DP-300 Practice Question: Monitor, configure, and optimize database resources
You are a database administrator for a medium-sized e-commerce company. The company runs its online transaction processing (OLTP) workload on an Azure SQL Database in the General Purpose service tier (DTU-based, S3). The database is used for order processing, inventory management, and customer data. Recently, during peak shopping hours (10 AM to 2 PM), users have reported that order entry forms take several seconds to submit, and inventory queries are timing out. Monitoring shows that DTU usage regularly hits 100% during these hours, with high PAGELATCH_IO waits. You need to resolve the performance issue with minimal cost increase. What should you do?
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
✓
Migrate to the vCore model with Hyperscale service tier
Migrate to the vCore model with Hyperscale service tier. The issue is high DTU usage with PAGELATCH_IO waits, indicating resource contention on I/O. Hyperscale architecture separates compute and storage, eliminating such bottlenecks and providing near-instant scaling for peak loads. Option A (increase storage) does not address DTU limits. Option B (increase to S4) adds more DTUs but retains the same architecture limitations that cause PAGELATCH_IO. Option C (read replica) only offloads read queries, not write-heavy OLTP.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Increase the max storage size to 1 TB
Why it's wrong here
Storage size does not affect DTU.
- ✗
Increase the service tier to S4 during peak hours
Why it's wrong here
Temporarily increases DTU but not architectural fix.
- ✗
Create a read-only replica and offload reporting queries
Why it's wrong here
Does not reduce DTU usage from writes.
- ✓
Migrate to the vCore model with Hyperscale service tier
Why this is correct
Hyperscale eliminates resource contention and handles high concurrency.
Visual reference
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
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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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DP-300 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-300 exam.