Azure Developer CLI (azd) Container Apps Deployment

Overview

This public intake copy packages

plugins/antigravity-awesome-skills-claude/skills/azd-deployment

https://github.com/sickn33/antigravity-awesome-skills

Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.

This intake keeps the copied upstream files intact and uses

metadata.json

ORIGIN.md

Azure Developer CLI (azd) Container Apps Deployment Deploy containerized frontend + backend applications to Azure Container Apps with remote builds, managed identity, and idempotent infrastructure.

Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: Core File Structure, azure.yaml Configuration, Environment Variables Flow, Idempotent Deployments, Container App Service Discovery, Managed Identity & RBAC.

When to Use This Skill

Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.

• This skill is applicable to execute the workflow or actions described in the overview.
• Use when the request clearly matches the imported source intent: Deploy containerized frontend + backend applications to Azure Container Apps with remote builds, managed identity, and idempotent infrastructure.
• Use when the operator should preserve upstream workflow detail instead of rewriting the process from scratch.
• Use when provenance needs to stay visible in the answer, PR, or review packet.
• Use when copied upstream references, examples, or scripts materially improve the answer.
• Use when the workflow should remain reviewable in the public intake repo before the private enhancer takes over.

Operating Table

metadata.json

ORIGIN.md

SKILL.md

SKILL.md

## Related Skills

Workflow

This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.

1. Confirm the user goal, the scope of the imported workflow, and whether this skill is still the right router for the task.
2. Read the overview and provenance files before loading any copied upstream support files.
3. Load only the references, examples, prompts, or scripts that materially change the outcome for the current request.
4. Execute the upstream workflow while keeping provenance and source boundaries explicit in the working notes.
5. Validate the result against the upstream expectations and the evidence you can point to in the copied files.
6. Escalate or hand off to a related skill when the work moves out of this imported workflow's center of gravity.
7. Before merge or closure, record what was used, what changed, and what the reviewer still needs to verify.

Imported Workflow Notes

Imported: Core File Structure

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

Examples

Example 1: Ask for the upstream workflow directly

Use @azd-deployment to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.

Explanation: This is the safest starting point when the operator needs the imported workflow, but not the entire repository.

Example 2: Ask for a provenance-grounded review

Review @azd-deployment against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.

Explanation: Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.

Example 3: Narrow the copied support files before execution

Use @azd-deployment for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.

Explanation: This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.

Example 4: Build a reviewer packet

Review @azd-deployment using the copied upstream files plus provenance, then summarize any gaps before merge.

Explanation: This is useful when the PR is waiting for human review and you want a repeatable audit packet.

Imported Usage Notes

Imported: Quick Start

# 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

Imported: Common Commands

# 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

Best Practices

Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.

• Keep the imported skill grounded in the upstream repository; do not invent steps that the source material cannot support.
• Prefer the smallest useful set of support files so the workflow stays auditable and fast to review.
• Keep provenance, source commit, and imported file paths visible in notes and PR descriptions.
• Point directly at the copied upstream files that justify the workflow instead of relying on generic review boilerplate.
• Treat generated examples as scaffolding; adapt them to the concrete task before execution.
• Route to a stronger native skill when architecture, debugging, design, or security concerns become dominant.

Troubleshooting

Problem: The operator skipped the imported context and answered too generically

Symptoms: The result ignores the upstream workflow in

plugins/antigravity-awesome-skills-claude/skills/azd-deployment

metadata.json

ORIGIN.md

Problem: The imported workflow feels incomplete during review

Symptoms: Reviewers can see the generated

SKILL.md

Problem: The task drifted into a different specialization

Symptoms: The imported skill starts in the right place, but the work turns into debugging, architecture, design, security, or release orchestration that a native skill handles better. Solution: Use the related skills section to hand off deliberately. Keep the imported provenance visible so the next skill inherits the right context instead of starting blind.

Related Skills

• @ai-dev-jobs-mcp

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

• @arm-cortex-expert

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

• @asana-automation

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

• @ask-questions-if-underspecified

  - Use when the work is better handled by that native specialization after this imported skill establishes context.

Additional Resources

Use this support matrix and the linked files below as the operator packet for this imported skill. They should reflect real copied source material, not generic scaffolding.

references

references/n/a

examples

examples/n/a

scripts

scripts/n/a

agents

agents/n/a

assets

assets/n/a

Imported Reference Notes

Imported: Reference Files

• Bicep patterns: See references/bicep-patterns.md for Container Apps modules
• Troubleshooting: See references/troubleshooting.md for common issues
• azure.yaml schema: See references/azure-yaml-schema.md for full options

Imported: azure.yaml Configuration

Minimal Configuration

name: azd-deployment
services:
  backend:
    project: ./src/backend
    language: python
    host: containerapp
    docker:
      path: ./Dockerfile
      remoteBuild: true

Full Configuration with Hooks

name: azd-deployment
metadata:
  template: my-project@1.0.0

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}"

Key azure.yaml Options

remoteBuild: true

context: .

host: containerapp

infra.provider: bicep

Imported: Environment Variables Flow

Three-Level Configuration

1. Local

   .env

   - For local development only

2. .azure/<env>/.env

   - azd-managed, auto-populated from Bicep outputs

3. main.parameters.json

   - Maps env vars to Bicep parameters

Parameter Injection Pattern

// infra/main.parameters.json
{
  "parameters": {
    "environmentName": { "value": "${AZURE_ENV_NAME}" },
    "location": { "value": "${AZURE_LOCATION=eastus2}" },
    "azureOpenAiEndpoint": { "value": "${AZURE_OPENAI_ENDPOINT}" }
  }
}

Syntax:

${VAR_NAME}

${VAR_NAME=default_value}

Setting Environment Variables

# 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 "..." 

Bicep Output → Environment Variable

// 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

Imported: Idempotent Deployments

Why azd up is Idempotent

1. Bicep is declarative - Resources reconcile to desired state
2. Remote builds tag uniquely - Image tags include deployment timestamp
3. ACR reuses layers - Only changed layers upload

Preserving Manual Changes

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

Handling Existing Resources

// 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

Imported: Container App Service Discovery

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;
}

Imported: Managed Identity & RBAC

Enable System-Assigned Identity

resource containerApp 'Microsoft.App/containerApps@2024-03-01' = {
  identity: {
    type: 'SystemAssigned'
  }
}

output principalId string = containerApp.identity.principalId

Post-Provision RBAC Assignment

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

Imported: Critical Reminders

1. Always use

   remoteBuild: true

   - Local builds fail on M1/ARM Macs deploying to AMD64
2. Bicep outputs auto-populate .azure/<env>/.env - Don't manually edit
3. Use

   azd env set

   for secrets - Not main.parameters.json defaults
4. Service tags (

   azd-service-name

   ) - Required for azd to find Container Apps

5. || true

   in hooks - Prevent RBAC "already exists" errors from failing deploy

Imported: Limitations

• Use this skill only when the task clearly matches the scope described above.
• Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
• Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.