Microsoft Certified: DevOps Engineer Expert Practice Mode

Community Discussion

Written by other learners. Comments can disagree with the marked answer — check the official documentation when in doubt.

• Chose A1

  Azure Log Analytics is the right tool for analyzing monitoring data using ad-hoc queries. It uses the Kusto Query Language (KQL) to query and analyze data collected from: Azure Application Insights: Provides telemetry data like request rates, response times, and failure rates. Azure SQL Database Intelligent Insights: When integrated, logs diagnostic and performance data into Log Analytics.

• Chose A2

  The confusion here arises from the distinction between Azure Log Analytics as a service and the query language it uses, which is Kusto Query Language (KQL). To clarify: Azure Log Analytics is a service that allows you to aggregate and analyze data from various Azure resources, including Azure SQL Database and Azure Application Insights. KQL is the query language used within Azure Log Analytics to perform ad-hoc queries and retrieve insights. When the question asks about utilizing the "correct query language," it is referring to the query language used within the Azure Log Analytics platform, which is KQL. So, in the context of the question, using Azure Log Analytics is indeed the correct approach because it leverages KQL to analyze data. Conclusion: The answer of A. Yes is correct because Azure Log Analytics uses KQL, which is the correct query language for analyzing the monitoring data from both Azure SQL Database Intelligent Insights and Azure Application Insights.

• Chose A1

  answer can be yes tough log analytics is not a query languge