AZ-400 Designing and Implementing Microsoft DevOps Solutions Exam

Formulate and Run Basic Kusto Query Language Queries

When working with Azure Data Explorer, one can utilize the powerful Kusto Query Language (KQL) to analyze logs and telemetry data efficiently. The Azure Data Explorer web UI provides several features that make writing KQL queries more efficient, including KQL Intellisense, inline documentation, and various quick fix options.

KQL Intellisense and Autocomplete

The query editor in Azure Data Explorer has built-in KQL Intellisense which offers contextual suggestions for functions, operators, and more. It also includes autocomplete, which helps complete your queries as you type. This can save time and ensure accuracy.

To use these features:

• Begin typing your query in the editor.
• KQL Intellisense will provide a dropdown list of suggestions that you can navigate using keyboard arrow keys and select with Enter or a mouse click.
• Errors or suggestions are highlighted, and hovering over underlined keywords will reveal more details.

Viewing Documentation Inline

Inline documentation is a valuable feature in the query editor that allows you to access information on operators, functions, and commands directly within the UI.

To view inline documentation:

• Hover over the operator, function, or command in the Intellisense suggestions.
• Click on the right arrow icon to open an inline preview of the documentation.
• This documentation preview will remain active until you close it or end your session.

Quick Fixes

The query editor provides quick fix options to help you address suggestions and warnings. These quick fixes can range from adjusting performance issues to extracting values into variables or defining functions inline.

To apply a quick fix:

• Hover over the term to view any suggestions or warnings.
• Select Quick Fix to view available options.
• Choose the appropriate fix from the provided list.

Using KQL Tools

The KQL tools in the toolbar of the query editor offer additional functionality such as duplicating queries, opening the command palette, or accessing documentation.

To use these tools:

• Select KQL Tools from the toolbar.
• You can perform actions like duplicating a query or accessing a wide range of documentation resources easily from here.

Useful KQL Operators

For effective querying and troubleshooting, certain KQL operators are particularly useful:

• where: Filters a table based on specified conditions.
• project: Selects specific columns from a table.
• summarize: Aggregates data based on specified metrics.
• extend: Adds new columns to a table by computing expressions.

These operators help in filtering data, transforming log data, aggregating metrics, and deriving actionable insights for monitoring and troubleshooting Azure services.