DVA-C02 Troubleshooting and Optimization Practice Question
A developer is troubleshooting a DynamoDB table that is experiencing high write throttling (ProvisionedThroughputExceededException) on certain days. The table has provisioned write capacity of 1000 WCU. The table has a partition key of 'user_id' which is a UUID. The table is accessed by multiple services. CloudWatch metrics show that the WriteThrottleEvents are spiking during specific hours, and the ConsumedWriteCapacityUnits often reaches 1000. What is the most likely cause of the throttling?
⚠ Common exam trap
Many exam-takers assume throttling must be caused by a hot partition (Option A) when the partition key is not a UUID, but in this case the UUID ensures even distribution, so the real issue is simply insufficient capacity during traffic spikes.
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 provisioned write capacity is insufficient to handle the traffic spikes.
The ConsumedWriteCapacityUnits consistently reaches the provisioned 1000 WCU during specific hours, and WriteThrottleEvents spike at those same times. This indicates that the provisioned capacity is insufficient to handle peak traffic, causing requests to be throttled. The partition key (UUID) is well-distributed, so a hot partition is unlikely.
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 partition key is not distributed evenly, causing a hot partition.
Why it's wrong here
This option is incorrect because using a Universally Unique Identifier (UUID) as a partition key inherently promotes an even distribution of data across partitions. A well-distributed partition key minimizes the likelihood of a single "hot partition" receiving a disproportionate number of requests, which would indeed cause throttling for that specific partition. Therefore, if UUIDs are in use, hot partitions are generally not the root cause of widespread high throttling across the table.
- ✓
The provisioned write capacity is insufficient to handle the traffic spikes.
Why this is correct
This is the correct answer. DynamoDB tables operate on a provisioned throughput model, where Write Capacity Units (WCUs) must be sufficient to handle the incoming write traffic. When the rate of write requests, especially during traffic spikes, exceeds the allocated provisioned write capacity, DynamoDB will begin to throttle requests. This throttling mechanism protects the underlying infrastructure and ensures consistent performance for other requests within the provisioned limits, but it results in rejected write operations for the application.
- ✗
The table does not have DynamoDB Accelerator (DAX) enabled.
Why it's wrong here
This option is incorrect because DynamoDB Accelerator (DAX) is a fully managed, highly available, in-memory cache specifically designed to improve read performance for DynamoDB tables. DAX caches read requests and significantly reduces response times for frequently accessed data. However, DAX has no impact on write operations or the table's provisioned write capacity, and therefore cannot alleviate issues related to write throttling or insufficient write throughput.
- ✗
The table is configured with eventual consistency, which throttles writes.
Why it's wrong here
This option is incorrect because the consistency model configured for a DynamoDB table, whether eventual or strong, exclusively pertains to read operations. Eventual consistency means reads might not reflect the most recent writes immediately, while strong consistency guarantees the latest data. These settings do not influence the table's ability to accept or process write requests; write throttling is solely determined by the available provisioned write capacity units, not by read consistency preferences.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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