Gradle or Maven project

Using YAML or the Azure Classic editor to create the Azure build pipeline with new Gradle or Maven tasks.

Before you begin, see the Azure Pipelines integration overview page.

Once you have created and set up your SonarQube Community Build project, check out the Creating and configuring your project and Setting up project integration pages for information about adding the SonarQube analysis to your Azure build pipeline.

To create your Azure build pipeline, you can use either YAML or the Azure Classic editor.

• The use of the Classic editor is not always possible (e.g. if your code is stored on GitHub).

• If you use YAML, Sonar can provide you with YAML templates or code examples.

About the analysis parameter setup

Analysis parameters can be set at different levels; see the Configuring the project analysis parameters article for details. You must define the project key in the Prepare Analysis Configuration task of your pipeline. You may define additional parameters in this task the same way. In that case, these parameters have precedence over parameters defined at the project or global level.

Using YAML

1. Add the SonarQube analysis run to your build task.

2. Add the following SonarQube tasks:

   • Before your build task, add a Prepare Analysis Configuration task.

   • After your build task, add a Run Code Analysis task.

   • After the Rune Code Analysis task, add a Publish Quality Gate Result task.

By default, the scanner version used will be the one specified in your Maven/Gradle build configuration, see SonarScanner for Maven or SonarScanner for Gradle. You can overwrite it by using the sqMavenPluginVersionChoice or sonarQubeGradlePluginVersion input in your pipeline’s Execute build task.

See the YAML file example below. See also our YAML pipeline templates. For information about the SonarQube task inputs, check the SonarQube tasks for Azure Pipelines page.

Make sure the SonarQube task version used in your YAML file is the correct one. For example, in SonarQubePrepare@7, 7 should correspond to the version of the Azure DevOps extension you’re using.

YAML file example

trigger:
- master # or the name of your main branch
- feature/*

steps:
 # Checkout the repository
 - checkout: self

 # Disable shallow fetch
  fetchDepth: 0

# Prepare Analysis Configuration task
- task: SonarQubePrepare@7
  inputs:
    SonarQube: '<YourSonarqubeEndpoint>'
    scannerMode: 'other'
    extraProperties: 'sonar.projectKey=<YourProjectKey>'

# If you use Gradle: add the Execute Gradle build as shown below
- task: Gradle@3
   inputs:
      sonarQubeRunAnalysis: true

# If you use Maven: add the Execute Maven goal as shown below
 - task: Maven@4
      inputs:
      sonarQubeRunAnalysis: true

# Publish Quality Gate Result task
- task: SonarQubePublish@7
  inputs:
    pollingTimeoutSec: '300'

Using the Classic editor

1. In the Azure DevOps’ Classic editor, create or update your build pipeline.

2. Add a Prepare Analysis Configuration task before your build task:

• In SonarQube Service Endpoint, select the SonarQube Server service connection you created during setup. See the Setting up project integration page for more information about adding a connection.

• Under Choose a way to run the analysis, select Integrate with Maven or Gradle.

• Expand the Advanced section and replace the Additional Properties with the following snippet:

# Additional properties that will be passed to the scanner,
# Put one key=value per line, example:
# sonar.exclusions=**/*.bin
sonar.projectKey=<YourProjectKey>
sonar.projectName=<YourProjectName>

3. Add a new Maven or Gradle task:

• Under Code Analysis, check Run SonarQube or SonarCloud Analysis.

4. Add a new Publish quality gate result task on your build pipeline summary.

5. Ensure that the pipeline runs automatically for all the branches you want: Under the Triggers tab of your pipeline, select Enable continuous integration and select all the branches for which you want SonarQube Community Build analysis to run automatically.

6. Save your pipeline.

Related pages

• .NET project

• JS, TS, Go, Python, PHP, etc. project

• Using various features when adding the analysis to your pipeline

• Quality gate status in release pipeline

• SonarQube tasks for Azure Pipelines