The answer is to increase the number of parallel tasks in the DMS task settings. This directly improves AWS DMS full load throughput by splitting the 2 TB dataset across multiple concurrent threads, allowing the migration to process more rows per second than a single-threaded approach. On the AWS Certified Data Engineer Associate DEA-C01 exam, this concept tests your understanding of DMS performance tuning for large-scale migrations, where the common trap is to immediately scale up the replication instance instead of first optimizing parallelism. While increasing instance size does help, parallel tasks are the most effective lever for full loads because they maximize CPU and I/O utilization across the existing resources. Remember the memory tip: for full loads, think "parallel over power"—maximize threads before you maximize hardware.
DEA-C01 Data Ingestion and Transformation Practice Question
This DEA-C01 practice question tests your understanding of data ingestion and transformation. 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 uses AWS DMS to migrate a 2 TB Oracle database to Amazon RDS for PostgreSQL. The migration is taking longer than expected. The task status shows 'Full load in progress' with a low 'Table throughput (rows/s)'. Which action would MOST improve throughput?
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 tasks in the DMS task settings
Using multiple parallel tasks splits the load across threads, improving throughput. Increasing the DMS replication instance size also helps, but parallel tasks are more effective for large datasets.
Key principle: ACLs process entries top to bottom and stop at the first match. Entry order and interface direction matter as much as the permit or deny statement.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✗
Enable Multi-AZ on the DMS replication instance
Why it's wrong here
Multi-AZ provides failover but does not improve throughput.
✗
Change the target table preparation mode to 'Do nothing'
Why it's wrong here
This avoids truncation but does not affect load speed.
✓
Increase the number of parallel tasks in the DMS task settings
Why this is correct
Parallel tasks allow concurrent loading of tables, increasing throughput.
Related concept
Standard ACLs match source addresses.
✗
Increase the number of shards in the source database
Why it's wrong here
Sharding is not applicable to Oracle; DMS handles sharding internally.
Common exam traps
Common exam trap: ACLs stop at the first match
ACLs are processed top to bottom. The first matching entry wins, and an implicit deny usually exists at the end.
Detailed technical explanation
How to think about this question
ACL questions test precision: source, destination, protocol, port and direction. A generally correct ACL can still fail if it is applied on the wrong interface or in the wrong direction.
KKey Concepts to Remember
Standard ACLs match source addresses.
Extended ACLs can match source, destination, protocol and ports.
The first matching ACL entry is used.
There is usually an implicit deny at the end.
TExam Day Tips
→Check inbound versus outbound direction.
→Read the ACL from top to bottom.
→Look for a broader permit or deny above the intended line.
Key takeaway
ACLs process entries top to bottom and stop at the first match. Entry order and interface direction matter as much as the permit or deny statement.
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. ACLs process entries top to bottom and stop at the first match. Entry order and interface direction matter as much as the permit or deny statement. 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.
Review ACL processing order, placement rules (standard near destination, extended near source), and inbound vs outbound direction. Study wildcard masks and implicit deny. Then practise related DEA-C01 ACL questions on filtering logic and placement.
Data Ingestion and Transformation — This question tests Data Ingestion and Transformation — Standard ACLs match source addresses..
What is the correct answer to this question?
The correct answer is: Increase the number of parallel tasks in the DMS task settings — Using multiple parallel tasks splits the load across threads, improving throughput. Increasing the DMS replication instance size also helps, but parallel tasks are more effective for large datasets.
What should I do if I get this DEA-C01 question wrong?
Review ACL processing order, placement rules (standard near destination, extended near source), and inbound vs outbound direction. Study wildcard masks and implicit deny. Then practise related DEA-C01 ACL questions on filtering logic and placement.
What is the key concept behind this question?
Standard ACLs match source addresses.
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Question Discussion
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