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MicrosoftKnown publishermicrosoft-foundry/foundry-agent-webapp/.github/skills/deploying-to-azure/SKILL.md

deploying-to-azure

Skill124 starsChanged 7 months agoMITView on GitHub

Provides deployment commands and troubleshooting for Azure Container Apps. Use when running azd commands, deploying containers, debugging deployment failures, or updating infrastructure in this repository.

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    Change resource: Run azd provision to re-run discovery, or:

    line 86

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SKILL.md

Deploying to Azure

Subagent Delegation for Deployment Analysis

Container logs and deployment output can be massive (1000+ lines). Delegate to subagent for:

  • Analyzing full deployment logs
  • Debugging container startup failures
  • RBAC permission troubleshooting
  • Multi-resource status checks

Delegation Pattern

runSubagent(
  prompt: "ANALYSIS task - analyze deployment issue.
    
    **Problem**: [describe the deployment failure]
    
    **Run these commands**:
    1. az containerapp logs show --name <app> --resource-group <rg> --tail 200
    2. az containerapp show --name <app> --resource-group <rg> --query 'properties.provisioningState'
    
    **Find**:
    - Error messages or stack traces
    - Resource provisioning failures
    - Configuration mismatches
    
    **Return** (max 15 lines):
    - Root cause (1-2 sentences)
    - Key error lines only (max 5)
    - Suggested fix command
    
    Do NOT include full log output.",
  description: "Debug: [deployment issue]"
)

When to Delegate vs Inline

Delegate to SubagentKeep Inline
Full log analysis (100+ lines)Quick status check
Multi-resource debuggingSingle az command
RBAC permission auditContainer image query
Startup failure diagnosisProvisioning state check

Quick Commands

CommandPurposeTime
azd upFull deployment (Entra app + infrastructure + container)10-12 min
azd deployCode-only deployment (Docker rebuild + push)3-5 min
azd provisionRe-run infrastructure + AI Foundry discovery5-7 min

Deployment Phases

  1. preprovision → AI Foundry auto-discovery + tenant detection. For CI: azd env set ENTRA_SERVICE_MANAGEMENT_REFERENCE "<guid>"
  2. provision → Deploy Azure resources via Bicep (infrastructure + Entra app via Microsoft Graph Bicep extension + placeholder container image)
  3. postprovision → Sets identifierUri on Entra app + updates redirect URIs + assigns RBAC to AI Foundry + generates local dev config
  4. predeploy → Builds container (local Docker or ACR cloud build)

Implementation:

  • infra/entra-app.bicep (Entra app registration via Microsoft Graph Bicep extension)
  • deployment/hooks/preprovision.ps1 (AI Foundry discovery)
  • deployment/hooks/postprovision.ps1 (Entra config + RBAC + local config generation)
  • deployment/hooks/predeploy.ps1 (container build + push)
  • deployment/hooks/modules/Get-AIFoundryAgents.ps1 (agent discovery via REST)

Docker Multi-Stage Build

Build order: React → .NET → Runtime

  • Frontend: deployment/docker/frontend.Dockerfile
  • Backend: deployment/docker/backend.Dockerfile
  • Custom npm registries: Add .npmrc to frontend/ directory

AI Foundry Resource Configuration

Auto-discovery (azd up): Searches subscription for AI Foundry resources → prompts to select if multiple → discovers agents via REST API → configures RBAC.

Change resource: Run azd provision to re-run discovery, or:

azd env set AI_FOUNDRY_RESOURCE_GROUP <rg>
azd provision

Container Infrastructure

  • Health Probes: Liveness (GET /api/health every 30s) and startup (GET /api/health every 10s, 5s initial delay) probes configured on the Container App
  • ACR Pull: Uses a user-assigned managed identity with AcrPull role — no admin credentials or secrets. The MI is created in main-infrastructure.bicep before the Container App, avoiding the chicken-and-egg problem.
  • Resource Defaults: 0.5 vCPU, 1GB RAM, 0-3 replicas (all parameterized in container-app.bicep)

