- A
Set a cache size for the serverless SQL pool
Why wrong: Incorrect. Cache sizing is a feature for dedicated SQL pools, not serverless SQL pools. Serverless SQL pools do not have configurable cache sizes.
- B
Configure a dedicated SQL pool with auto-scaling
Why wrong: Incorrect. Configuring a dedicated SQL pool with auto-scaling is not applicable to serverless SQL pools; this option describes a different resource type.
- C
Use workload classification to assign resources
Why wrong: Incorrect. Workload classification is used in dedicated SQL pools to assign resources based on workload groups; serverless SQL pools do not support workload classification.
- D
Enable auto-resume and auto-pause on the serverless SQL pool endpoint
Incorrect. Auto-resume and auto-pause do not scale compute resources; they only manage when the pool is active. Serverless SQL pools scale automatically without this feature.
DP-203 Serverless SQL pool Practice Question
This DP-203 practice question tests your understanding of develop data processing. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. A key principle to apply: serverless SQL pool. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
Your team is developing a data processing solution in Azure Synapse Analytics. You need to ensure that the solution can automatically scale compute resources based on workload demand for serverless SQL pools. Which feature should you configure?
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 auto-resume and auto-pause on the serverless SQL pool endpoint
Serverless SQL pools in Azure Synapse Analytics automatically scale compute resources based on workload demand without requiring any configuration. None of the provided options enable this automatic scaling. Auto-resume and auto-pause only control the pool's active state, not its compute size. Dedicated SQL pool features like auto-scaling, cache sizing, and workload classification do not apply to serverless pools.
Key principle: Serverless SQL pool
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Set a cache size for the serverless SQL pool
Why it's wrong here
Incorrect. Cache sizing is a feature for dedicated SQL pools, not serverless SQL pools. Serverless SQL pools do not have configurable cache sizes.
- ✗
Configure a dedicated SQL pool with auto-scaling
Why it's wrong here
Incorrect. Configuring a dedicated SQL pool with auto-scaling is not applicable to serverless SQL pools; this option describes a different resource type.
- ✗
Use workload classification to assign resources
Why it's wrong here
Incorrect. Workload classification is used in dedicated SQL pools to assign resources based on workload groups; serverless SQL pools do not support workload classification.
- ✓
Enable auto-resume and auto-pause on the serverless SQL pool endpoint
Why this is correct
Incorrect. Auto-resume and auto-pause do not scale compute resources; they only manage when the pool is active. Serverless SQL pools scale automatically without this feature.
Related concept
Serverless SQL pool
Common exam traps
Common exam trap: answer the scenario, not the keyword
Candidates often assume that serverless SQL pools require a scaling configuration or that auto-resume/auto-pause scales compute resources. In reality, scaling is automatic and not configurable; auto-resume/auto-pause only manage availability.
Detailed technical explanation
How to think about this question
Serverless SQL pools in Azure Synapse use a distributed query engine that dynamically allocates compute nodes based on the complexity and size of the query, scaling from zero to hundreds of nodes per query. The auto-resume and auto-pause feature is configured at the endpoint level and uses a default pause timeout of 5 minutes of inactivity, after which the endpoint is deallocated to save costs. This behavior is distinct from dedicated SQL pools, which require explicit scaling actions or auto-scaling rules based on DWU thresholds.
KKey Concepts to Remember
- Serverless SQL pool
- Automatic scaling
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Serverless SQL pool
Real-world example
How this comes up in practice
An e-commerce site experiences heavy traffic on Black Friday and near-zero traffic during off-peak weeks. Rather than provisioning permanent large VMs, the team uses auto-scaling groups that add capacity automatically under load and reduce it overnight. Questions like this test whether you understand elasticity, availability zones, and cloud compute scaling patterns.
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 |
What to study next
Got this wrong? Here's your next step.
Review serverless SQL pool, then practise related DP-203 questions on the same topic to reinforce the concept.
- →
Develop data processing — study guide chapter
Learn the concepts, then practise the questions
- →
Develop data processing practice questions
Targeted practice on this topic area only
- →
All DP-203 questions
851 questions across all exam domains
- →
Microsoft Azure Data Engineer Associate DP-203 study guide
Full concept coverage aligned to exam objectives
- →
DP-203 practice test guide
How to use practice tests most effectively before exam day
Related practice questions
Related DP-203 practice-question pages
Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.
Secure, monitor, and optimize data storage and data processing practice questions
Practise DP-203 questions linked to Secure, monitor, and optimize data storage and data processing.
Design and develop data processing practice questions
Practise DP-203 questions linked to Design and develop data processing.
Design and implement data security practice questions
Practise DP-203 questions linked to Design and implement data security.
Monitor and optimize data storage and processing practice questions
Practise DP-203 questions linked to Monitor and optimize data storage and processing.
Design and implement data storage practice questions
Practise DP-203 questions linked to Design and implement data storage.
Develop data processing practice questions
Practise DP-203 questions linked to Develop data processing.
DP-203 fundamentals practice questions
Practise DP-203 questions linked to DP-203 fundamentals.
DP-203 scenario practice questions
Practise DP-203 questions linked to DP-203 scenario.
DP-203 troubleshooting practice questions
Practise DP-203 questions linked to DP-203 troubleshooting.
Practice this exam
Start a free DP-203 practice session
Short sessions build daily habit. Longer sessions build exam-day stamina. Try a timed session to simulate real conditions.
FAQ
Questions learners often ask
What does this DP-203 question test?
Develop data processing — This question tests Develop data processing — Serverless SQL pool.
What is the correct answer to this question?
The correct answer is: Enable auto-resume and auto-pause on the serverless SQL pool endpoint — Serverless SQL pools in Azure Synapse Analytics automatically scale compute resources based on workload demand without requiring any configuration. None of the provided options enable this automatic scaling. Auto-resume and auto-pause only control the pool's active state, not its compute size. Dedicated SQL pool features like auto-scaling, cache sizing, and workload classification do not apply to serverless pools.
What should I do if I get this DP-203 question wrong?
Review serverless SQL pool, then practise related DP-203 questions on the same topic to reinforce the concept.
What is the key concept behind this question?
Serverless SQL pool
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Keep practising
More DP-203 practice questions
- You are designing a data storage solution for IoT sensor data. The data is written thousands of times per second and req…
- A data processing job in Azure Synapse Analytics writes results to a table in the dedicated SQL pool. After a failure, t…
- A multinational corporation uses Azure Data Lake Storage Gen2 to store petabytes of parquet files partitioned by date an…
- A company ingests streaming data from IoT devices into Azure Event Hubs. The data must be processed in near real-time to…
- Which THREE factors should be considered when choosing between Azure Stream Analytics and Azure Databricks for a real-ti…
- You are designing a data lake on Azure Data Lake Storage Gen2. The data will be used by both batch processing (Spark) an…
Last reviewed: Jul 4, 2026
This DP-203 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-203 exam.
Question Discussion
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
Sign in to join the discussion.