- A
Enable DynamoDB Accelerator (DAX) to cache write requests and reduce the load on the table.
Why wrong: DAX is a read cache, not designed to buffer writes.
- B
Shard the DynamoDB table manually by adding a random suffix to the partition key to distribute writes more evenly.
Why wrong: Sharding helps with hot partitions but does not address overall throughput limits; sudden spikes still cause throttling.
- C
Increase the maximum write capacity for Auto Scaling to a higher value, such as 20000 WCU.
Why wrong: This may still not handle extreme spikes and incurs higher cost; Auto Scaling lags behind sudden spikes.
- D
Implement an Amazon SQS queue to buffer write requests and process them in batches, with a Lambda function writing to DynamoDB.
SQS decouples the write path, absorbing spikes and allowing throttled writes to DynamoDB.
DBS-C01 Workload-Specific Database Design Practice Question
This DBS-C01 practice question tests your understanding of workload-specific database design. 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.
A company runs an online gaming platform that uses Amazon DynamoDB to store player profiles and game state. The platform experiences sudden spikes in write traffic when popular events occur. During these spikes, some write requests fail with ProvisionedThroughputExceededException. The operations team has configured DynamoDB Auto Scaling with a maximum write capacity of 10000 WCU, but during spikes, the write rate exceeds 10000 WCU for short bursts. The team needs to handle these bursts without losing data or sacrificing performance. What is the MOST effective solution?
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
Implement an Amazon SQS queue to buffer write requests and process them in batches, with a Lambda function writing to DynamoDB.
DynamoDB Auto Scaling can increase capacity, but it reacts to CloudWatch alarms and takes time (minutes). For sudden spikes, the best solution is to use DynamoDB Accelerator (DAX) for reads, not writes. For writes, you can implement exponential backoff and retries in the application, but that may increase latency. Another option is to use a queue (Amazon SQS) to buffer writes and process them at a controlled rate. This decouples the application from the database, allowing spikes to be absorbed. Option A (increase max WCU) helps but may not be enough if spikes are very high and unpredictable. Option B (DAX) does not help with writes. Option C (SQS buffer) is a common pattern. Option D (sharding) requires application changes and may not be necessary. So the best is to use SQS to buffer writes.
Key principle: NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
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 DynamoDB Accelerator (DAX) to cache write requests and reduce the load on the table.
Why it's wrong here
DAX is a read cache, not designed to buffer writes.
- ✗
Shard the DynamoDB table manually by adding a random suffix to the partition key to distribute writes more evenly.
Why it's wrong here
Sharding helps with hot partitions but does not address overall throughput limits; sudden spikes still cause throttling.
- ✗
Increase the maximum write capacity for Auto Scaling to a higher value, such as 20000 WCU.
Why it's wrong here
This may still not handle extreme spikes and incurs higher cost; Auto Scaling lags behind sudden spikes.
- ✓
Implement an Amazon SQS queue to buffer write requests and process them in batches, with a Lambda function writing to DynamoDB.
Why this is correct
SQS decouples the write path, absorbing spikes and allowing throttled writes to DynamoDB.
Related concept
Static NAT maps one inside address to one outside address.
Common exam traps
Common exam trap: NAT rules depend on direction and matching traffic
NAT is not only about the public address. The inside/outside interface roles and the ACL or rule that matches traffic are just as important.
Detailed technical explanation
How to think about this question
NAT questions usually test address translation, overload/PAT behaviour, static mappings and whether the right traffic is being translated. Read the interface direction and address terms carefully.
KKey Concepts to Remember
- Static NAT maps one inside address to one outside address.
- PAT allows many inside hosts to share one public address using ports.
- Inside local and inside global describe the private and translated addresses.
- NAT ACLs identify traffic for translation, not always security filtering.
TExam Day Tips
- Identify inside and outside interfaces first.
- Check whether the scenario needs static NAT, dynamic NAT or PAT.
- Do not confuse NAT matching ACLs with normal packet-filtering intent.
Key takeaway
NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
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. NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated. 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 the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related DBS-C01 NAT questions on configuration and troubleshooting.
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Workload-Specific Database Design — study guide chapter
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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 — Static NAT maps one inside address to one outside address..
What is the correct answer to this question?
The correct answer is: Implement an Amazon SQS queue to buffer write requests and process them in batches, with a Lambda function writing to DynamoDB. — DynamoDB Auto Scaling can increase capacity, but it reacts to CloudWatch alarms and takes time (minutes). For sudden spikes, the best solution is to use DynamoDB Accelerator (DAX) for reads, not writes. For writes, you can implement exponential backoff and retries in the application, but that may increase latency. Another option is to use a queue (Amazon SQS) to buffer writes and process them at a controlled rate. This decouples the application from the database, allowing spikes to be absorbed. Option A (increase max WCU) helps but may not be enough if spikes are very high and unpredictable. Option B (DAX) does not help with writes. Option C (SQS buffer) is a common pattern. Option D (sharding) requires application changes and may not be necessary. So the best is to use SQS to buffer writes.
What should I do if I get this DBS-C01 question wrong?
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related DBS-C01 NAT questions on configuration and troubleshooting.
What is the key concept behind this question?
Static NAT maps one inside address to one outside address.
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Last reviewed: Jun 20, 2026
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