• Bot code tested locally with Bot Framework Emulator.
• Environment variables for AZURE_OPENAI_ENDPOINT, DEPLOYMENT_ID, and API_KEY correctly referenced.
• Docker container runs successfully on localhost:3978.

• Resource Group created or selected.
• Azure Container Registry (ACR) created and admin access enabled (if not using managed identity).
• Azure OpenAI Service created with deployed model (e.g., gpt-35-turbo).

• Docker image built with docker build -t <image> ..
• Docker image tagged with ACR address.
• Docker image pushed to ACR.

• Parameter values prepared, either inline or in containerapp-params.json.
• Verified API Key, OpenAI endpoint, and deployment ID.
• Verified ACR server, username, and password (if required).

• Bicep template validated with az bicep build.
• Deployment executed with either inline parameters or parameter file.
• Verified Container App is running in Azure Portal.

• Verified public URL responds (default port 3978).
• Connected Bot Framework Emulator to Container App URL.
• Tested conversation flow using OpenAI backend.

• Confirmed ACR access is secured.
• Configured auto-scaling (if needed).
• Applied secure ingress settings (HTTPS, auth if needed).

• Log Analytics Workspace attached.
• Application logging enabled and verified in Azure Monitor.

• Log Analytics Workspace created and linked to Container App Environment.
• App Logs verified in Log Analytics > Logs with queries like:

AppContainerAppConsoleLogs_CL \\
| where ContainerAppName_s == "<your-container-app-name>"\\
| sort by TimeGenerated desc

• Metrics monitoring verified (CPU, Memory, Request Count).

• Alert Rule for CPU Usage
  • Example: Alert if CPU exceeds 80% for 5 minutes.
• Alert Rule for Memory Usage
  • Example: Alert if Memory exceeds 75% for 5 minutes.
• Alert Rule for HTTP 500 Errors
  • Example: Query for failed requests in Log Analytics.

AppContainerAppConsoleLogs_CL
| where Log_s contains "500"
| summarize Count = count() by bin(TimeGenerated, 5m)

1. Go to Azure Monitor > Alerts.
2. Click + New Alert Rule.
3. Select Resource: Your Container App or Log Analytics Workspace.
4. Condition: Add a metric or log query condition.
5. Action Group: Create or select action groups (email, Teams, webhook, etc.).
6. Alert Details: Name and severity.

• Notification Channels Configured
  • Email
  • Teams
  • Webhook (optional)

param containerAppResourceId string
param logAnalyticsWorkspaceId string
param actionGroupId string

@description('Create CPU High Usage Alert')
resource cpuAlert 'Microsoft.Insights/metricAlerts@2018-03-01' = {
  name: 'cpu-high-usage'
  location: 'global'
  properties: {
    description: 'Alert when CPU usage exceeds 80%'
    severity: 3
    enabled: true
    scopes: [containerAppResourceId]
    evaluationFrequency: 'PT1M'
    windowSize: 'PT5M'
    criteria: {
      allOf: [
        {
          metricName: 'cpuUsagePercentage'
          metricNamespace: 'Microsoft.App/containerApps'
          operator: 'GreaterThan'
          threshold: 80
          timeAggregation: 'Average'
        }
      ]
    }
    actions: [
      {
        actionGroupId: actionGroupId
      }
    ]
  }
}

@description('Create Memory High Usage Alert')
resource memoryAlert 'Microsoft.Insights/metricAlerts@2018-03-01' = {
  name: 'memory-high-usage'
  location: 'global'
  properties: {
    description: 'Alert when memory usage exceeds 75%'
    severity: 3
    enabled: true
    scopes: [containerAppResourceId]
    evaluationFrequency: 'PT1M'
    windowSize: 'PT5M'
    criteria: {
      allOf: [
        {
          metricName: 'memoryWorkingSetBytes'
          metricNamespace: 'Microsoft.App/containerApps'
          operator: 'GreaterThan'
          threshold: 75
          timeAggregation: 'Average'
        }
      ]
    }
    actions: [
      {
        actionGroupId: actionGroupId
      }
    ]
  }
}