Detecting Abnormal Rise in Failed Requests for Azure Web App in Azure DevOps | Solution Recommendation

Detecting Abnormal Rise in Failed Requests

Question

You have an Azure DevOps organization named Contoso and an Azure subscription. The subscription contains an Azure virtual machine scale set named VMSS1 that is configured for autoscaling.

You use Azure DevOps to build a web app named App1 and deploy App1 to VMSS1. App1 is used heavily and has usage patterns that vary on a weekly basis.

You need to recommend a solution to detect an abnormal rise in the rate of failed requests to App1. The solution must minimize administrative effort.

What should you include in the recommendation?

Answers

Explanations

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A

After setting up Application Insights for your project, and if your app generates a certain minimum amount of data, Smart Detection of failure anomalies takes 24 hours to learn the normal behavior of your app, before it is switched on and can send alerts.

https://docs.microsoft.com/en-us/azure/azure-monitor/app/proactive-failure-diagnostics

The recommended solution to detect an abnormal rise in the rate of failed requests to App1 with minimal administrative effort is to use the Smart Detection feature in Azure Application Insights.

Smart Detection is a machine learning-based feature in Azure Application Insights that automatically detects and diagnoses issues in web applications by analyzing application telemetry data. Smart Detection uses machine learning algorithms to continuously analyze telemetry data from applications and infrastructure components to detect and diagnose issues such as failed requests, slow responses, and abnormal usage patterns. Smart Detection can also provide remediation advice to help resolve issues.

The Failures feature in Azure Application Insights is another feature that can be used to detect failures in applications, but it requires manual configuration to set up the failure conditions and alert rules. The Failures feature can be used in combination with Smart Detection to provide more comprehensive monitoring of applications.

An Azure Service Health alert can be used to monitor the health of Azure services, but it is not specific to the application and cannot detect issues within the application.

An Azure Monitor alert that uses an Azure Log Analytics query can be used to monitor specific log data from applications and infrastructure, but it requires manual configuration and maintenance to set up the alert rules and queries.

Therefore, the recommended solution to detect an abnormal rise in the rate of failed requests to App1 with minimal administrative effort is to use the Smart Detection feature in Azure Application Insights.