Test your Microsoft Fabric Migration Deployment

After you deploy and orchestrate your workloads into Microsoft Fabric and configure all necessary supporting services (like Lakehouses, Pipelines, Warehouses, etc.), it's crucial to test the migration in an isolated and controlled way. This ensures both the architecture and operational readiness of the migrated workload.

Focus of Fabric Migration Testing

In Microsoft Fabric, testing focuses on two critical domains:

• Architecture validation: Ensure that Lakehouse structures, pipeline flows, data model compatibility, and integration with external sources (e.g., SQL DBs, APIs, Eventstreams) work as expected.
• Operational readiness: Validate logging, alerting, governance policies (via Microsoft Purview), and permissions (via Entra ID and Fabric workspaces).

This is distinct from business testing and is driven by platform engineers and data product teams.

Perform Fabric Test Migrations

Since Microsoft Fabric workloads are predominantly data platform workloads, test migration means staging data pipelines, dataflows, and Lakehouses in a sandbox workspace or dedicated development workspace.

• Use Deployment Pipelines or Git-based deployment in Fabric to deploy to a development or test workspace.
• Simulate source system ingestion via Dataflows Gen2, Eventstreams, or Shortcuts to OneLake.
• Validate warehouse scripts, DAX metrics, and visuals inside Power BI artifacts.

Requirements for the Test Environment

• A dedicated Fabric workspace for testing (can be part of the Deployment Pipeline).
• Test credentials or service principals with scoped access.
• Simulated source datasets (e.g., via test CSV files in OneLake, synthetic data pipelines).
• Clear separation from production environments (no shared Lakehouses or shortcuts pointing to prod data).

Example Test Plan

Test	Successful/Unsuccessful	Note
Lakehouse deployed	✅	Lake structure, schema in place
SQL Analytics endpoint responds	✅	Queries work as expected
Pipeline ingests CSV from OneLake	✅	Data arrives and is shaped
KQL query on Eventhouse works	✅	Live data streaming verified
DAX measures in Power BI visual	✅	Numbers match expectation
Scheduled refresh of Power BI dataset	❌	Missing gateway connection
Lineage view in Purview	✅	Traceability validated
Data access policies applied	✅	RLS tested in Power BI

Remediate Testing Problems

Record all issues in your remediation backlog and prioritize based on:

• Severity of the impact (blocking vs. cosmetic)
• Ability to implement a workaround before release
• Dependencies on other teams or services

Align remediation tracking with your existing DevOps tooling (e.g., Azure DevOps, GitHub Issues).

Next Steps

Once all technical issues are addressed and the test plan is validated, proceed to the Release phase, which includes stakeholder signoff, business testing, and full production promotion.