Question 1hardmultiple choice
Full question →hardmultiple choiceObjective-mapped
Exhibit
Table schema: - TableName: EventStore - PartitionKey: tenantId (String) - SortKey: eventTime (Number) CloudWatch metrics during promotion: - WriteThrottleEvents: increasing steadily - ConsumedWriteCapacityUnits: near provisioned limit - SuccessfulRequestLatency p95: 14 ms Sample traffic distribution: - tenantId=ACME: 82% of writes, 79% of reads - all other tenants combined: 18% of writes, 21% of reads Application note: - Queries must continue to support tenant-scoped lookups by time range.
Based on the exhibit, a DynamoDB-backed event processing system is throttling during a promotion. The table uses tenantId as the partition key and eventTime as the sort key. One tenant accounts for most of the write traffic, and the application must preserve fast lookups for that tenant without relying on a single hot partition. What change is the best fix?
Answer choices
Why each option matters
Good practice is not just finding the correct option. The wrong answers often show the exact trap the exam wants you to fall into.
A
Best answer
Add a sharding suffix to the partition key, such as tenantId#shardId, and query across the tenant's shards.
Sharding the partition key spreads ACME traffic across multiple partitions, which removes the hot key problem. Because the application still needs tenant-scoped time-range queries, it can fan out across the shard values and merge results.
B
Distractor review
Enable DynamoDB Streams so the table can process writes more quickly.
Streams capture changes after writes succeed, but they do not change partition distribution or write capacity pressure. The hot partition would still throttle under the same traffic pattern.
C
Distractor review
Switch the table to on-demand capacity mode and keep the same key design.
On-demand mode can absorb variable load, but it does not solve a single partition becoming hot. A skewed key can still throttle even when total table capacity increases automatically.
D
Distractor review
Add a global secondary index on eventTime and query the index instead of the base table.
A GSI changes the access pattern, but it still needs a well-distributed partition key. Indexing only by eventTime would not preserve tenant-scoped lookups and could introduce a new hot partition.
Common exam trap
Common exam trap: NAT rules depend on direction and matching traffic
NAT is not only about the public address. The inside/outside interface roles and the ACL or rule that matches traffic are just as important.
Technical deep dive
How to think about this question
NAT questions usually test address translation, overload/PAT behaviour, static mappings and whether the right traffic is being translated. Read the interface direction and address terms carefully.
KKey Concepts to Remember
- Static NAT maps one inside address to one outside address.
- PAT allows many inside hosts to share one public address using ports.
- Inside local and inside global describe the private and translated addresses.
- NAT ACLs identify traffic for translation, not always security filtering.
TExam Day Tips
- Identify inside and outside interfaces first.
- Check whether the scenario needs static NAT, dynamic NAT or PAT.
- Do not confuse NAT matching ACLs with normal packet-filtering intent.
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FAQ
Questions learners often ask
What does this SAA-C03 question test?
Static NAT maps one inside address to one outside address.
What is the correct answer to this question?
The correct answer is: Add a sharding suffix to the partition key, such as tenantId#shardId, and query across the tenant's shards. — The evidence points to a hot partition caused by one tenant dominating traffic on a single partition key value. DynamoDB performance depends heavily on even partition-key distribution. Adding write sharding to the partition key spreads that tenant's load across multiple partitions while still allowing tenant-scoped time-range queries through fan-out. This is the most direct way to improve throughput and remove throttling without changing the business meaning of the data. Streams do not influence write distribution or partition hot spots. On-demand capacity helps with fluctuating overall traffic, but a single hot key can still throttle because the partition, not the table, is the constraint. A GSI on eventTime would not preserve the required tenant-scoped access pattern and may simply move the hot spot somewhere else.
What should I do if I get this SAA-C03 question wrong?
Then try more questions from the same exam bank and focus on understanding why the wrong options are tempting.
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