DP-300 Practice Question: Monitor, configure, and optimize database resources
Exhibit
Refer to the exhibit. The following KQL query is used to analyze performance metrics for an Azure SQL Database: AzureDiagnostics | where ResourceProvider == "MICROSOFT.SQL" | where Category == "QueryStoreRuntimeStatistics" | summarize avg_duration = avg(duration_s) by query_hash, DatabaseName | where avg_duration > 1000 | order by avg_duration desc
The query returns a list of query hashes with high average duration. You need to identify which queries are most likely causing CPU pressure. What additional metric should you include?
⚠ Common exam trap
The trap is assuming that high logical reads or wait stats directly indicate CPU pressure, when CPU time is the direct measure.
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
✓
Include avg_cpu_time to measure CPU usage.
To identify queries causing CPU pressure, you need to measure CPU usage per query. The `avg_cpu_time` metric directly indicates how much CPU time each query consumes on average, making it the most relevant additional metric.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Include wait_stats to see blocking.
Why it's wrong here
Wait stats reveal blocking and resource waits, not CPU consumption per query. To attribute CPU pressure you need total worker time or CPU time alongside duration, since a long-running query may be I/O-bound. Wait stats would be the right inclusion when diagnosing latency caused by locks or contention rather than processor saturation.
- ✗
Include count_executions to see frequency.
Why it's wrong here
Execution count shows how often a query runs, not how much CPU each run consumes, so a rare expensive query can still dominate CPU. It is tempting because frequency is the right metric when identifying queries whose repeated short runs cumulatively load the server.
- ✗
Include avg_logical_reads to see I/O consumption.
Why it's wrong here
Logical reads measure buffer pool page access, indicating memory and I/O pressure rather than CPU consumption. It is tempting because logical reads are the correct metric when diagnosing queries causing memory grants, spills or storage throughput saturation.
- ✓
Include avg_cpu_time to measure CPU usage.
Why this is correct
Query Store's avg_cpu_time exposes CPU consumption per query hash, directly revealing which queries drive CPU pressure. Duration alone can reflect waits or blocking, so adding avg_cpu_time isolates the actual CPU-heavy offenders the stem asks for.
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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
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