DP-300 Plan and implement data platform resources Practice Question
You are planning the deployment of a new Azure SQL Database for a line-of-business application. The application's workload is not yet known, and you must keep the monthly cost as low as possible while still being able to scale compute resources up or down without redeploying the database. You also need to ensure that storage is billed based on the actual data and log used rather than a pre-provisioned maximum. Which purchasing model and service tier should you choose?
⚠ Common exam trap
The trap here is assuming that any service tier can be combined with serverless compute; serverless is only available with the General Purpose 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
✓
Serverless compute tier with General Purpose service tier
The serverless compute tier in the General Purpose service tier is designed for unpredictable workloads and cost optimisation. It automatically scales compute based on demand and can auto-pause during inactive periods, billing only for compute used. Storage is billed based on actual data and log usage. Provisioned tiers reserve compute capacity and bill continuously, making them less suitable when the workload is unknown and cost must be minimised.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Provisioned compute tier with General Purpose service tier
Why it's wrong here
The provisioned compute tier reserves a fixed amount of vCores and memory, and you are billed for that reserved capacity even when the database is idle. It supports scaling but does not bill storage based on actual usage in the same way as the serverless tier. For an unknown workload where cost minimisation is critical, this model is not the best fit because you pay for provisioned compute continuously.
- ✓
Serverless compute tier with General Purpose service tier
Why this is correct
The serverless compute tier automatically scales compute based on workload demand and bills per second of compute used, with a configurable auto-pause delay that can stop compute entirely during inactive periods. Storage is billed based on the actual data and log used rather than a pre-provisioned maximum. This directly meets the requirements of low cost for an unknown workload and the ability to scale without redeployment.
- ✗
Hyperscale service tier with provisioned compute
Why it's wrong here
The Hyperscale service tier is designed for very large databases up to 100 TB and provides rapid scale-out of compute and storage, but it is not the most cost-effective choice for a small or unknown workload. It uses provisioned compute, so you pay for reserved capacity continuously. While it supports scaling, it does not bill storage based on actual usage in the same way as serverless.
- ✗
Provisioned compute tier with Business Critical service tier
Why it's wrong here
The Business Critical service tier provides the highest performance and availability with local SSD storage and built-in read replicas, but it is significantly more expensive than General Purpose. It also uses the provisioned compute model, which reserves and bills for fixed compute capacity regardless of actual usage. For a cost-sensitive deployment with unknown workload, this tier is not appropriate.
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
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 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.