azure-pipelines.yml

# Starter pipeline
# Start with a minimal pipeline that you can customize to build and deploy your code.
# Add steps that build, run tests, deploy, and more:
# https://aka.ms/yaml

trigger:
- master

pool:
  vmImage: 'Ubuntu-16.04'

steps:
- task: UsePythonVersion@0
  displayName: 'Use Python 3.6'
  inputs:
    versionSpec: 3.6
    
- script: |
   pip install flake8
   pip install flake8_formatter_junit_xml
   flake8 --format junit-xml --output-file $(Build.BinariesDirectory)/flake8_report.xml --exit-zero --ignore E111
  displayName: 'Check code quality'
  
- task: PublishTestResults@2
  condition: succeededOrFailed()
  inputs:
    testResultsFiles: '$(Build.BinariesDirectory)/*_report.xml'
    testRunTitle: 'Publish test results'

- task: AzureCLI@1
  inputs:
    azureSubscription: 'build-demo'
    scriptLocation: 'inlineScript'
    inlineScript: 'az extension add -n azure-cli-ml'
    workingDirectory: 'model-training'

- task: AzureCLI@1
  inputs:
    azureSubscription: 'build-demo'
    scriptLocation: 'inlineScript'
    inlineScript: 'az ml folder attach -w build-2019-demo -g scottgu-all-hands'
    workingDirectory: ''

- task: AzureCLI@1
  inputs:
    azureSubscription: 'build-demo'
    scriptLocation: 'inlineScript'
    inlineScript: 'az ml run submit-script -c sklearn -e test -d training-env.yml train-sklearn.py'
    workingDirectory: 'model-training'

- task: AzureCLI@1
  inputs:
    azureSubscription: 'build-demo'
    scriptLocation: 'inlineScript'
    inlineScript: 'az ml model register -n mymodel -p sklearn_regression_model.pkl -t model.json'
    workingDirectory: 'model-deployment'
    
- task: AzureCLI@1
  inputs:
    azureSubscription: 'build-demo'
    scriptLocation: 'inlineScript'
    inlineScript: 'az ml model deploy -n acicicd -f model.json --ic inferenceConfig.yml --dc aciDeploymentConfig.yml --overwrite'
    workingDirectory: 'model-deployment'