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Monitoring Your Deployment

Effective monitoring is essential for maintaining a healthy and responsive application. This guide covers how to monitor your CodeNull AI Backend deployment on Azure Container Apps.

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Accessing Logs

Azure Container Apps provides built-in logging capabilities that allow you to monitor your application in real-time.

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Streaming Logs

To stream logs from your running container app: 
az containerapp logs show -n web-codenull-app -g web-fastapi-codenull-rg
This command displays the most recent logs from your application, which is helpful for troubleshooting issues or monitoring application behavior.

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Filtering Logs

You can filter the logs to focus on specific information: 
az containerapp logs show -n web-codenull-app -g web-fastapi-codenull-rg --follow
The --follow flag allows you to stream logs in real-time, which is useful during debugging sessions.

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Monitoring Application Health

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Health Check Endpoint

CodeNull AI Backend provides a built-in health check endpoint that you can use to verify that the application is running correctly: 
GET /health
Example request: 
curl -X GET https://<your-app-name>.<region>.azurecontainerapps.io/health
This endpoint returns a status code 200 if the application is healthy. You can also include the mongo_db_check parameter (default: 1) to verify MongoDB connectivity.

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Viewing Deployment Information

To view detailed information about your deployed container app: 
az containerapp show -n web-codenull-app -g web-fastapi-codenull-rg
This command returns configuration details, including:
  • Application URL
  • Resource allocation
  • Scaling rules
  • Environment variables
  • Network configuration

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Setting Up Azure Monitor (Optional)

For more comprehensive monitoring:
  1. Navigate to your Container App in the Azure Portal
  2. Select “Monitoring” from the left navigation
  3. Configure alerts for metrics like:
    • Request count
    • Response time
    • Error rate
    • CPU and memory usage
  1. Regular Health Checks: Set up automated health checks to periodically verify your application’s status
  2. Log Analysis: Review logs regularly to identify potential issues before they affect users
  3. Performance Monitoring: Track response times and resource usage to optimize your application
  4. Alert Configuration: Set up alerts for critical metrics to be notified of issues promptly
By following these monitoring practices, you can ensure your CodeNull AI Backend remains reliable and performant.