Quick Answer
The answer is to increase the number of Streaming Units (SUs). When Azure Stream Analytics SU utilization is consistently at 90% or higher, the job is resource-constrained, meaning the allocated compute power is insufficient to keep up with the incoming data rate. Scaling out by adding SUs directly increases the parallel processing capacity, allowing the job to handle more events per second and reduce backlog. On the DP-203 exam, this scenario tests your understanding of reactive scaling strategies for real-time pipelines; a common trap is to assume repartitioning or adjusting the output sink will fix high SU utilization, but those address data skew or egress bottlenecks, not raw compute pressure. Remember the memory tip: "High SU? Add SU."—when utilization is pegged, the immediate fix is to scale out, not to reconfigure the query or risk data loss by lowering the event ordering tolerance.
This DP-203 practice question tests your understanding of secure, monitor, and optimize data storage and data processing. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. 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 are monitoring Azure Stream Analytics job performance. The job is falling behind in processing real-time data. You notice that the SU (Streaming Unit) utilization is consistently at 90% or higher. What is the most appropriate action to improve throughput?
Change the output to use a partition scheme
Why wrong: Partitioning may help but scaling is more direct
Reduce the window duration in the query
Why wrong: Would reduce accuracy, not necessarily throughput
Increase the number of Streaming Units (SUs)
Scaling out increases processing capacity
Decrease the event ordering tolerance
Why wrong: Might reduce throughput
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Increase the number of Streaming Units (SUs)
Option A is correct because increasing the number of SUs (scale out) is the direct way to increase throughput when SU utilization is high. Option B is wrong because it can cause data loss. Option C is wrong because it reduces throughput. Option D is wrong because partitioning might help but the immediate need is to scale.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Change the output to use a partition scheme
Why it's wrong here
Partitioning may help but scaling is more direct
Reduce the window duration in the query
Why it's wrong here
Would reduce accuracy, not necessarily throughput
Increase the number of Streaming Units (SUs)
Why this is correct
Scaling out increases processing capacity
Related concept
Read the scenario before looking for a memorised answer.
Decrease the event ordering tolerance
Why it's wrong here
Might reduce throughput
Common exam traps
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
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.
What to study next
Identify which DP-203 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
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FAQ
Secure, monitor, and optimize data storage and data processing — This question tests Secure, monitor, and optimize data storage and data processing — Read the scenario before looking for a memorised answer..
The correct answer is: Increase the number of Streaming Units (SUs) — Option A is correct because increasing the number of SUs (scale out) is the direct way to increase throughput when SU utilization is high. Option B is wrong because it can cause data loss. Option C is wrong because it reduces throughput. Option D is wrong because partitioning might help but the immediate need is to scale.
Identify which DP-203 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 21, 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.
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