusable Terraform modules for extensibility
6️⃣ Custom Spark Settings – Automatically set per-workspace Spark configuration
7️⃣ Environment-Specific Configs – Define variables per environment for seamless Dev/Test/Prod parity

⚙️ How It Works

1. Define the desired infrastructure in a terraform.tfvars file


2. Reuse core Terraform modules for Fabric workspace, Spark pool, and role assignment


3. Store configuration files in a Git repo


4. Use an Azure DevOps YAML pipeline to run terraform init, plan, and apply


5. Authenticate via a Service Principal (SPN) with least-privilege access


6. Validate successful deployment via Terraform outputs and logs

🧱Modular Terraform Architecture for Microsoft Fabric

This solution follows a modular Infrastructure-as-Code (IaC) design using Terraform to provision Microsoft Fabric infrastructure. The repository is organized into distinct layers to support environment-specific deployments, clean separation of logic, and CI/CD automation through Azure DevOps.

🧩 How the Modular Approach Works

Each logical unit—like workspace creation, Spark pool setup, or Lakehouse provisioning—is encapsulated in a dedicated Terraform module. This design provides reusability, scalability, and isolation of concerns.

⚙️ Why This Modular Design Matters

• ✅ Clean separation of logic – Easy to maintain and extend


• ✅ Supports multiple environments – Just pass different tfvars


• ✅ Pluggable components – Reuse modules across teams or projects


• ✅ CI/CD friendly – Declarative, auditable, and automatable

💡 Why Terraform?

Terraform empowers you to define cloud infrastructure in code:

• Enables GitOps workflows for Microsoft Fabric setup


• Integrates easily with Azure DevOps and other CI/CD platforms


• Enforces consistency, compliance, and automation


• Promotes reusability across teams and environments

✅ Result

Once deployed, your Microsoft Fabric environment will have:

• Workspaces mapped to correct capacities


• Role assignments enforced via code


• Lakehouses and Spark pools provisioned with required settings


• Centralized logging and traceability through Azure DevOps

🚀 Get Started Today!

Use this solution to:

• Accelerate Fabric workspace provisioning


• Enforce consistent governance policies


• Reduce operational overhead


• Scale your data platform with confidence

Browse the GitHub Repository