DP-300 Practice Question: Monitor, configure, and optimize database resources
You manage an Azure SQL Managed Instance that hosts a critical OLTP database. You notice that the average CPU usage is consistently above 90% during business hours. You have enabled Intelligent Insights, which recommends creating a missing index. What should you do first to validate the recommendation before implementing it?
⚠ Common exam trap
The trap is treating an automated recommendation as a validated fix — candidates often jump to 'create the index' or 'enable automatic tuning' because it sounds proactive, but the question explicitly asks what to do first to validate, which points to Query Store evidence.
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
✓
Use Query Store to review query performance and missing index details.
Before acting on Intelligent Insights' missing index recommendation, you should validate it against actual workload evidence. Query Store captures query text, plans, runtime stats, and wait categories, so you can confirm the query is genuinely expensive and that the missing index would help. This avoids creating an index that adds write overhead without meaningful read benefit.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Use Query Store to review query performance and missing index details.
Why this is correct
Query Store captures execution plans, runtime statistics and missing-index suggestions per query, letting you confirm the high-CPU queries Intelligent Insights flagged and assess the proposed index's projected impact. This satisfies the stem's requirement to validate the recommendation before implementing it, since Query Store retains historical workload data rather than relying on the advisory alone.
- ✗
Scale up the managed instance to a higher tier.
Why it's wrong here
Scaling up adds compute without addressing the missing index causing the CPU pressure, raising cost while leaving the inefficient query plan intact. It is tempting because sustained high CPU often indicates insufficient resources, and scaling would be correct if the instance were genuinely undersized rather than plan-bound.
- ✗
Enable automatic index tuning.
Why it's wrong here
Automatic tuning applies index changes without prior validation, so it cannot serve as the validation step itself and may act on unverified recommendations. It is tempting because automatic tuning genuinely reduces manual index administration, and would be correct for ongoing hands-off tuning once the workload's behaviour is understood.
- ✗
Create the recommended index immediately.
Why it's wrong here
Applying the index immediately skips validation, risking regressions and write overhead on a critical OLTP workload before confirming the recommendation's benefit. It is tempting because Intelligent Insights surfaces genuine missing-index findings, and creating an index would be correct once impact has been verified against representative query workloads.
Go deeper
Related to this question
Learn chapter
Optimizing Database Query and Index Performance
Key term
Query Store
Query Store is a built-in SQL Server feature that captures and stores a history of query execution plans and performance data for easy monitoring and troubleshooting.
Key term
Azure SQL Managed Instance
Azure SQL Managed Instance is a fully managed cloud database service that gives you nearly all the features of Microsoft SQL Server on your own server, without you having to manage the hardware or operating system.
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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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