- A
Configure workload management (WLM) queues to separate ETL and dashboard queries, and assign different concurrency levels.
WLM allows resource allocation per queue, ensuring dashboard queries have dedicated resources.
- B
Enable concurrency scaling to handle bursts of queries.
Why wrong: Concurrency scaling adds capacity but does not prioritize dashboard queries.
- C
Enable short query acceleration (SQA) to prioritize queries that run under a certain time threshold.
Why wrong: SQA prioritizes short queries but does not prevent long ETL jobs from consuming resources.
- D
Increase the number of nodes in the Redshift cluster.
Why wrong: Adding nodes increases overall capacity but does not guarantee priority for short queries.
Question 1,342 of 1,730
Redshift WLM for Mixed Workloads
This DBS-C01 practice question tests your understanding of workload-specific database design. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. 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.
A financial services company uses Amazon Redshift for analytics. The workload consists of a mix of short-running queries from dashboards and long-running ETL jobs. The company notices that during peak hours, short queries experience high latency due to queueing behind ETL jobs. How can the company reduce the impact of ETL jobs on dashboard queries?
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 workload management (WLM) queues to separate ETL and dashboard queries, and assign different concurrency levels.
Option A is correct because Amazon Redshift's Workload Management (WLM) allows you to create separate queues for different query types, such as ETL jobs and dashboard queries. By assigning different concurrency levels to each queue, you prevent long-running ETL jobs from consuming all available slots and blocking short dashboard queries, thereby reducing latency during peak hours.
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.
- ✓
Configure workload management (WLM) queues to separate ETL and dashboard queries, and assign different concurrency levels.
Why this is correct
WLM allows resource allocation per queue, ensuring dashboard queries have dedicated resources.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Enable concurrency scaling to handle bursts of queries.
Why it's wrong here
Concurrency scaling adds capacity but does not prioritize dashboard queries.
- ✗
Enable short query acceleration (SQA) to prioritize queries that run under a certain time threshold.
Why it's wrong here
SQA prioritizes short queries but does not prevent long ETL jobs from consuming resources.
- ✗
Increase the number of nodes in the Redshift cluster.
Why it's wrong here
Adding nodes increases overall capacity but does not guarantee priority for short queries.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse concurrency scaling or SQA as solutions for queueing, but these features do not isolate workloads; they only add capacity or prioritize within a single queue, whereas WLM queue separation directly addresses the root cause by dedicating resources per workload type.
Detailed technical explanation
How to think about this question
WLM in Amazon Redshift uses queue slots to manage concurrency; by default, all queries share a single queue with a concurrency of 5 (or 15 for ra3 nodes). Creating separate queues with different concurrency levels (e.g., 2 for ETL, 5 for dashboards) ensures that dashboard queries always have dedicated slots, even during peak ETL activity. Additionally, you can set a timeout for long-running queries in the dashboard queue to prevent runaway jobs from blocking other queries.
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 cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
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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FAQ
Questions learners often ask
What does this DBS-C01 question test?
Workload-Specific Database Design — This question tests Workload-Specific Database Design — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Configure workload management (WLM) queues to separate ETL and dashboard queries, and assign different concurrency levels. — Option A is correct because Amazon Redshift's Workload Management (WLM) allows you to create separate queues for different query types, such as ETL jobs and dashboard queries. By assigning different concurrency levels to each queue, you prevent long-running ETL jobs from consuming all available slots and blocking short dashboard queries, thereby reducing latency during peak hours.
What should I do if I get this DBS-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jul 4, 2026
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