Liquibase Enterprise can be integrated with Azure DevOps to deploy your database code. Visit the Azure DevOps website to learn more about https://learn.microsoft.com/en-us/azure/devops/pipelines/?view=azure-devops.

This document explains how to setup an Azure pipeline with an agent to execute Liquibase Enterprise operations. An Azure DevOps agent can be shared among multiple projects, so one agent can serve several teams. You can learn more about Azure agents here: https://learn.microsoft.com/en-us/azure/devops/pipelines/agents/agents?view=azure-devops&tabs=browser.

Additionally we’ll show how Liquibase Enterprise forecast and deploy commands can run via an Azure Release using a Classic release pipeline: https://learn.microsoft.com/en-us/azure/devops/pipelines/release/?view=azure-devops

Instructions

1 Instructions

Sample Repo

A sample public GitHub repo can be found here:

Prerequisites

Before following the steps in this document, setup your databases and create the Liquibase project.

Liquibase Enterprise requires two repositories which are referred to as Repos in Azure DevOps. Azure Pipelines can be built from code stored in Azure Repos, Bitbucket, GitHub, and other Git or Subversion sources. For this example we will be using Azure Repos.

In Azure Repos create the following two projects:

The Liquibase Project repository.
The SQL code repository.

This example also uses 2 optional repos:

A centralized Rules repository.
- When using a centralized Rules repository be sure to include the following in the .gitignore of the Liquibase Project repository.
  - Rules/
A centralized CI/CD repository.

Push the Liquibase project configuration files to the project repository in Azure Repos.

git init --initial-branch=main
git remote add origin git@ssh.dev.azure.com:v3/asmith0101/Liquibase/ABC_DDB
git push -u origin --all
git add .
git commit -m "Initial commit"
git push -u origin main

Step 1: Setup an Azure Agent Pool

Instructions:

An Azure Agent Pool can be created under Project Settings. Agent pools are shared across an organization.

Step 2: Create an Azure Agent

Instructions:

After setting up an Agent Pool you can create a New agent. Instructions will be provided for the type of agent (Windows or Linux) that you wish to use. Note there are also Detailed Instructions for each of the types. Make sure to use a supported version of Windows or Linux.

Step 3: Setup authentication from the Agent to the Repositories

This example uses SSH keys for git authentication. You can find information on using SSH keys with Azure at .

If you wish to use HTTPS for git authentication you will need to setup Git Credential Manager. Instructions can be found at .

Step 4: Install Liquibase Enterprise on the Agent

Follow these instructions to install Liquibase Enterprise:

Windows:
Linux:

Make sure that git is installed on the agent as it will be needed by the Liquibase Enterprise Deploy Packager.

Step 5: Setup an Azure Key Vault with the database credentials

Instructions:

The Azure Key Vault is a secure method for storing database credentials. It is recommended that you add Key Vault secrets for all databases in your pipeline including the DMC database.

In this example, Secrets added in the Key Vault will be referenced by the pipeline using Variable Groups.

Step 6: Setup an Azure Library Variable Group

Instructions: and

Use an Azure Library to group credentials from your Key Vault into a Variable Group. This grouping makes it easy to associate credentials to Azure Pipelines and Releases.

Step 7: Create a Pipeline to run Packager

Create an Azure Pipeline to run the Deploy Packager (Build) job. Azure Pipelines are created from an azure_pipelines.yml file.

azure_pipelines.yml file

trigger: none

name: $(Application.Name)-$(Build.BuildId)

variables:
- template: ./variables.yml 
- group: Liquibase_Variables

pool:
   name: $(Agent.PoolName)

workspace:
      clean: all

resources:         
  repositories:

  - repository: DDB_REPOSITORY
    name: ABC_DDB
    type: git
    connection: AzureRepos
    source: ABC_DDB
    ref: 'refs/heads/main'

  - repository: SQL_REPOSITORY
    name: ABC_SQL
    type: git
    connection: AzureRepos
    source: ABC_SQL
    ref: 'refs/heads/current'

  - repository: CICD_REPOSITORY
    name: Liquibase/DB_CICD_PIPELINES
    type: git
    connection: AzureRepos
    source: Liquibase/DB_CICD_PIPELINES
    ref: 'refs/heads/main'
 
