Mastering Data Joins in Azure Application Insights with KQL

Introduction :

In Azure Monitor, formerly known as Azure Log Analytics or Azure Application Insights, analyzing data from multiple sources is essential for gaining insights into the performance and health of your applications and infrastructure. One powerful feature that Azure Monitor offers is the ability to join data from multiple log types stored in the same table using the Kusto Query Language (KQL). Mastering table joins in KQL allows you to combine and analyze data efficiently, providing valuable insights into your Azure environment.

Here's a step-by-step guide with a query example:

Step 1: Access Application Insights

Navigate to the Azure Portal (https://portal.azure.com/) and sign in with your credentials.

Step 2: Select Application Insights Resource

Locate and select your Application Insights resource from the list of Azure services. You can use the search bar at the top of the Azure Portal to quickly find your resource.

Step 3: Open Logs

Within your Application Insights resource, locate and click on the "Logs" option in the left-hand menu. This will open the Log Analytics workspace where you can write and execute KQL queries.

Step 4: Write KQL Query

Now "MyAppInsights" tracks telemetry data from a web application. We want to join data from two custom event types: "PageView" and "ButtonClick". Here's how you can write a KQL query to accomplish this:

let PageViewData = 
    customEvents

    | where name == "PageView"

    | project timestamp, userId, pageUrl;

let ButtonClickData =

    customEvents

    | where name == "ButtonClick"

    | project timestamp, userId, buttonName;

PageViewData

| join kind=inner (

    ButtonClickData

) on userId

| project timestamp, userId, pageUrl, buttonName        

Step 5: Explanation:

• We define two subqueries: PageViewData and ButtonClickData. Each subquery filters data from the customEvents table based on the event name and selects relevant fields (timestamp, userId, and additional properties specific to each event type).
• The join operator is used to merge data from both event types based on a common field (userId). We choose an inner join (kind=inner) to include only the records that have matching userId values in both datasets.
• Finally, This query effectively joins data from "PageView" and "ButtonClick" custom event types based on the user ID, allowing us to analyze user behavior across different interactions with the web application.

Step 6: Execute Query

After writing your query, click the "Run" button to execute it. Application Insights will process the query and display the results below the query editor.

Step 7: Review Results

Examine the query results to ensure that the data from multiple log types has been successfully joined based on the common field. You can scroll through the results or use visualizations to gain insights from the data.

Step 8: Further Analysis and Visualization

You can perform additional analysis or create visualizations based on the joined data. Utilize the charting options and visualization tools available in Application Insights to create insightful dashboards and reports.

Step 9: Save or Export Results

If desired, you can save or export the query results for further analysis or reporting. Use options like "Export," "Save," or "Add to Workbook" to save the results to a file or integrate them into other Azure services.

Conclusion:

Mastering data joins in Application Insights using KQL is pivotal for comprehensive analysis. By seamlessly merging data from disparate sources, such as custom events or telemetry tables, analysts gain a holistic understanding of system performance and user behavior. Through the step-by-step process outlined, you've learned to craft queries that unify datasets based on common fields, empowering you to uncover valuable insights that drive informed decision-making and continuous improvement in application functionality and performance. As you continue exploring Application Insights and KQL, experimentation with different join types and utilization of visualization tools will further enhance your analytical capabilities, unlocking actionable insights to propel your applications and business objectives forward.

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