--- title: Fabric Lakehouse - Deployment description: Deploy the generated artifacts of a Fabric Lakehouse project with deploy.ps1. --- [Skip to content](https://knowledge.bigenius-x.com/fabric-lakehouse-deployment-2.0#main-content) [Contact us](https://knowledge.bigenius-x.com/kb-tickets/new?hsLang=en) [Go to Customer Portal](https://knowledge.bigenius-x.com/customer-portal?hsLang=en) [![TRI\_Logo\_biGENIUS\_2020\_RGB\_s](https://knowledge.bigenius-x.com/hs-fs/hubfs/Marketing/TRI_Logo_biGENIUS_2020_RGB_s.png?width=150&height=42&name=TRI_Logo_biGENIUS_2020_RGB_s.png)](https://www.bigenius-x.com/) Open main navigation Close main navigation - [Contact us](https://knowledge.bigenius-x.com/kb-tickets/new) - [Go to Customer Portal](https://knowledge.bigenius-x.com/customer-portal) How can we help you? - There are no suggestions because the search field is empty. 1. [biGENIUS-X Knowledge Base](https://knowledge.bigenius-x.com/?hsLang=en) 2. [Generators](https://knowledge.bigenius-x.com/generators?hsLang=en) 3. [Deployment](https://knowledge.bigenius-x.com/generators?hsLang=en#deployment) # Fabric Lakehouse - Deployment **Applies to** Platform: Fabric Lakehouse Deploy the generated artifacts of a Fabric Lakehouse project with `deploy.ps1`. The script uploads the notebooks to your Fabric workspace and runs the notebook `_deploy`, which creates the load control log tables and the objects of every layer. Afterwards the solution is ready to load. The procedure applies to all Fabric Lakehouse generator configurations with Target Platform `Fabric`. For Target Platform `Azure Synapse`, see [Azure Synapse - Deployment](https://knowledge.bigenius-x.com/azure-synapse-deployment-2.0?hsLang=en). ### Prerequisites - The [Fabric Lakehouse target environment](https://knowledge.bigenius-x.com/fabric-lakehouse-target-environment?hsLang=en) is prepared. - PowerShell 7. The script installs the module Az.Accounts when it is missing. - The artifacts are [generated](https://knowledge.bigenius-x.com/generate-artifacts?hsLang=en) and [downloaded](https://knowledge.bigenius-x.com/download-generated-artifacts?hsLang=en). - The placeholders are [replaced](https://knowledge.bigenius-x.com/replace-the-placeholders-in-the-artifacts?hsLang=en) with the [Fabric Lakehouse placeholder values](https://knowledge.bigenius-x.com/fabric-lakehouse-placeholder-values-2.0?hsLang=en), including a `schema_name` for every layer and for the load control. - The client ID, a client secret and the tenant ID of the service principal. ### Deploy the artifacts 1. Open PowerShell 7 in the artifacts folder, the folder that contains `deploy.ps1`. With the default Deployment Options, Generate Drop Table Statements is selected. Each deployment replaces every generated table and the load control log tables, which deletes their data. This also applies when deploy.ps1 runs the deployment after the upload. Before you deploy to a target that holds data, clear Generate Drop Table Statements in Project Settings and generate the artifacts again. 2. Run `.\deploy.ps1`. 3. At `Please specify the workspace name`, enter the name of the workspace. ![PowerShell after .\\deploy.ps1 with the prompt Please specify the workspace name](https://knowledge.bigenius-x.com/hs-fs/hubfs/image-png-Mar-25-2026-08-55-41-8224-AM.png?width=640&height=91&name=image-png-Mar-25-2026-08-55-41-8224-AM.png) 4. At `Please specify the folder`, enter a workspace folder for the notebooks, or leave it empty for the root folder. The script creates a missing folder. 5. At `Please specify the service principle user name`, enter the client ID of the service principal. 6. At `Please specify the service principle password`, enter the client secret. 7. At `Please specify the Azure tenant ID`, enter the tenant ID. 8. Wait until the script prints `Finished`. It runs `_deploy` as a notebook job and prints its status every 15 seconds. The script sets the first lakehouse it finds in the workspace as the default lakehouse of every notebook, without asking, and prints its name. To skip the prompts, pass the values as parameters: ``` .\deploy.ps1 -WorkspaceName -Folder -UserName -Password -TenantId ``` Type the call on one line. With an empty user name, the script asks for the tenant and subscription ID and signs you in through the browser. It also uploads an [Apache Airflow DAG](https://knowledge.bigenius-x.com/fabric-lakehouse-load-data-apache-airflow-load-control?hsLang=en) when one is generated. With `-SkipDeployment`, the script only uploads. Then open the notebook `_deploy` in Fabric and run all cells: ![Notebook deploy with two cells: notebook.run of deploy\_loadcontrol with timeout 120 and of Deployment with timeout 3600](https://knowledge.bigenius-x.com/hs-fs/hubfs/image-png-Dec-17-2025-10-22-24-1566-AM.png?width=670&height=110&name=image-png-Dec-17-2025-10-22-24-1566-AM.png) ### Check the result The deployment succeeded when the script prints `Deployment job run completed successfully` before `Finished`. The workspace folder then holds the notebooks: ![Workspace folder StageJDBC with the notebooks deploy, deploy\_1, deploy\_loadcontrol, Deployment, MultithreadingLoadExecution, SelectResults and a loader](https://knowledge.bigenius-x.com/hs-fs/hubfs/image-png-Mar-25-2026-09-16-52-9423-AM.png?width=670&height=254&name=image-png-Mar-25-2026-09-16-52-9423-AM.png) The