Conduct periodic access reviews and certifications. Implement access governance and recertification workflows. Use when managing access compliance.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Set up Azure Pipelines for CI/CD, configure build and release pipelines, manage Azure DevOps projects, and integrate with Azure services. Use when working with Azure DevOps Services or Server for enterprise DevOps workflows.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Build, test, and deploy applications using Azure Pipelines with YAML or classic editor.
Use this skill when:
Create azure-pipelines.yml in repository root:
trigger:
branches:
include:
- main
- develop
paths:
include:
- src/*
pool:
vmImage: 'ubuntu-latest'
variables:
buildConfiguration: 'Release'
nodeVersion: '20.x'
stages:
- stage: Build
jobs:
- job: BuildJob
steps:
- task: NodeTool@0
inputs:
versionSpec: $(nodeVersion)
- script: |
npm ci
npm run build
displayName: 'Build application'
- publish: $(Build.ArtifactStagingDirectory)
artifact: drop
- stage: Deploy
dependsOn: Build
condition: and(succeeded(), eq(variables['Build.SourceBranch'], 'refs/heads/main'))
jobs:
- deployment: DeployWeb
environment: 'production'
strategy:
runOnce:
deploy:
steps:
- script: echo Deploying to production
trigger:
branches:
include:
- main
- release/*
exclude:
- feature/*
tags:
include:
- v*
pr:
branches:
include:
- main
paths:
include:
- src/*
exclude:
- docs/*
schedules:
- cron: '0 2 * * *'
displayName: 'Nightly build'
branches:
include:
- main
always: true
stages:
- stage: Test
jobs:
- job: UnitTests
pool:
vmImage: 'ubuntu-latest'
steps:
- script: npm run test:unit
- job: IntegrationTests
pool:
vmImage: 'ubuntu-latest'
steps:
- script: npm run test:integration
jobs:
- job: Build
strategy:
matrix:
linux:
vmImage: 'ubuntu-latest'
windows:
vmImage: 'windows-latest'
mac:
vmImage: 'macos-latest'
pool:
vmImage: $(vmImage)
steps:
- script: npm test
stages:
- stage: Build
jobs:
- job: A
steps:
- script: echo Job A
- job: B
dependsOn: A
steps:
- script: echo Job B
variables:
- group: 'production-secrets'
- name: buildConfiguration
value: 'Release'
parameters:
- name: environment
displayName: 'Environment'
type: string
default: 'dev'
values:
- dev
- staging
- prod
stages:
- stage: Deploy
variables:
env: ${{ parameters.environment }}
jobs:
- job: Deploy
steps:
- script: echo "Deploying to $(env)"
variables:
- name: mySecret
value: $(SECRET_FROM_PIPELINE) # Set in pipeline settings
steps:
- script: |
echo "Using secret"
./deploy.sh
env:
API_KEY: $(mySecret)
# templates/build-job.yml
parameters:
- name: nodeVersion
default: '20'
jobs:
- job: Build
steps:
- task: NodeTool@0
inputs:
versionSpec: ${{ parameters.nodeVersion }}
- script: npm ci && npm run build
# azure-pipelines.yml
stages:
- stage: Build
jobs:
- template: templates/build-job.yml
parameters:
nodeVersion: '20'
# templates/deploy-stage.yml
parameters:
- name: environment
type: string
- name: serviceConnection
type: string
stages:
- stage: Deploy_${{ parameters.environment }}
jobs:
- deployment: Deploy
environment: ${{ parameters.environment }}
strategy:
runOnce:
deploy:
steps:
- task: AzureWebApp@1
inputs:
azureSubscription: ${{ parameters.serviceConnection }}
appName: 'myapp-${{ parameters.environment }}'
stages:
- stage: DeployStaging
jobs:
- deployment: DeployWeb
environment: 'staging'
strategy:
runOnce:
deploy:
steps:
- download: current
artifact: drop
- script: ./deploy.sh staging
Configure in Azure DevOps UI:
jobs:
- deployment: Deploy
environment: 'production'
strategy:
rolling:
maxParallel: 2
deploy:
steps:
- script: ./deploy.sh
- task: AzureWebApp@1
inputs:
azureSubscription: 'my-azure-connection'
appType: 'webAppLinux'
appName: 'my-web-app'
package: '$(Pipeline.Workspace)/drop/*.zip'
- task: AzureContainerApps@1
inputs:
azureSubscription: 'my-azure-connection'
containerAppName: 'my-container-app'
resourceGroup: 'my-rg'
imageToDeploy: 'myregistry.azurecr.io/myapp:$(Build.BuildId)'
- task: KubernetesManifest@0
inputs:
action: 'deploy'
kubernetesServiceConnection: 'my-aks-connection'
namespace: 'default'
manifests: |
$(Pipeline.Workspace)/manifests/deployment.yml
$(Pipeline.Workspace)/manifests/service.yml
containers: |
myregistry.azurecr.io/myapp:$(Build.BuildId)
- task: Docker@2
inputs:
containerRegistry: 'my-acr-connection'
repository: 'myapp'
command: 'buildAndPush'
Dockerfile: '**/Dockerfile'
tags: |
$(Build.BuildId)
latest
# Download agent
mkdir myagent && cd myagent
curl -o vsts-agent.tar.gz https://vstsagentpackage.azureedge.net/agent/3.227.2/vsts-agent-linux-x64-3.227.2.tar.gz
tar zxvf vsts-agent.tar.gz
# Configure
./config.sh --url https://dev.azure.com/myorg --auth pat --token PAT_TOKEN --pool default
# Run as service
sudo ./svc.sh install
sudo ./svc.sh start
pool:
name: 'my-self-hosted-pool'
demands:
- docker
- Agent.OS -equals Linux
Problem: Cannot authenticate to Azure Solution: Verify service principal permissions, check connection in project settings
Problem: Download artifact fails Solution: Ensure publish task ran successfully, check artifact name matches
Problem: Deployment to environment fails Solution: Create environment in Pipelines > Environments first
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Conduct periodic access reviews and certifications. Implement access governance and recertification workflows. Use when managing access compliance.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Build automated evaluation suites for AI agents using golden datasets, rubrics, and regression gates. Use when shipping agent features, validating prompt changes, or gating deployments on quality.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Instrument AI agents with tracing, token metrics, latency, and cost visibility. Use for reliability and debugging.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Secure AI agents against prompt injection, tool abuse, and data exfiltration with defense-in-depth controls. Use when building, deploying, or hardening agentic AI systems that invoke tools, access data, or interact with production infrastructure.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Secure AI coding agents (Claude Code, Cursor, Codex, Copilot) with permission boundaries, secret protection, code review gates, and safe sandbox configurations for team environments.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use service mesh patterns for AI inference traffic management, mTLS, canary releases, policy enforcement, and cross-cluster resilience.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.