- A
Use Azure Data Factory to scale the database based on pipeline triggers.
Why wrong: Data Factory is not designed for scaling databases.
- B
Create an Azure Automation runbook that scales the database on a schedule.
Why wrong: Schedule-based scaling does not respond to workload patterns.
- C
Configure autoscale settings for the Azure SQL Database.
Autoscale automatically adjusts resources based on workload.
- D
Use an elastic pool and manually adjust eDTUs.
Why wrong: Manual adjustment is not automated.
Quick Answer
The answer is to configure the autoscale feature for the Azure SQL Database. This is correct because Azure SQL Database offers a built-in, native autoscaling mechanism through the serverless compute tier, which automatically pauses and resumes the database, or through DTU-based scaling policies that dynamically adjust resources based on real-time workload patterns without requiring any manual intervention or custom scripting. On the Microsoft Azure Database Administrator Associate DP-300 exam, this question tests your understanding of reactive scaling versus scheduled scaling—a common trap is to confuse autoscale with elastic pool scaling or manual tier changes, but the key distinction is that autoscale reacts to workload patterns in real time using a built-in Azure feature. Remember the memory tip: "Serverless scales on demand, DTU scales with demand"—if the question emphasizes minimizing manual intervention and using native features, think serverless or DTU autoscale, not scheduled jobs or manual resizing.
DP-300 Configure and manage automation of tasks Practice Question
This DP-300 practice question tests your understanding of configure and manage automation of tasks. 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. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. 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.
You need to automatically scale an Azure SQL Database based on workload patterns. The solution must use built-in Azure features and minimize manual intervention. Which feature should you configure?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"minimum / minimize"Why it matters: Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
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
Configure autoscale settings for the Azure SQL Database.
Azure SQL Database supports built-in autoscale through the 'Autoscale' feature (serverless compute tier or DTU-based scaling policies), which automatically adjusts resources based on workload patterns without manual intervention. This is the only option that leverages a native Azure feature for dynamic, reactive scaling rather than scheduled or manual actions.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use Azure Data Factory to scale the database based on pipeline triggers.
Why it's wrong here
Data Factory is not designed for scaling databases.
- ✗
Create an Azure Automation runbook that scales the database on a schedule.
Why it's wrong here
Schedule-based scaling does not respond to workload patterns.
- ✓
Configure autoscale settings for the Azure SQL Database.
Why this is correct
Autoscale automatically adjusts resources based on workload.
Clue confirmation
The clue word "minimum / minimize" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use an elastic pool and manually adjust eDTUs.
Why it's wrong here
Manual adjustment is not automated.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates confuse 'automation' (Azure Automation runbooks) with 'automatic scaling' (built-in autoscale), or mistakenly think Azure Data Factory can manage database scaling, when only the native autoscale feature provides dynamic, policy-driven scaling without manual intervention.
Detailed technical explanation
How to think about this question
Azure SQL Database autoscale operates via the serverless compute tier, which automatically pauses databases during idle periods and scales compute based on vCore usage, or via DTU-based scaling policies that adjust service tiers (e.g., S0 to S3) using Azure Monitor metrics and autoscale rules. The feature uses a reactive model with cooldown periods to prevent thrashing, and can be configured through the Azure portal, CLI, or ARM templates. In real-world scenarios, this is critical for variable workloads like e-commerce sites with traffic spikes during sales events.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
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
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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Configure and manage automation of tasks — study guide chapter
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FAQ
Questions learners often ask
What does this DP-300 question test?
Configure and manage automation of tasks — This question tests Configure and manage automation of tasks — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Configure autoscale settings for the Azure SQL Database. — Azure SQL Database supports built-in autoscale through the 'Autoscale' feature (serverless compute tier or DTU-based scaling policies), which automatically adjusts resources based on workload patterns without manual intervention. This is the only option that leverages a native Azure feature for dynamic, reactive scaling rather than scheduled or manual actions.
What should I do if I get this DP-300 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Are there clue words in this question I should notice?
Yes — watch for: "minimum / minimize". Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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 →
Same concept, more angles
2 more ways this is tested on DP-300
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. You need to automatically scale an Azure SQL Database based on workload patterns. Which Azure feature should you use?
easy- ✓ A.Serverless compute tier
- B.Provisioned tier with auto-scale setting
- C.Azure Automation runbook that modifies the service tier
- D.Elastic Database Jobs to add replicas
Why A: Option A is correct because Azure SQL Database's serverless compute tier automatically scales based on workload. Option B is wrong because auto-scaling is not available in provisioned tier without manual intervention. Option C is wrong because Azure Automation with runbooks can perform scaling but is less efficient than serverless. Option D is wrong because Elastic Database Jobs are for multi-database operations, not scaling.
Variation 2. You have an Azure SQL Database that needs to be automatically scaled up during peak hours and scaled down during off-peak. The solution must use native Azure capabilities without custom code. What should you use?
hard- A.Use Azure Functions with timer trigger and PowerShell to change the pricing tier.
- B.Configure autoscale for the elastic pool that contains the database.
- C.Configure autoscale settings on the Azure SQL Database server.
- ✓ D.Create Elastic Database Jobs that run ALTER DATABASE to change the service objective at scheduled times.
Why D: Option B is correct because Elastic Database Jobs can be used to run ALTER DATABASE statements on a schedule. Option A is wrong because Autoscale is not supported for Azure SQL Database. Option C is wrong because Azure Functions would require custom code. Option D is wrong because Elastic Pool autoscale only adjusts per-database DTUs, not the pool size itself.
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Last reviewed: Jun 11, 2026
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