Troubleshooting

IssueFix
VITE_ENTRA_SPA_CLIENT_ID not setRun azd up to generate .env files
AI_AGENT_ENDPOINT not configuredRun azd provision to re-discover AI Foundry
No AI Foundry resources foundCreate at https://ai.azure.com
Multiple AI Foundry resourcesRun azd provision to select different resource
Container not updatingCheck az containerapp logs show --name $app --resource-group $rg
Container fails health checkVerify /api/health endpoint returns 200 — check container logs for startup errors

Useful Commands

# Check current container image
az containerapp show --name $app --resource-group $rg `
    --query "properties.template.containers[0].image"

# View container logs
az containerapp logs show --name $app --resource-group $rg --tail 100

# Check RBAC assignments
$principalId = az containerapp show --name $app --resource-group $rg `
    --query "identity.principalId" -o tsv
az role assignment list --assignee $principalId

Preprovision Hook Details

File: deployment/hooks/preprovision.ps1

What it does:

  1. Discovers AI Foundry resources in subscription (prompts if multiple)
  2. Discovers agents via REST API using Get-AIFoundryAgents.ps1
  3. Auto-detects tenant ID
  4. Sets azd environment variables

Note: Entra app registration is handled by Bicep (infra/entra-app.bicep), not this hook.

Postprovision Hook Details

File: deployment/hooks/postprovision.ps1

What it does:

  1. Sets identifierUri (api://{clientId}) on Entra app — can't be done in Bicep because it references the auto-generated appId
  2. Updates Entra app redirect URIs (localhost + Container App FQDN)
  3. Assigns Cognitive Services User role to Container App's managed identity on AI Foundry resource (via Azure CLI, not Bicep)
  4. Generates local dev config files (.env.local for frontend, .env for backend)

Why RBAC via CLI?: Using Azure CLI for role assignment prevents azd from tracking the external AI Foundry resource group, avoiding accidental deletion on azd down.

Predeploy Hook Details

File: deployment/hooks/predeploy.ps1

What it does:

  1. Detects if Docker is available and running
  2. Uses local Docker build + push if available (~2 min)
  3. Falls back to ACR cloud build if Docker unavailable (~4-5 min)
  4. Updates Container App with new image (if it exists)
  5. Sets SERVICE_WEB_IMAGE_NAME env var for Bicep

Dockerfile Example

File: deployment/docker/frontend.Dockerfile (production build)

# Stage 1: Build React Frontend
FROM node:22-alpine AS frontend-builder
ARG ENTRA_SPA_CLIENT_ID
ARG ENTRA_TENANT_ID
WORKDIR /app/frontend
COPY frontend/ ./
RUN npm ci
# Remove local .env files to prevent localhost config
RUN rm -f .env.local .env.development .env
ENV NODE_ENV=production
ENV VITE_ENTRA_SPA_CLIENT_ID=$ENTRA_SPA_CLIENT_ID
ENV VITE_ENTRA_TENANT_ID=$ENTRA_TENANT_ID
RUN npm run build

# Stage 2: Build .NET Backend
FROM mcr.microsoft.com/dotnet/sdk:10.0 AS backend-builder
WORKDIR /app
COPY backend/WebApp.sln ./
COPY backend/WebApp.Api/WebApp.Api.csproj ./backend/WebApp.Api/
COPY backend/WebApp.ServiceDefaults/WebApp.ServiceDefaults.csproj ./backend/WebApp.ServiceDefaults/
RUN dotnet restore backend/WebApp.Api/WebApp.Api.csproj
COPY backend/ ./backend/
RUN dotnet publish backend/WebApp.Api/WebApp.Api.csproj -c Release -o /app/publish

# Stage 3: Runtime - Single container serving API + static files
FROM mcr.microsoft.com/dotnet/aspnet:10.0-alpine
WORKDIR /app
COPY --from=backend-builder /app/publish ./
COPY --from=frontend-builder /app/frontend/dist ./wwwroot
EXPOSE 8080
ENV ASPNETCORE_URLS=http://+:8080
ENV ASPNETCORE_ENVIRONMENT=Production
ENTRYPOINT ["dotnet", "WebApp.Api.dll"]

Related Skills

  • writing-csharp-code - Backend coding patterns for Container App configuration
  • writing-bicep-templates - Infrastructure templates for Azure resources
  • troubleshooting-authentication - Entra ID and RBAC debugging

Official Documentation

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