DynamoDB Throttling Due to Hot Partitions
A company is troubleshooting an Amazon DynamoDB table that is throttling write requests. The table has a partition key ('userId') and a sort key ('timestamp'). The 'WriteCapacityUnits' is set to 1000. CloudWatch shows 'ThrottledWriteRequests' but the 'ConsumedWriteCapacityUnits' is only 500. Which TWO actions could resolve the throttling?
Quick Answer
The correct answers are A and B: adding a random suffix to the partition key and increasing the write capacity units. This resolves DynamoDB throttling due to hot partitions because a single partition is limited to 1000 WCU; when a partition key like 'userId' creates uneven access, one partition can hit its ceiling even though overall consumed capacity is only 500, causing throttled write requests. On the AWS Certified Database Specialty DBS-C01 exam, this scenario tests your understanding that provisioned throughput is distributed across partitions, and a hot partition throttles independently of total capacity. A common trap is assuming DAX (Option D) helps writes—it only caches reads—or that Global Tables (Option E) reduce throttling, when they actually replicate writes and can worsen it. Memory tip: “Hot partition, cool fix—spread the key or raise the ceiling.”
⚠ Common exam trap
Candidates often confuse throttling due to hot partitions with overall capacity shortage. They may think increasing capacity is unnecessary when consumed capacity is low, but it can help by increasing partitions.
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
✓
Add a random suffix to the partition key to distribute writes more evenly
The issue is throttling on write requests despite consumed capacity below provisioned. This indicates a hot partition where one partition receives more writes than its limit (1000 WCU per partition). Option A (add random suffix to partition key) distributes writes across partitions, preventing any single partition from exceeding its limit. Option C (increase write capacity units) can increase the number of partitions, thereby distributing the load and potentially raising the per-partition limit. Option B is incorrect because DAX is a read cache and does not affect write throughput. Option D (Global Tables) does not resolve throttling and may add latency. Option E (removing sort key) does not address partition hotness.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Add a random suffix to the partition key to distribute writes more evenly
Why this is correct
Randomizing the partition key helps distribute write load across partitions, reducing throttling.
- ✗
Enable DynamoDB Accelerator (DAX) to cache writes
Why it's wrong here
DAX is a read cache and does not handle write requests.
- ✓
Increase the write capacity units to allow more throughput
Why this is correct
Increasing WCU can increase the number of partitions, distributing the load.
- ✗
Enable Global Tables to replicate writes across regions
Why it's wrong here
Global Tables add more writes and could increase throttling.
- ✗
Remove the sort key and use only a partition key
Why it's wrong here
Removing the sort key does not affect partition distribution.
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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 running a production Amazon DynamoDB table and notices that read requests are being throttled. The table has on-demand capacity mode enabled. Which action should the database specialist take to troubleshoot the throttling?
easy- ✓ A.Check the CloudWatch metric 'ThrottledRequests' for the table and review 'SystemErrors' to identify hot partitions.
- B.Enable auto scaling on the table to automatically adjust capacity.
- C.Enable DynamoDB Accelerator (DAX) to reduce read load on the table.
- D.Switch the table to provisioned capacity mode and increase the read capacity units.
Why A: With on-demand capacity, throttling often results from hot partitions. The CloudWatch metric 'ThrottledRequests' helps detect throttling, and reviewing 'SystemErrors' can indicate partition-level errors, aiding in identifying hot partitions. Option B is incorrect because auto scaling is only supported for provisioned capacity mode, not on-demand. Option C is incorrect because enabling DAX can reduce read load but does not address the root cause of throttling due to hot partitions; it is not a troubleshooting step. Option D is incorrect because switching to provisioned capacity and increasing RCUs is a remediation action, not a troubleshooting action.
Variation 2. A company uses Amazon DynamoDB and notices that some queries are taking longer than expected. The table has a partition key only. The 'ConsumedReadCapacityUnits' is below the provisioned throughput. What is the most likely cause of the slow queries?
easy- A.DAX is misconfigured and slowing down reads
- B.Global tables replication is causing delays
- C.DynamoDB Streams is enabled and consuming read capacity
- ✓ D.The partition key is not distributed evenly, causing hot partitions
Why D: If the partition key is not chosen well, data can be skewed, causing hot partitions. Even if total consumed capacity is below provisioned, a single partition may receive more requests than its share of capacity, causing throttling on that partition, which slows queries. Option A is wrong because DAX is a caching layer that speeds up reads, not slows them. Option B is wrong because global tables replication does not affect read latency on the source table. Option C is wrong because DynamoDB Streams do not consume read capacity for reads from the table; they use separate capacity.
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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