Deploy containerized applications to Azure Container Apps using Azure Developer CLI (azd). Use when setting up azd projects, writing azure.yaml configuration, creating Bicep infrastructure for Container Apps, configuring remote builds with ACR, implementing idempotent deployments, managing environment variables across local/.azure/Bicep, or troubleshooting azd up failures. Triggers on requests for azd configuration, Container Apps deployment, multi-service deployments, and infrastructure-as-code with Bicep.
数据来源:ClawHub。 在 ClawSkills 查看
选择你使用的 Agent
方法一:命令行安装(推荐)
推荐(无需提前安装 clawhub)
npx clawhub@latest --dir ~/.claude/skills install azd-deployment或使用 clawhub CLI(需提前安装)
clawhub --dir ~/.claude/skills install azd-deployment⚠️ 需要 Node.js 18+,没有 Node?请使用下方方法二直接下载 ZIP。 安装 Node.js →
方法二:手动下载安装(无需 Node)
下载 ZIP,解压后将文件夹放到以下路径,重启 Agent 即可:
安装路径
~/.claude/skills/azd-deployment/💡解压后将文件夹放到上方路径,重启 Agent 即可生效
--- name: azd-deployment description: Deploy containerized applications to Azure Container Apps using Azure Developer CLI (azd). Use when setting up azd projects, writing azure.yaml configuration, creating Bicep infrastructure for Container Apps, configuring remote builds with ACR, implementing idempotent deployments, managing environment variables across local/.azure/Bicep, or troubleshooting azd up failures. Triggers on requests for azd configuration, Container Apps deployment, multi-service deployments, and infrastructure-as-code with Bicep. ---
Deploy containerized frontend + backend applications to Azure Container Apps with remote builds, managed identity, and idempotent infrastructure.
# Initialize and deploy
azd auth login
azd init # Creates azure.yaml and .azure/ folder
azd env new <env-name> # Create environment (dev, staging, prod)
azd up # Provision infra + build + deploy
project/
├── azure.yaml # azd service definitions + hooks
├── infra/
│ ├── main.bicep # Root infrastructure module
│ ├── main.parameters.json # Parameter injection from env vars
│ └── modules/
│ ├── container-apps-environment.bicep
│ └── container-app.bicep
├── .azure/
│ ├── config.json # Default environment pointer
│ └── <env-name>/
│ ├── .env # Environment-specific values (azd-managed)
│ └── config.json # Environment metadata
└── src/
├── frontend/Dockerfile
└── backend/Dockerfile
name: azd-deployment
services:
backend:
project: ./src/backend
language: python
host: containerapp
docker:
path: ./Dockerfile
remoteBuild: true
name: azd-deployment
metadata:
template: [email protected]
infra:
provider: bicep
path: ./infra
azure:
location: eastus2
services:
frontend:
project: ./src/frontend
language: ts
host: containerapp
docker:
path: ./Dockerfile
context: .
remoteBuild: true
backend:
project: ./src/backend
language: python
host: containerapp
docker:
path: ./Dockerfile
context: .
remoteBuild: true
hooks:
preprovision:
shell: sh
run: |
echo "Before provisioning..."
postprovision:
shell: sh
run: |
echo "After provisioning - set up RBAC, etc."
postdeploy:
shell: sh
run: |
echo "Frontend: ${SERVICE_FRONTEND_URI}"
echo "Backend: ${SERVICE_BACKEND_URI}"
| Option | Description | |--------|-------------| | remoteBuild: true | Build images in Azure Container Registry (recommended) | | context: . | Docker build context relative to project path | | host: containerapp | Deploy to Azure Container Apps | | infra.provider: bicep | Use Bicep for infrastructure |
.env - For local development only.azure//.env - azd-managed, auto-populated from Bicep outputsmain.parameters.json - Maps env vars to Bicep parameters// infra/main.parameters.json
{
"parameters": {
"environmentName": { "value": "${AZURE_ENV_NAME}" },
"location": { "value": "${AZURE_LOCATION=eastus2}" },
"azureOpenAiEndpoint": { "value": "${AZURE_OPENAI_ENDPOINT}" }
}
}
Syntax: ${VAR_NAME} or ${VAR_NAME=default_value}
# Set for current environment
azd env set AZURE_OPENAI_ENDPOINT "https://my-openai.openai.azure.com"
azd env set AZURE_SEARCH_ENDPOINT "https://my-search.search.windows.net"
# Set during init
azd env new prod
azd env set AZURE_OPENAI_ENDPOINT "..."