lakehouse shows a schema per layer and one for the load control. To count the deployment steps, run this query in a notebook, with the lakehouse and schema of the load control: ``` SELECT log_level, COUNT(*) AS row_count FROM ..deployment_log GROUP BY log_level; ``` ### Example A DataVault and Mart project was deployed to the lakehouse `my_lakehouse`, which has schemas, with the schemas `stage`, `rawvault`, `businessvault`, `mart` and `loadcontrol`. The output starts like this, shortened: ``` Running deploy.ps1 ... -> using workspace my_workspace -> using folder my_folder -> using user name and password for service principal ... Lakehouse my_lakehouse found with id (used as default lakehouse) - Please ensure that all referenced lakehouses exist! Setting default lakehouse my_lakehouse on notebook test_vaultandmart_spark_fabric_deploy... Uploading new notebook test_vaultandmart_spark_fabric_deploy ... Deployment job run status: NotStarted. Checking again in 15 seconds... ``` Long lines are wrapped here. The notebook ran for about five minutes and created the five schemas. The query above returned: ``` log_level row_count INFO 17 ``` ### Redeploy and keep data To deploy a changed project into a lakehouse with data: 1. In [Project Settings](https://knowledge.bigenius-x.com/manage-project-settings-and-generator-configuration?hsLang=en), clear `Generate Drop Table Statements` in [Deployment Options](https://knowledge.bigenius-x.com/deployment-options-project?hsLang=en). 2. Generate, download and replace the placeholders with the same values, then run `.\deploy.ps1` with the same workspace and folder. `deploy.ps1` updates the notebooks of the same names and runs `_deploy`. The notebooks then create tables and log tables with `CREATE TABLE IF NOT EXISTS` and insert missing unknown-member rows only. Views are created with `CREATE OR REPLACE VIEW`. Column changes are not applied to existing tables. With Generate Create Schema If Not Exists Statements also cleared, the schemas must exist. Notebooks that the project no longer generates stay in the workspace. ### Failure symptoms and recovery When the script prints `Deployment job run failed`, read the error of the failed cell in the run of `_deploy`. #### The load control deployment fails with a namespace error Message: `[REQUIRES_SINGLE_PART_NAMESPACE] spark_catalog requires a single-part namespace, but got .` Cause: The targets are in a lakehouse with schemas, but `deploy.ps1` set a lakehouse without schemas as default lakehouse of the notebooks. Fix: Make the lakehouse with schemas the default lakehouse of every uploaded notebook and run `_deploy` again. #### The schema of the load control cannot be created Message: `[REQUIRES_SINGLE_PART_NAMESPACE] spark_catalog requires a single-part namespace, but got ``.``` or `Failed to get database metadata` Cause: The load control `schema_name` is empty, and Generate Create Schema If Not Exists Statements is selected. The statement `CREATE SCHEMA` then fails in every lakehouse. Fix: Enter a `schema_name` for the load control and every layer, replace the placeholders again and run `.\deploy.ps1`. For failures in other steps, see [Troubleshoot generation, deployment and load failures](https://knowledge.bigenius-x.com/troubleshoot-generation-deployment-and-load-failures?hsLang=en). ### Release differences - Generator 2.2: `deploy.ps1` sets the default lakehouse of the notebooks. Up to Generator 2.0, add the lakehouse in each notebook before you run it: **Data items**, **Add data items**, **From OneLake catalog**. - Generator 1.10: the artifacts contain the notebook `_deploy`, see [Legacy manual deployment](https://knowledge.bigenius-x.com/fabric-lakehouse-deployment-2.0#legacy-manual-deployment). #### Legacy manual deployment Up to Generator 1.9, the artifacts had no notebook `_deploy`. You ran the notebook `Jupyter\_Deployment` from a notebook of your own with `%run`. With Generator 1.9, you also ran `LoadControl\_Deployment_LoadControl` the same way. ### Related articles - Previous: [Fabric Lakehouse - Target environment](https://knowledge.bigenius-x.com/fabric-lakehouse-target-environment?hsLang=en), [Generate artifacts](https://knowledge.bigenius-x.com/generate-artifacts?hsLang=en), [Download generated artifacts](https://knowledge.bigenius-x.com/download-generated-artifacts?hsLang=en), [Replace the placeholders in the artifacts](https://knowledge.bigenius-x.com/replace-the-placeholders-in-the-artifacts?hsLang=en) - Next: [Fabric Lakehouse - Load data - Native Load Control](https://knowledge.bigenius-x.com/fabric-lakehouse-load-data-native-load-control-2.0?hsLang=en), [Fabric Lakehouse - Load data - Apache Airflow Load Control](https://knowledge.bigenius-x.com/fabric-lakehouse-load-data-apache-airflow-load-control?hsLang=en) - Reference: [Fabric Lakehouse - Placeholder values](https://knowledge.bigenius-x.com/fabric-lakehouse-placeholder-values-2.0?hsLang=en), [Deployment Options (Project)](https://knowledge.bigenius-x.com/deployment-options-project?hsLang=en), [Notebook Deployment Objects Limit (Project)](https://knowledge.bigenius-x.com/notebook-deployment-objects-limit-project?hsLang=en), [Target Platform (Project)](https://knowledge.bigenius-x.com/target-platform-project?hsLang=en) - 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