DEA-C01 Data Store Management Practice Question
An e-commerce company uses Amazon DynamoDB as the primary data store for its product catalog. The table has a simple primary key (ProductID) and handles 10,000 writes per second during peak hours. Recently, the engineering team noticed increased write latency and throttled requests during peak times. The table's provisioned write capacity is set to 12,000 WCU. What is the most likely cause of the throttling?
⚠ Common exam trap
A common mix-up: candidates assume throttling only occurs when total provisioned capacity is exceeded, overlooking the per-partition throughput limits that cause throttling on hot partitions even when the table's overall WCU is underutilized.
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
✓
Write traffic is unevenly distributed across partitions
DynamoDB partitions data by the primary key's hash value. If write traffic is unevenly distributed across partitions (e.g., a few ProductIDs receive most writes), those hot partitions can exceed their individual throughput limits (3,000 WCU per partition for provisioned tables), causing throttling even when the table's total provisioned WCU of 12,000 is not fully utilized.
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 has reached the maximum number of partitions
Why it's wrong here
DynamoDB partitions split automatically as data and throughput grow; there is no fixed maximum partition count that would cause throttling here. It is tempting because partition limits do exist per table, so partition exhaustion is the correct diagnosis when a table genuinely hits the 3,000 RCU or 1,000 WCU per-partition ceiling.
- ✗
DynamoDB Accelerator (DAX) is not configured
Why it's wrong here
DAX caches read operations against DynamoDB; it does not absorb or accelerate writes, so it cannot relieve write throttling on a 12,000 WCU table. It is tempting because DAX genuinely reduces read latency and hot-key read pressure, making it the right choice when a read-heavy workload suffers repeated GetItem or Query latency.
- ✓
Write traffic is unevenly distributed across partitions
Why this is correct
Unevenly distributed write traffic concentrates load on a subset of partitions, so individual partitions exceed their 1,000 WCU per-partition limit even though total provisioned capacity of 12,000 WCU is not exhausted. DynamoDB throttles at partition level, making hot partitions the likely cause of the latency and throttling during peak hours.
- ✗
A global secondary index is consuming write capacity
Why it's wrong here
A global secondary index consumes its own provisioned write capacity, not the base table's 12,000 WCU, so it cannot explain throttling on the table itself. It is tempting because GSIs do cause write throttling, making this the right answer when the index's own WCU is undersized relative to its projected writes.
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Same concept, more angles
1 more way this is tested on DEA-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 large e-commerce company uses Amazon DynamoDB to store shopping cart data. The table has a partition key of 'user_id' and a sort key of 'item_id'. The application performs frequent updates to the 'quantity' attribute for items in a user's cart. Recently, the operations team noticed that write requests are being throttled during peak shopping hours. The table is provisioned with 10,000 write capacity units (WCUs) and uses DynamoDB Accelerator (DAX) for read caching. The data engineer suspects that the throttling is due to hot partitions. The application uses a single AWS SDK client configured with retries. After reviewing the Amazon CloudWatch metrics, the engineer sees that the WriteThrottleEvents metric spikes for a few partition keys. The table has a high number of partitions. What should the data engineer do to resolve the throttling issue with minimal application changes?
hard- A.Increase the provisioned write capacity to 20,000 WCUs permanently.
- B.Enable DynamoDB Global Tables to distribute writes across regions.
- C.Add more nodes to the DAX cluster to offload write traffic.
- ✓ D.Configure DynamoDB Auto Scaling with a maximum WCU setting of 20,000 and a target utilization of 70%.
Why D: DynamoDB Auto Scaling can dynamically adjust write capacity in response to traffic patterns, reducing throttling on hot partitions without requiring application changes. Option A is incorrect because permanently increasing WCUs does not adapt to variable demand and may lead to over-provisioning. Option B (Global Tables) replicates data across regions but does not increase write capacity for a single table, so it does not resolve hot partition throttling. Option C (DAX) is a read cache and does not offload write traffic; it only improves read performance.
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DEA-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DEA-C01 exam.