Azure Application Insights with Kusto Query Language

Azure Application Insights is a monitoring and diagnostics service that helps you understand the performance and usage of your web applications. It provides a range of tools and features to help you identify and troubleshoot issues, including real-time monitoring, alerting, and log analytics.

One of the key features of Azure Application Insights is the ability to use Kusto Query Language (KQL) to analyze log data and create custom queries and reports. KQL is a powerful and flexible query language that enables you to extract and analyze data from Azure Application Insights logs and other sources.

Here is an example of how you can use KQL to create a custom query in Azure Application Insights:

  1. Navigate to the Azure portal and open the Azure Application Insights resource for your application.
  2. Click on the “Logs” button in the left menu.
  3. In the “Logs” blade, enter the following KQL query:
requests | where success == false | summarize count() by resultCode

This query will retrieve all failed requests and group them by result code, showing the number of failed requests for each result code.

  1. To save the query and create a chart, click on the “Save as chart” button in the top menu.
  2. In the “Save chart” blade, enter a name for the chart and select the desired chart type.
  3. Click on the “Save” button to create the chart.

This will create a custom chart in Azure Application Insights that shows the number of failed requests grouped by result code, using the KQL query that you defined.

In summary, Azure Application Insights is a monitoring and diagnostics service that provides a range of tools and features to help you understand the performance and usage of your web applications. You can use KQL to create custom queries and reports in Azure Application Insights, enabling you to extract and analyze data from your logs and other sources in order to identify and troubleshoot issues.

Kusto Query Language (KQL)

Kusto Query Language (KQL) is a powerful and flexible query language that enables you to extract and analyze data from a variety of sources, including logs, metrics, and documents. It is used by a range of Azure services, including Azure Log Analytics, Azure Monitor, and Azure Application Insights, as well as other services such as Azure Data Explorer and Azure Stream Analytics.

KQL is designed to be easy to learn and use, with a simple and intuitive syntax that enables you to quickly build and execute queries. It supports a range of operators and functions that enable you to filter, group, and aggregate data, as well as transform and manipulate data using expressions and custom functions.

Here is an example of a simple KQL query that counts the number of requests to a web server:

requests | count

This query retrieves all requests from the requests table and counts the number of rows.

KQL also supports more complex queries, such as the following example, which counts the number of requests grouped by result code:

requests | summarize count() by resultCode

This query retrieves all requests from the requests table and groups them by result code, showing the number of requests for each result code.

In summary, KQL is a powerful and flexible query language that enables you to extract and analyze data from a variety of sources. It is used by a range of Azure services to enable you to build custom queries and reports, and is designed to be easy to learn and use, with a simple and intuitive syntax.

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