Your company makes use of Azure SQL Database Intelligent Insights and Azure Application Insights for monitoring purposes.
You have been tasked with analyzing the monitoring using ad-hoc queries. You need to utilize the correct query language.
Solution: You use the Contextual Query Language (CQL).
Does the solution meet the goal?
Click on the arrows to vote for the correct answer
A. B.B
https://docs.microsoft.com/en-us/azure/azure-monitor/insights/azure-sqlThe solution proposed to use the Contextual Query Language (CQL) for analyzing the monitoring using ad-hoc queries in Azure SQL Database Intelligent Insights and Azure Application Insights.
CQL is a query language that is used to search, filter, and aggregate logs and events from Azure Application Insights. It is designed to enable users to write powerful and efficient queries that can extract valuable insights from the monitoring data. CQL supports a wide range of operations, including filtering, grouping, sorting, aggregating, and joining, which makes it a versatile language for analyzing monitoring data.
Azure SQL Database Intelligent Insights, on the other hand, is a set of tools and services that are used to monitor the performance of Azure SQL databases. It provides real-time insights into database performance, identifies potential issues, and suggests solutions to optimize database performance. However, it does not support CQL as a query language.
Therefore, the solution proposed to use CQL to analyze the monitoring data in Azure SQL Database Intelligent Insights is not valid. CQL is only applicable for analyzing the monitoring data in Azure Application Insights. For analyzing the monitoring data in Azure SQL Database Intelligent Insights, you should use T-SQL (Transact-SQL), which is a standard query language used to manage relational databases, including Azure SQL Database.
In conclusion, the proposed solution does not meet the goal, and the correct query language for analyzing monitoring data in Azure SQL Database Intelligent Insights is T-SQL.