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Question 1,416 of 1,730

Workload-Specific Database Design →hardMultiple ChoiceObjective-mapped

Avoiding DynamoDB Per-Partition Throttling with Write Sharding

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 gaming company uses Amazon DynamoDB as the primary data store for player profiles and game state. The application experiences sudden spikes in traffic during new game launches, causing throttling on write requests. The current table has on-demand capacity mode. The table's partition key is 'player_id' (high cardinality). The read/write patterns are evenly distributed. Despite on-demand mode, throttling occurs because the per-partition throughput limit is being reached. The company wants to eliminate throttling without changing the partition key. Which solution should be recommended?

Clue words in this question

Noticing these words before you look at the options changes how you read each choice.

Clue: "primary"
Why it matters: Asks for the main purpose or function, not a secondary benefit. Eliminate answers that describe side-effects or partial functions.

A
Implement Amazon DynamoDB Accelerator (DAX) to offload read traffic.
Why wrong: DAX does not help with write throttling.
B
Use DynamoDB auto scaling with provisioned capacity.
Why wrong: Auto scaling does not overcome per-partition limits.
C
Enable DynamoDB adaptive capacity and implement write sharding using a random suffix.
Adaptive capacity helps distribute load; write sharding further spreads writes across partitions.
D
Switch to provisioned capacity mode and increase write capacity units.
Why wrong: Per-partition limit still applies.

Full breakdown with real-world context →

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

✓

Enable DynamoDB adaptive capacity and implement write sharding using a random suffix.

Option C is correct. On-demand capacity mode already scales automatically, but per-partition throughput limits can still be reached if a single partition receives too many writes. Adaptive capacity (enabled by default) helps by dynamically adjusting per-partition throughput based on traffic patterns. However, if a specific partition key value experiences hot-spotting, write sharding—adding a random suffix to the partition key—further distributes writes across multiple partitions, increasing overall write capacity. Option A (DAX) caches reads, not writes. Option B (auto scaling with provisioned) does not solve per-partition limits; it adjusts table-level capacity. Option D (provisioned with increased WCU) also addresses table-level capacity, not per-partition limits.

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.

✗
Implement Amazon DynamoDB Accelerator (DAX) to offload read traffic.
Why it's wrong here
DAX does not help with write throttling.
✗
Use DynamoDB auto scaling with provisioned capacity.
Why it's wrong here
Auto scaling does not overcome per-partition limits.
✓
Enable DynamoDB adaptive capacity and implement write sharding using a random suffix.
Why this is correct
Adaptive capacity helps distribute load; write sharding further spreads writes across partitions.
Clue confirmation
The clue word "primary" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
Switch to provisioned capacity mode and increase write capacity units.
Why it's wrong here
Per-partition limit still applies.

Common exam traps

Common exam trap: answer the scenario, not the keyword

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

How to think about this question

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.

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.
Use explanations to understand the rule behind the answer.

TExam Day Tips

Underline the problem statement mentally.
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 startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.

What to study next

Got this wrong? Here's your next step.

Identify which DBS-C01 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

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: Enable DynamoDB adaptive capacity and implement write sharding using a random suffix. — Option C is correct. On-demand capacity mode already scales automatically, but per-partition throughput limits can still be reached if a single partition receives too many writes. Adaptive capacity (enabled by default) helps by dynamically adjusting per-partition throughput based on traffic patterns. However, if a specific partition key value experiences hot-spotting, write sharding—adding a random suffix to the partition key—further distributes writes across multiple partitions, increasing overall write capacity. Option A (DAX) caches reads, not writes. Option B (auto scaling with provisioned) does not solve per-partition limits; it adjusts table-level capacity. Option D (provisioned with increased WCU) also addresses table-level capacity, not per-partition limits.

What should I do if I get this DBS-C01 question wrong?

Are there clue words in this question I should notice?

Yes — watch for: "primary". Asks for the main purpose or function, not a secondary benefit. Eliminate answers that describe side-effects or partial functions.

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 uses Amazon DynamoDB to store user session data for a web application. The table has a partition key of 'user_id' and no sort key. Each item is about 5 KB. The application performs frequent GetItem and UpdateItem operations. Recently, the application has been experiencing higher than expected latency and some throttling. The table's read and write capacity are set to on-demand mode. The CloudWatch metrics show that the ConsumedWriteCapacityUnits are well below the provisioned limits (if they were provisioned), but there are occasional ThrottledWriteEvents. The application team also notices that the throttling occurs for specific users. What is the most likely cause and solution?

medium

A.Create a global secondary index with a different partition key for the hot users.
B.Add a sort key to the table to improve data distribution.
✓ C.Implement write sharding by appending a random suffix to the partition key for high-traffic users.
D.Switch to provisioned capacity mode and increase the write capacity units significantly.

Why C: The correct answer is C: Implement write sharding by appending a random suffix to the partition key for high-traffic users. In DynamoDB on-demand mode, each partition can handle up to 3000 read request units or 1000 write request units per second. When a single partition key (user_id) receives high write traffic, that partition can become a hot partition and be throttled, even though overall consumption is within limits. Write sharding distributes the writes for a hot user across multiple partition key values by adding a random suffix to the user_id, thereby spreading the load across multiple partitions. Option A (creating a GSI) would not solve the base table write throttling because the base table writes still target the same partition. Option B (adding a sort key) does not change the partition key distribution; the partition key remains the same, so the hot partition issue persists. Option D (switching to provisioned capacity) would not automatically solve the hot partition; it would require proper partition design similarly.

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