  - repository: CENTRALIZED_RULES_REPOSITORY
    name: Liquibase/CENTRALIZED_RULES
    type: git
    connection: AzureRepos
    source: Liquibase/CENTRALIZED_RULES
    ref: 'refs/heads/main'

steps:
- checkout: DDB_REPOSITORY
  persistCredentials: true
  clean: true
- checkout: SQL_REPOSITORY
  clean: true
  fetchDepth: 100
  persistCredentials: true
- checkout: CENTRALIZED_RULES_REPOSITORY
  clean: true
  persistCredentials: true
  
- script: |
    whoami
    hammer show version
    echo $(System.DefaultWorkingDirectory)
  displayName: 'Run Prechecks'
 
# Ensure the PATH includes the necessary executables, eg. hammer and sqlplus/sqlcmd/clpplus/psql
# Also copy the Rules from the Centralized rules folder to the DDB folder
- powershell: |
    $Env:Path += ";C:\Users\Administrator\DaticalDB\repl"
    $Env:Path += ";C:\Program Files\Microsoft SQL Server\Client SDK\ODBC\170\Tools\Binn\"
    cd $(Git.Repository)
    xcopy /s/e/y ..\CENTRALIZED_RULES\Rules\. .\Rules\*
  condition: eq( variables['Agent.OS'], 'Windows_NT' )
  displayName: 'Update PATH (Windows) and set Rules'
  
- script: |
    export PATH="$PATH:/opt/datical/DaticalDB/repl"
    export PATH="$PATH:/opt/mssql-tools/bin"
    cd $(Git.Repository)
    cp -R ../CENTRALIZED_RULES/Rules .
  condition: eq( variables['Agent.OS'], 'Linux' )
  displayName: 'Update PATH (Linux) and set Rules'
  
- script: |
    cd $(Git.Repository) 
    hammer groovy deployPackager.groovy pipeline=current commitPrefix="[skip ci]" scm=true labels=$(Build.BuildId),current
    if [ $? -ne 0 ]; then exit 1; fi
  displayName: 'Run Liquibase packager'
  env:
    DDB_USER: $(Liquibase-abc-ref1-User)
    DDB_PASS: $(Liquibase-abc-ref1-Pass)
    DDB_DMCDB_USER: $(Liquibase-abc-dmc-User)
    DDB_DMCDB_PASS: $(Liquibase-abc-dmc-Pass)

# Compress files into .zip
- task: ArchiveFiles@2
  inputs:
    rootFolderOrFile: '$(System.DefaultWorkingDirectory)/$(Git.Repository)'
    includeRootFolder: true
    archiveType: 'zip'
    archiveFile: '$(System.DefaultWorkingDirectory)/artifacts/$(Application.Name)-$(Build.BuildId).zip'

- upload: $(System.DefaultWorkingDirectory)/artifacts/$(Application.Name)-$(Build.BuildId).zip
  artifact: drop

- task: ArtifactoryGenericUpload@2
  inputs:
    artifactoryService: 'ArtifactoryCS'
    specSource: 'taskConfiguration'
    fileSpec: |
      {
        "files": [
          {
            "pattern": "artifacts/$(Application.Name)-$(Build.BuildId).zip",
            "target": "$(Project.Name)/$(Application.Name)/"
          }
        ]
      }
    replaceSpecVars: true
    specVars: '$(Application.Name),$(Build.BuildId)'
    collectBuildInfo: true
    buildName: '$(Build.DefinitionName)'
    buildNumber: '$(Build.BuildNumber)'
    module: '$(Project.Name)'
    failNoOp: true
  displayName: 'Upload zip to artifactory'

- task: ArtifactoryPublishBuildInfo@1
  inputs:
    artifactoryService: 'ArtifactoryCS'
    buildName: '$(Build.DefinitionName)'
    buildNumber: '$(Build.BuildNumber)'
  displayName: 'Publish Build Info to artifactory'

- task: ArtifactoryBuildPromotion@1
  inputs:
    artifactoryService: 'ArtifactoryCS'
    buildName: '$(Build.DefinitionName)'
    buildNumber: '$(Build.BuildNumber)'
    targetRepo: '$(Project.Name)'
    status: 'Released'
    sourceRepo: '$(Project.Name)'
    includeDependencies: false
    copy: false
    dryRun: false
  displayName: 'Promote Build to artifactory'

- task: AzureKeyVault@2
  inputs:
    azureSubscription: 'CustomerSuccessPayAsGo'
    KeyVaultName: 'cs-key-vault1'
    SecretsFilter: '*'
    RunAsPreJob: true

variables.yml file

Step 8: Create a Release to run Forecast and Deploy Jobs

Instructions:

Azure Releases can be used to run the Liquibase Enterprise Forecast and Deploy jobs. These jobs will pull the repository from an Artifact.

