SAA-C03 Design High-Performing Architectures Practice Question
A DynamoDB table for a retail API has a partition key based only on the current date. Write throttling occurs during business hours. What is the best design change? The design must avoid adding custom operational scripts.
⚠ Common exam trap
Watch out — candidates often confuse GSIs as a solution for write hot spots, but GSIs only help with read patterns and do not change the base table's write distribution.
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
✓
Use a higher-cardinality partition key that distributes writes across partitions
Using only the current date as a partition key creates a 'hot partition' because all writes for the day target a single partition, exceeding its 1,000 WCU limit. A higher-cardinality partition key (e.g., combining date with user ID or order ID) distributes writes evenly across partitions, eliminating throttling without custom scripts.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Use a higher-cardinality partition key that distributes writes across partitions
Why this is correct
A partition key with only two distinct values funnels all writes into two partitions, each capped at 1,000 write capacity units, so a high write volume quickly throttles. Introducing a higher-cardinality key—such as customer ID or a composite key with a random suffix—spreads writes across many partitions, letting the table utilize its full provisioned capacity and avoid any single hot partition.
- ✗
Create a global secondary index with the same date key
Why it's wrong here
Creating a global secondary index on the same low-cardinality date key does not fix the root problem because the GSI maintains its own partitions and is subject to the same 1,000-WCU-per-partition limit. Every write to the base table also propagates to the GSI synchronously, so the GSI's date-only key would simply become another hot partition, causing the same throttling errors and potentially doubling the write cost.
- ✗
Reduce the table's write capacity
Why it's wrong here
Reducing the table's write capacity is diametrically opposite to solving a throttling problem: it lowers the total provisioned write budget available across partitions, making the hot partition even more likely to exhaust its allowance. Throttling occurs because one key receives disproportionate traffic, not because total capacity is wasted; the fix is to redistribute writes, not to shrink the capacity granted to the entire table.
- ✗
Move the table to S3 Glacier Instant Retrieval
Why it's wrong here
S3 Glacier Instant Retrieval is an object-storage class designed for long-lived, infrequently retrieved archives, not a transactional database for high-throughput item writes. Moving a DynamoDB table to it would abandon DynamoDB's partition-aware write engine, and the service cannot serve low-latency, item-level read/update/delete operations via the DynamoDB API; it is also not a way to scale write throughput for a hot key.
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