DP-700 Monitor and Optimize an Analytics Solution Practice Question
You are using a KQL Database in a Microsoft Fabric Eventhouse to analyze streaming data. You need to monitor the performance of your Kusto queries and identify which ones are consuming the most resources. Which TWO methods should you use?
⚠ Common exam trap
Candidates confuse KQL-specific query diagnostics with standard Spark optimization tools or generic database execution plans, missing Kusto native commands.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Run the '.show queries' command in the KQL queryset.
Monitoring KQL performance requires specialized tools within the Eventhouse and Fabric environment. The '.show queries' command provides immediate insights into currently running and recently completed queries, while the Capacity Metrics app provides the high-level view of how these queries impact the overall cost and resource allocation of the Fabric capacity.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Run the '.show queries' command in the KQL queryset.
Why this is correct
The '.show queries' command returns a list of queries that have been executed on the database, including details like execution time, user, and resource consumption (CPU and memory). This is the most direct way to audit query performance and identify poorly written or resource-intensive KQL statements in real-time.
- ✓
Use the Fabric Capacity Metrics app 'KQL Database' tab.
Why this is correct
The Capacity Metrics app tracks the CU consumption specifically for KQL databases. It allows you to see the aggregate load placed on the capacity by the Eventhouse, helping you understand if KQL queries are the primary driver of capacity usage and if they are contributing to any throttling events.
- ✗
Check the Spark UI for Kusto connector logs.
Why it's wrong here
The Spark UI is only relevant if you are using a Spark notebook to pull data from or push data to a KQL database. It will show the performance of the Spark job itself, but it cannot provide the internal execution metrics of queries running natively within the KQL engine.
- ✗
Review the OneLake access logs in the Azure Portal.
Why it's wrong here
OneLake access logs track file-level operations but do not capture the execution details of KQL queries, which operate on data stored in a specialized format within the Eventhouse. These logs are useful for security audits but are ineffective for troubleshooting the performance of analytical queries in Kusto.
- ✗
Monitor the 'Dataflow Gen2' refresh history.
Why it's wrong here
Dataflow Gen2 is a separate component for data ingestion and transformation. While it might be used to load data into a KQL database, its refresh history will not show the performance of the queries being run against that database by end-users or reporting tools like Power BI.
About these practice questions
Courseiva writes every DP-700 question from scratch — 152 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or dumps. Learn why practice questions differ from exam dumps →
JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Microsoft exam blueprint
This DP-700 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DP-700 exam.