Under Releases select + NEW to create a New Release Pipeline. Add an artifact. This example uses a JFrog Artifactory artifact. For JFrog Artifactory you will need to have setup an Artifactory Service, see .

For the Build Name, select the build pipeline you created in Step 7.

Step 9: Configure your Release Pipeline

In this example we have setup the following workflow:

Deploy to DEV → Forecast to Test → Deploy to Test → Forecast to Prod → Deploy to Prod

Under the Variables section, make sure to Link the Variable Group created in Step 6.

Each step represents a Stage in the Pipeline.

Configure a Forecast Stage

For each Forecast Stage, select the Agent that will be used to run the job. Be sure to select the Agent Pool configured in Step 1.

Each Azure Stage is comprised of Tasks. Use a Command line task to run the Liquibase Enterprise hammer commands. (Please note, use of Windows agents may require slightly different task types or script code. Eg. Powershell may be required.)

Be sure to unzip the artifact prior to running the hammer commands.
You’ll need to specify the Working Directory under the Advanced section.
You’ll also want to set DDB_USER, DDB_PASS, DDB_DMCDB_USER, and DDB_DMCDB_PASS under the Environment Variables section. These values will be set to the name of the vault values, eg. $(Liquibase-abc-dev-User), $(Liquibase-abc-dev-Pass), $(Liquibase-abc-dmc-User), $(Liquibase-abc-dmc-Pass)

Script Code:

Configure a Deploy Stage

A Deploy Stage will be identical to a Forecast stage with the exception of the Script Code.

For Deploys use the following:

Step 10: Test your Pipeline

Commit a change to the packaging branch in your SQL repo. Go to your Pipeline in Azure and select “Run pipeline”.

After all your pipeline steps have completed successfully, your artifact will be ready to run a Release.

Go to Releases and select “Create release”.
Select all the stages to run.
Specify the Artifact Version to run. Select the most recent.
You’ll need to click on the Stages to trigger them. You’ll need to click “Deploy”. (Please note this “Deploy” terminology is from Azure. Even the Liquibase Enterprise Forecast will be triggered via a “Deploy” button.)

Troubleshooting

ERROR: Error getting list of commits; Invalid revision range; unknown revision or path not in the working tree

Problem: One of the following messages appears when executing the pipeline:

ERROR: Error getting list of commits
ERROR: fatal: Invalid revision range

ERROR: fatal: ambiguous argument '158902d..HEAD': unknown revision or path not in the working tree.

Resolution

Azure Devops has a default GitHub fetch depth of 1 commit. This causes a problem of not being able to find the sqlScmLastImportID specified in deployPackager.properties. Updating the sqlScmLastImportID in the latest commit results in a temporary one-off success.

A large fetchDepth can affect performance of the pipeline over time, especially if large commits are made to the SQL repo. For example, a fetchDepth of '0' can be used to get all commits in the branch, but doing this every time could be wasteful of resources as time goes on, or if there are large commits: ( ).

This parameter might require tuning or intervention over time if the error appears again. We recommend starting with a relatively low value, say 100, for maintaining a consistent rolling window of 100 commits. While this setting can be made using the UI for basic pipelines with no YAML definition, it should be made directly in the pipeline YAML where checkout steps are defined.

Below is an example of the usage of fetchDepth:

Liquibase Enterprise Knowledge Base

How To: Use Liquibase Enterprise with Azure DevOps

Instructions

Sample Repo

Prerequisites

Step 1: Setup an Azure Agent Pool

Step 2: Create an Azure Agent

Step 3: Setup authentication from the Agent to the Repositories

Step 4: Install Liquibase Enterprise on the Agent

Step 5: Setup an Azure Key Vault with the database credentials

Step 6: Setup an Azure Library Variable Group

Step 7: Create a Pipeline to run Packager

azure_pipelines.yml file

variables.yml file

Step 8: Create a Release to run Forecast and Deploy Jobs

Step 9: Configure your Release Pipeline

Configure a Forecast Stage

Configure a Deploy Stage

Step 10: Test your Pipeline

Troubleshooting

ERROR: Error getting list of commits; Invalid revision range; unknown revision or path not in the working tree