DP-300 Plan and implement data platform resources Practice Question
You are deploying a new Azure SQL Database for a line-of-business application. The application's usage pattern is unpredictable, with long idle periods overnight and short bursts of heavy activity during business hours. Cost optimization is a priority, and the database can tolerate a brief reconnection delay when scaling. You need to select a purchasing model and service tier that minimizes cost while automatically adjusting compute resources. What should you do?
⚠ Common exam trap
The trap here is assuming that any vCore service tier supports automatic scaling, when in fact only the serverless compute tier provides that behavior.
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
✓
Deploy the database by using the vCore purchasing model with the General Purpose service tier and configure the serverless compute tier.
The serverless compute tier in the vCore purchasing model automatically scales compute resources based on workload activity and can pause the database during idle times, charging only for storage. This matches the need to minimize cost for unpredictable usage and tolerates the brief reconnection delay upon resuming. Other tiers either lack auto-scaling or are not cost-effective for this pattern.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Deploy the database by using the DTU purchasing model with the Standard service tier and configure elastic pool auto-scaling.
Why it's wrong here
The DTU model with Standard tier does not support automatic scaling of individual database compute. Elastic pool auto-scaling applies to pools, not single databases, and the scenario describes a single database deployment. Additionally, DTU-based service tiers are legacy and lack the serverless compute auto-scaling capabilities needed for unpredictable workloads.
- ✗
Deploy the database by using the vCore purchasing model with the Hyperscale service tier and enable read-scale replicas.
Why it's wrong here
Hyperscale is designed for very large databases (up to 100 TB) and rapid scale-out of read workloads, but it does not automatically scale compute up and down based on demand. It also has a higher baseline cost. The scenario requires cost minimization during idle periods and automatic compute adjustment, which Hyperscale does not provide.
- ✓
Deploy the database by using the vCore purchasing model with the General Purpose service tier and configure the serverless compute tier.
Why this is correct
The vCore model with General Purpose service tier supports the serverless compute tier, which automatically scales compute based on workload demand and can pause the database during inactive periods, billing only for storage. This directly addresses unpredictable usage and cost optimization, while accepting a brief reconnection delay when resuming from a paused state, exactly as the scenario permits.
- ✗
Deploy the database by using the vCore purchasing model with the Business Critical service tier and configure auto-scaling.
Why it's wrong here
The vCore model's Business Critical tier provides high performance and local SSD, but it does not offer automatic scaling of compute resources based on workload. Scaling requires manual intervention or scheduled scripts, which would not respond to unpredictable bursts and would incur unnecessary cost during idle periods. This option is both more expensive and operationally complex for the stated requirements.
Quick reference
Cloud Service Model Comparison
| Model | You Manage | Provider Manages | Examples |
|---|---|---|---|
| IaaS | OS, runtime, apps, data | Hardware, hypervisor, networking | EC2, Azure VMs, GCP Compute Engine |
| PaaS | Apps and data | OS, runtime, middleware, hardware | Elastic Beanstalk, Azure App Service |
| SaaS | Data and settings only | Everything else | Microsoft 365, Salesforce, Workday |
| FaaS / Serverless | Function code only | Infra, scaling, runtime | Lambda, Azure Functions, Cloud Run |
| CaaS | Containers and apps | Kubernetes, OS, hardware | EKS, AKS, GKE |
Go deeper
Related to this question
Learn chapter
Deploying and Configuring SQL Server on Azure Virtual Machines
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 and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Microsoft exam blueprint
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.