Question 135 of 1,663
Why DynamoDB On-Demand Throttles: Common Causes
A company is using Amazon DynamoDB with on-demand capacity mode. The application experiences occasional throttling on a table during peak hours. The table's read and write requests are within the throughput limits, but the provisioned read/write capacity is exceeded. What is the most likely cause of this throttling?
Quick Answer
The answer is that the table’s previous peak throughput was lower than the current traffic, and DynamoDB is still adapting. This is because on-demand capacity mode automatically scales to handle up to your table’s previous peak throughput within 30 minutes, but a sudden spike beyond that historical peak can trigger throttling while the service adjusts to the new demand. On the AWS Certified Database Specialty DBS-C01 exam, this concept tests your understanding that on-demand is not infinite—it has a “memory” of past traffic, and throttling occurs when you exceed that remembered peak, not a provisioned limit. A common trap is assuming on-demand never throttles or confusing it with provisioned capacity limits. Remember the memory tip: “On-demand remembers your last peak; spike past it and you’ll leak.”
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
✓
The table's previous peak throughput was lower than the current traffic, and DynamoDB is still adapting.
On-demand capacity mode in DynamoDB automatically scales based on the table's previous peak throughput. If current traffic suddenly exceeds that previous peak, DynamoDB may throttle requests until it adapts to the new traffic level, even if the requests are within the eventual on-demand limits. Option B is incorrect because although a hot partition can cause throttling, the question states that read and write requests are within the throughput limits, implying the issue is not at the partition level but rather a sudden spike beyond the adapted peak. Option C is incorrect because on-demand mode has no maximum throughput limit; it scales automatically. Option D is incorrect because on-demand mode does not use provisioned capacity; it scales without manual configuration.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
The table's previous peak throughput was lower than the current traffic, and DynamoDB is still adapting.
Why this is correct
On-demand capacity mode can throttle if traffic exceeds the table's previous peak by a large margin, as DynamoDB needs time to scale up.
- ✗
The table has a hot partition that is receiving more requests than the partition can handle.
Why it's wrong here
While hot partitions can cause throttling, the question indicates that overall requests are within limits, suggesting the issue is not partition-level.
- ✗
The table has exceeded the maximum allowed throughput for on-demand capacity mode.
Why it's wrong here
On-demand capacity mode does not have a maximum throughput limit; it can scale to handle very high traffic.
- ✗
The table's provisioned read/write capacity is set too low.
Why it's wrong here
On-demand mode does not use provisioned capacity; it scales automatically based on traffic.
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Same concept, more angles
2 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 using Amazon DynamoDB with on-demand capacity mode. The company notices that during a flash sale, the write requests are throttled. What is the most likely cause of the throttling?
easy- A.The table has reached its maximum throughput limit for on-demand mode.
- B.The table is not configured for auto scaling.
- ✓ C.A hot partition is causing throttling even though the table uses on-demand capacity.
- D.The provisioned write capacity units (WCUs) are set too low.
Why C: For a DynamoDB table in on-demand capacity mode, throttling is typically caused by a hot partition. On-demand mode automatically scales table-level throughput, but if a single partition key is heavily accessed (e.g., during a flash sale), that partition can exceed its individual capacity limit, resulting in throttled write requests. This is the most likely cause, making option C correct. Option A (maximum throughput limit) does not apply because on-demand has no fixed maximum; option B (auto scaling) is irrelevant since on-demand manages scaling automatically; option D (provisioned WCUs) is not used in on-demand mode.
Variation 2. A company is using Amazon DynamoDB with on-demand capacity for a serverless web application. The application experiences occasional throttling. The DynamoDB table has a simple primary key (partition key only). The throttled requests are related to a small number of partition keys. What is the MOST likely cause?
easy- A.On-demand capacity has a per-partition throughput limit that is too low.
- ✓ B.The partition key design leads to uneven access patterns, causing a hot partition.
- C.The table uses a composite primary key, which limits throughput.
- D.The table's read/write capacity mode is set to provisioned instead of on-demand.
Why B: Throttling on a few partition keys indicates a hot partition. Option A is wrong because on-demand capacity handles overall traffic, but partition-level limits still apply. Option C is wrong because a simple primary key is fine, but the data distribution is the issue. Option D is wrong because on-demand capacity automatically scales, but not per partition beyond the limit.
Last reviewed: Jun 20, 2026
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