Deployment in different destinations

This section explains the configuration steps to deploy a report across stages that use different destinations.

Consider an EDITABLE visual available in the Azure SQL database in the 'Dev' stage. For demonstration purposes, let's assume we need to deploy the report to the Fabric Warehouse and Fabric SQL databases for the 'Test' and 'Prod' stages, respectively.

This can be accomplished by following the steps below:

1. Create EDITable reports: Create EDITable visuals that you want to deploy in these data destinations. Ensure to create them under the same schema with the same table name and column names.

2. Deploy the report in the Power BI pipeline: Deploy the report and its corresponding semantic model from 'Dev' to 'Test' and 'Test' to 'Prod' in the Power BI pipeline initially.

3. Configure deployment rules: Configure the data source deployment rules for your semantic model in the Power BI pipeline.

4. Add report: Add the report in the EDITable pipeline.

5. Configure destinations: Configure the required deployment destinations in the EDITable pipeline.

6. Deploy the report in the EDITable pipeline: Deploy the report using EDITable pipeline to update the report as it progresses.

1. Create EDITable reports

The first step is to create the reports in the required destinations. Here, we'll create in the Fabric Warehouse and Fabric SQL destinations. You can refer to this section for the steps to create them.

Creating a table in Fabric Warehouse:

Creating a table in Fabric SQL:

The images below show the tables created at different destinations. You can notice that they are under the same schema and have the same table name and columns.

Creating tables in different destinations

2. Deploy the report in the Power BI pipeline

Deploy the report and its corresponding semantic model from 'Dev' to 'Test' and 'Test' to 'Prod' in the Power BI pipeline, by clicking Deploy across stages.

Deploy the report

In the next step, we will configure the data sources for each stage by configuring deployment rules.

3. Configure deployment rules

Next, we will be defining data source rules for our semantic model (EmployeeDetails) to point to the different databases instead of the one in the 'Dev' stage. The rule is defined in the testing and production stages under the appropriate semantic model. Once the rule is defined, content deployed from development to test and test to production inherits the value as defined in the deployment rule. Learn more about configuring deployment rules here.

Data source rules for the 'Test' stage

Please note that these deployment rules only take effect the next time you deploy to that stage. Deploy the report once to update the available connections.

Data source rules for the 'Prod' stage

4. Add report

Now add this report to the EDITable pipeline by following the steps explained here: Add Report.

5. Configure destinations

Now, let us configure the report and their respective destinations in the 'Test' and 'Prod' stages. To do so, edit the pipeline using the pencil icon as highlighted below.

Edit pipeline stages

Select the required connections from the drop-down list, then select the table 'EmployeeDetails', which we have already created. Click Update.

Configure destinations

6. Deploy the report in the EDITable pipeline

Click Deploy to deploy the report from 'Dev' to 'Test' and from 'Test' to 'Prod' stages. The test and production stages now point to the configured destinations.

Deploy report in EDItable pipeline

You can now use this pipeline to deploy report changes in stages to the appropriate databases.

In the following section, we will look at other pipeline options as well as how to trigger deployment from external applications via an API endpoint.