DP-300 Practice Question: Monitor, configure, and optimize database resources
Exhibit
Azure Monitor metric for Azure SQL Database: Metric: dtu_consumption_percent Time range: Past hour Average: 95% Max: 100% Min: 30% Metric: cpu_percent Average: 80% Max: 95% Metric: physical_data_read_percent Average: 90% Max: 100% Metric: log_write_percent Average: 20% Query Store top resource consumers: Query ID: 1234 Execution count: 5000 Total logical reads: 2.5 million Total duration: 10,000 ms Query ID: 5678 Execution count: 100 Total logical reads: 50,000 Total duration: 500 ms
Refer to the exhibit. An Azure SQL Database in the Standard tier (S2: 50 DTU) is consistently showing high DTU consumption. Which action would most effectively reduce DTU usage?
⚠ Common exam trap
Many candidates choose scaling up (Option C) as a quick fix, not realizing that it only increases resource limits without addressing the underlying inefficient query or missing index, leading to continued high DTU usage and unnecessary cost.
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 an index on the tables accessed by Query 1234
Query 1234 is likely the primary contributor to high DTU consumption, as indicated by the exhibit (not shown here but implied). Creating an index on the tables it accesses can reduce the number of logical reads and improve query performance, directly lowering DTU usage without additional cost. This is the most effective action because it addresses the root cause—poor query performance—rather than masking the symptom with more resources.
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 an index on the tables accessed by Query 1234
Why this is correct
Reducing logical reads via indexing directly lowers DTU usage.
- ✗
Increase the log_write_percent by adjusting transaction log settings
Why it's wrong here
Log writes are low; not a bottleneck.
- ✗
Scale up to a higher service tier (e.g., S3)
Why it's wrong here
Scaling up increases DTU, but does not fix inefficient queries.
- ✗
Rebuild all indexes in the database
Why it's wrong here
May help but less targeted than optimizing the specific high-impact query.
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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