DP-300 Practice Question: Monitor, configure, and optimize database resources
You are configuring performance optimization for an Azure SQL Database that uses the Hyperscale service tier. The database has heavy read-write workloads. Which THREE actions should you take to optimize performance?
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
✓
Create nonclustered columnstore indexes on large fact tables.
Options A, C, and D are correct. Hyperscale benefits from nonclustered indexes on read-intensive tables, accelerated database recovery reduces log IO, and read-scale replicas distribute read load. Option B is wrong because Hyperscale does not support resource governor. Option E is wrong because increasing service tier is not an optimization action.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Create nonclustered columnstore indexes on large fact tables.
Why this is correct
Columnstore indexes improve performance for large analytical queries.
- ✗
Configure resource governor to limit CPU usage.
Why it's wrong here
Resource governor is not supported in Hyperscale.
- ✓
Enable accelerated database recovery (ADR) to reduce transaction log IO.
Why this is correct
ADR reduces log IO, which is beneficial in Hyperscale.
- ✓
Configure read-scale replicas to offload reporting queries.
Why this is correct
Read-scale replicas in Hyperscale can serve read-only workloads.
- ✗
Increase the service tier to Business Critical.
Why it's wrong here
Hyperscale is already the highest tier for scalability; changing is not an optimization.
Go deeper
Related to this question
Learn chapter
Overview of Azure Data Platform Options
Key term
Azure SQL Performance Tuning
Azure SQL Performance Tuning is the process of optimizing the speed and efficiency of queries and database operations in Microsoft Azure SQL Database or SQL Managed Instance to reduce latency and improve throughput.
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