Describe core data concepts →hardMultiple ChoiceObjective-mapped

DP-900 Describe core data concepts Practice Question

Exhibit

{
  "type": "Microsoft.Sql/servers/databases",
  "apiVersion": "2023-08-01-preview",
  "properties": {
    "collation": "SQL_Latin1_General_CP1_CI_AS",
    "maxSizeBytes": 268435456000,
    "requestedBackupStorageRedundancy": "Geo",
    "edition": "GeneralPurpose",
    "requestedServiceObjectiveName": "GP_Gen5_4"
  }
}

Refer to the exhibit. You are reviewing an ARM template for an Azure SQL Database deployment. The database must support a read-only workload that requires low latency. The current configuration uses General Purpose tier with 4 vCores. What is the most significant performance improvement you can make without changing the tier?

⚠ Common exam trap

Many exam-takers confuse scaling storage (maxSizeBytes) or changing backup redundancy with performance improvements, but the question specifically targets read latency for a read-only workload, which is directly addressed by read scale-out rather than storage or backup changes.

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

✓

Enable read scale-out by adding 'readScale' property

Enabling read scale-out by adding the 'readScale' property allows the database to use a read-only replica, offloading read workloads from the primary and providing low-latency reads. This is the most significant performance improvement within the General Purpose tier because it directly addresses the read-only workload requirement without changing the tier or incurring additional compute costs.

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 maxSizeBytes to 1 TB
Why it's wrong here
Increasing maxSizeBytes to 1 TB in your ARM template only raises the maximum database storage limit; it does not add more compute, memory, or I/O capacity. Your database may still hit the same DTU/vCore limits or storage throughput constraints, so queries won't run faster. In fact, for General Purpose tier, a larger max size can even increase the cost of storage without improving latency or throughput at all.
✗
Set the edition to 'Serverless'
Why it's wrong here
Setting the edition to 'Serverless' changes the compute billing and auto-scaling behavior, not the raw performance ceiling. Serverless can pause and resume, which introduces cold-start latency and may cause connection timeouts for workloads that need consistent low latency. It is not a performance tuning knob; it is an operational model for intermittent, unpredictable usage, and it cannot make an existing general-purpose database 'faster' in a steady state.
✓
Enable read scale-out by adding 'readScale' property
Why this is correct
Enabling read scale-out by adding the 'readScale' property to your ARM template routes read-only connections to an automatically provisioned read-only replica. This offloads read-heavy query load from the primary replica, freeing up its CPU, memory, and I/O for write operations and transactional workloads. This is the only option that directly improves query performance by scaling out the read path, especially for workloads that separate reporting or analytical queries from OLTP traffic.
✗
Change requestedBackupStorageRedundancy to 'Local'
Why it's wrong here
Changing the requestedBackupStorageRedundancy property to 'Local' alters how your database backups are replicated for durability—it does not affect the live database's compute, memory, or I/O. Local redundancy stores backups in a single data center, which reduces resiliency and may be chosen for cost, but it has zero impact on query execution speed or resource limits. Performance is determined by the service tier, compute size, and replica configuration, not by backup storage redundancy.

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DP-900 Describe core data concepts Practice Question

Exhibit

Why each option matters

Option-by-option breakdown

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