Question 1hardmulti select
Full question →hardmulti selectObjective-mapped
A retail analytics table stores events in Amazon DynamoDB with partition key tenantId and sort key eventTime. During a promotion, one tenant generates most writes and repeatedly polls the same latest-status items, causing throttling on a single partition key and high latency on reads. The business can tolerate read results that are a few seconds stale. Which two changes will most effectively reduce throttling and latency? Select two.
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
Introduce write sharding by adding a bounded random suffix to the hot tenant partition key and fan out reads across the shards.
Sharding spreads the hot tenant’s traffic across multiple partitions so DynamoDB is no longer forced to serve all writes through one physical partition. Querying across the shard set restores access to the tenant’s data while reducing throttling. This is the standard fix when a single partition key becomes a hot spot.
B
Best answer
Add DynamoDB Accelerator (DAX) in front of the table for the repeated status reads.
DAX can serve repeated eventually consistent reads from an in-memory cache with microsecond latency. Because the business accepts a few seconds of staleness, DAX is a strong fit for the repeated latest-status access pattern. It reduces read pressure on the table and improves response times for hot read paths.
C
Distractor review
Keep the same key design and increase only the table’s provisioned RCUs and WCUs.
More capacity can help only if the workload is broadly distributed. A single hot partition key can still bottleneck even when table capacity is raised. This option does not change the skewed access pattern that is causing throttling on one partition.
D
Distractor review
Replace the table reads with a Scan operation to distribute the load across all partitions.
A Scan reads many items and is far more expensive and slower than a targeted Query. It would increase latency and consume more capacity, not reduce it. Scans are not a solution for a hot key or for low-latency repeated reads.
E
Distractor review
Move the table to another Availability Zone so the hot tenant uses a different storage node.
DynamoDB is a regional service and its partitioning behavior is not solved by picking a different AZ. The issue is logical data skew, not a single-AZ placement problem. Moving the table would not change the hot partition key pattern.
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: Introduce write sharding by adding a bounded random suffix to the hot tenant partition key and fan out reads across the shards. — The correct approach combines write sharding for the hot tenant and DAX for repeated status reads. Sharding removes the single-partition bottleneck that throttles writes, while DAX speeds up frequent eventual-consistency reads that can safely tolerate a small amount of staleness. Together, they address both sides of the workload: reducing write contention and offloading repeated reads from DynamoDB. Increasing capacity alone does not fix a skewed partition key, and Scan is the wrong access pattern for low-latency status lookups. Availability Zone placement does not solve DynamoDB hot-key behavior because the bottleneck is logical partition distribution. The scenario explicitly allows slightly stale reads, which makes DAX an appropriate and supportable optimization.
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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