- A
Increase the Aurora cluster's max_connections parameter
Why wrong: This may not directly improve CDC performance.
- B
Increase the number of parallel apply threads in the DMS task
More parallel apply threads can increase the rate of applying changes to Aurora, reducing CPU usage per thread.
- C
Increase the DMS task's target storage allocation
Why wrong: DMS does not allocate storage on the target; Aurora manages its own storage.
- D
Change the Aurora cluster to a larger instance class
Why wrong: High CPU on target indicates the target is struggling; this could help, but the question asks for DMS change.
Question 1,712 of 1,730
Improving DMS CDC Performance: Increasing Parallel Apply Threads
This DBS-C01 practice question tests your understanding of deployment and migration. 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.
A company is migrating a 5 TB Oracle database to Amazon Aurora MySQL using AWS DMS. The full load completes successfully, but the CDC phase is slow and the target Aurora cluster is consuming high CPU. The DMS instance type is dms.c4.2xlarge. Which change will most likely improve CDC performance?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"most likely"Why it matters: Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
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
✓
Increase the number of parallel apply threads in the DMS task
The correct answer is B because increasing the number of parallel apply threads in the DMS task allows the CDC phase to apply multiple transactions concurrently to the target Aurora cluster, reducing the backlog of changes. The high CPU on the target suggests the apply process is the bottleneck, not the source or network, and DMS's parallel apply threads directly address this by enabling multi-threaded writes, which improves throughput without requiring larger instances.
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.
- ✗
Increase the Aurora cluster's max_connections parameter
Why it's wrong here
This may not directly improve CDC performance.
- ✓
Increase the number of parallel apply threads in the DMS task
Why this is correct
More parallel apply threads can increase the rate of applying changes to Aurora, reducing CPU usage per thread.
Clue confirmation
The clue word "most likely" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Increase the DMS task's target storage allocation
Why it's wrong here
DMS does not allocate storage on the target; Aurora manages its own storage.
- ✗
Change the Aurora cluster to a larger instance class
Why it's wrong here
High CPU on target indicates the target is struggling; this could help, but the question asks for DMS change.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often assume high CPU on the target means the instance is undersized and needs a larger class (Option D), but the real issue is the DMS apply process being single-threaded, which causes CPU to spike due to inefficient serial writes rather than insufficient compute capacity.
Detailed technical explanation
How to think about this question
DMS CDC uses a single apply thread by default, which can become a bottleneck when applying high-volume transactional changes to Aurora MySQL, especially with large batch sizes or many small transactions. The parallel apply threads feature (enabled via the 'ParallelApplyThreads' task setting) allows DMS to partition changes across multiple threads, each applying to the target in separate transactions, which leverages Aurora's multi-core CPUs and reduces latency. In practice, this is critical for migrations with high write throughput, such as OLTP workloads, where the CDC lag can grow unbounded without parallelism.
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.
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FAQ
Questions learners often ask
What does this DBS-C01 question test?
Deployment and Migration — This question tests Deployment and Migration — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Increase the number of parallel apply threads in the DMS task — The correct answer is B because increasing the number of parallel apply threads in the DMS task allows the CDC phase to apply multiple transactions concurrently to the target Aurora cluster, reducing the backlog of changes. The high CPU on the target suggests the apply process is the bottleneck, not the source or network, and DMS's parallel apply threads directly address this by enabling multi-threaded writes, which improves throughput without requiring larger instances.
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.
Are there clue words in this question I should notice?
Yes — watch for: "most likely". Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
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Same concept, more angles
1 more ways this is tested on DBS-C01
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. A company is migrating a 10 TB Oracle database to Amazon Aurora PostgreSQL. The migration uses AWS DMS with CDC. After the full load, the CDC phase is falling behind by several minutes. The source Oracle database generates 500 MB of redo logs per minute. Which action will most likely improve CDC performance?
hard- A.Disable CDC and perform a full load only
- ✓ B.Increase the number of parallel apply threads on the DMS task
- C.Reduce the batch size in the DMS task settings
- D.Increase the source Oracle redo log size
Why B: Increasing the number of parallel apply threads on the DMS task allows the target Aurora PostgreSQL database to apply changes concurrently, reducing the bottleneck caused by sequential apply. With 500 MB/min of redo logs, the single-threaded default apply cannot keep pace, so parallel apply directly addresses the lag by distributing the load across multiple threads.
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Last reviewed: Jul 4, 2026
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