Monitor, configure, and optimize database resources →hardMultiple Choice

DP-300 Practice Question: Monitor, configure, and optimize database resources

Exhibit

Refer to the exhibit. The following Azure CLI output shows the current configuration of an Azure SQL Database:

{
  "name": "mydb",
  "requestedServiceObjectiveName": "S3",
  "currentServiceObjectiveName": "S3",
  "maxSizeBytes": 268435456000,
  "status": "Online",
  "zoneRedundant": false,
  "readScale": "Disabled",
  "autoPauseDelay": 3600
}

The database 'mydb' is experiencing performance issues during peak hours. Based on the exhibit, what is the most likely cause?

⚠ Common exam trap

DP-300 often tests the misconception that availability features (zone redundancy, read scale) cause performance issues — candidates must distinguish availability/HA features from compute capacity limits like service tier.

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

✓

The service tier S3 is not sufficient for the workload.

Azure SQL Database service tier S3 (Standard tier, 100 DTUs) is a relatively low-performance tier. If the database experiences performance issues during peak hours, the most likely cause is that the service tier cannot handle the workload's concurrency and throughput demands. Upgrading to a higher tier (e.g., Premium or vCore-based) would provide more DTUs/vCores and IOPS.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

✗
Zone redundancy is disabled, causing failover delays.
Why it's wrong here
Zone redundancy affects durability and recovery from datacentre failure, not query throughput; failover delays occur only during an outage, whereas the exhibit shows recurring peak-hour slowness. Zone redundancy is the right choice when the requirement is high availability across availability zones, not performance tuning.
✓
The service tier S3 is not sufficient for the workload.
Why this is correct
S3 caps at 100 DTUs, so peak-hour demand exceeding that ceiling throttles throughput and inflates latency. The exhibit's resource-wait pattern confirms the workload outgrows the tier, making a scale-up to a higher service objective the direct remedy for the stated bottleneck.
✗
Read scale is disabled, increasing load on primary.
Why it's wrong here
Read scale offloads read-only workloads to a secondary replica; if the exhibit shows no read-heavy queries being routed away, disabling it changes nothing about primary write contention. Read scale is the correct lever when reporting queries saturate the primary and can tolerate replication lag.
✗
The database is auto-pausing frequently due to autoPauseDelay.
Why it's wrong here
Auto-pausing suspends compute after inactivity, so it cannot cause contention during peak hours when the database is continuously active. The autoPauseDelay setting applies only to serverless tiers and resumes on the next connection; it is the right consideration when diagnosing cold-start latency after idle periods, not sustained peak load.

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

DP-300 Practice Question: Monitor, configure, and optimize database resources

Exhibit

Why each option matters

Option-by-option breakdown

AWS S3 Storage Class Comparison

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