// In main.bicep - outputs auto-populate .azure/<env>/.env
output SERVICE_FRONTEND_URI string = frontend.outputs.uri
output SERVICE_BACKEND_URI string = backend.outputs.uri
output BACKEND_PRINCIPAL_ID string = backend.outputs.principalId
Custom domains added via Portal can be lost on redeploy. Preserve with hooks:
hooks:
preprovision:
shell: sh
run: |
# Save custom domains before provision
if az containerapp show --name "$FRONTEND_NAME" -g "$RG" &>/dev/null; then
az containerapp show --name "$FRONTEND_NAME" -g "$RG" \
--query "properties.configuration.ingress.customDomains" \
-o json > /tmp/domains.json
fi
postprovision:
shell: sh
run: |
# Verify/restore custom domains
if [ -f /tmp/domains.json ]; then
echo "Saved domains: $(cat /tmp/domains.json)"
fi
// Reference existing ACR (don't recreate)
resource containerRegistry 'Microsoft.ContainerRegistry/registries@2023-07-01' existing = {
name: containerRegistryName
}
// Set customDomains to null to preserve Portal-added domains
customDomains: empty(customDomainsParam) ? null : customDomainsParam
Internal HTTP routing between Container Apps in same environment:
// Backend reference in frontend env vars
env: [
{
name: 'BACKEND_URL'
value: 'http://ca-backend-${resourceToken}' // Internal DNS
}
]
Frontend nginx proxies to internal URL:
location /api {
proxy_pass $BACKEND_URL;
}
resource containerApp 'Microsoft.App/containerApps@2024-03-01' = {
identity: {
type: 'SystemAssigned'
}
}
output principalId string = containerApp.identity.principalId
hooks:
postprovision:
shell: sh
run: |
PRINCIPAL_ID="${BACKEND_PRINCIPAL_ID}"
# Azure OpenAI access
az role assignment create \
--assignee-object-id "$PRINCIPAL_ID" \
--assignee-principal-type ServicePrincipal \
--role "Cognitive Services OpenAI User" \
--scope "$OPENAI_RESOURCE_ID" 2>/dev/null || true
# Azure AI Search access
az role assignment create \
--assignee-object-id "$PRINCIPAL_ID" \
--role "Search Index Data Reader" \
--scope "$SEARCH_RESOURCE_ID" 2>/dev/null || true
# Environment management
azd env list # List environments
azd env select <name> # Switch environment
azd env get-values # Show all env vars
azd env set KEY value # Set variable
# Deployment
azd up # Full provision + deploy
azd provision # Infrastructure only
azd deploy # Code deployment only
azd deploy --service backend # Deploy single service
# Debugging
azd show # Show project status
az containerapp logs show -n <app> -g <rg> --follow # Stream logs
...
安装 Azd Deployment for Azure 后,可以对 AI 说这些话来触发它
Help me get started with Azd Deployment for Azure
Explains what Azd Deployment for Azure does, walks through the setup, and runs a quick demo based on your current project
Use Azd Deployment for Azure to deploy containerized applications to Azure Container Apps using Azu...
Invokes Azd Deployment for Azure with the right parameters and returns the result directly in the conversation
What can I do with Azd Deployment for Azure in my developer & devops workflow?
Lists the top use cases for Azd Deployment for Azure, with example commands for each scenario
将技能文件夹放到 ~/.claude/skills/azd-deployment/ 目录(个人级,所有项目可用),或 .claude/skills/azd-deployment/(项目级)。重启 AI 客户端后,用 /azd-deployment 主动调用,或让 AI 根据上下文自动发现并使用。
Azd Deployment for Azure 支持 Claude、Cursor、OpenClaw,可与这些 AI 平台无缝集成,扩展其能力。
Azd Deployment for Azure 可免费安装使用。请查阅仓库了解许可证信息。
Deploy containerized applications to Azure Container Apps using Azure Developer CLI (azd). Use when setting up azd projects, writing azure.yaml configuration, creating Bicep infrastructure for Container Apps, configuring remote builds with ACR, implementing idempotent deployments, managing environment variables across local/.azure/Bicep, or troubleshooting azd up failures. Triggers on requests for azd configuration, Container Apps deployment, multi-service deployments, and infrastructure-as-code with Bicep.
Automate my developer & devops tasks using Azd Deployment for Azure
Identifies repetitive steps in your workflow and sets up Azd Deployment for Azure to handle them automatically
Azd Deployment for Azure 属于「Developer & DevOps」分类,该分类的技能帮助 AI 智能体在此领域执行专业任务。