hardmultiple choiceObjective-mapped

Exhibit

DynamoDB metrics and access pattern:
- Table mode: on-demand
- ConsumedReadCapacityUnits: steady, no throttling overall
- SuccessfulRequestLatency: p95 = 34 ms
- Hot partition key detected: tenant#42 consumes 92% of read traffic during peak
Application notes:
- Requests repeatedly fetch the same dashboard items for up to 60 seconds
- Reads are eventually consistent and the application can tolerate brief cache staleness
- Writes are infrequent and do not dominate the workload

Based on the exhibit, which design change is the best way to reduce the observed read latency for this DynamoDB-backed service?

Question 1hardmultiple choice
Full question →

Based on the exhibit, which design change is the best way to reduce the observed read latency for this DynamoDB-backed service?

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 DynamoDB Accelerator (DAX) cluster in front of the table and send repeated read traffic through it.

DAX is designed to accelerate repeated eventually consistent reads from DynamoDB by caching hot items in memory. The exhibit shows one tenant driving most of the reads and the same dashboard items being requested repeatedly within a short window, which is an excellent fit for DAX. It reduces latency and offloads the hot key without requiring a schema redesign.

B

Distractor review

Increase the on-demand table limits so DynamoDB can automatically absorb more traffic.

On-demand already scales capacity automatically, and the problem here is hot, repeated reads with cacheable data rather than missing capacity.

C

Distractor review

Create a global secondary index on tenantId to distribute the load across more partitions.

A GSI changes access paths, but it does not cache repeated reads and may add write overhead without solving the hot-read pattern.

D

Distractor review

Move the dashboard data into S3 and use Lambda functions to read it on demand.

That would replace a low-latency database with an object-storage workflow and would worsen the user-facing read path.

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.

Related practice questions

Related SAA-C03 practice-question pages

Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.

More questions from this exam

Keep practising from the same exam bank, or move into a focused topic page if this question exposed a weak area.

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 DynamoDB Accelerator (DAX) cluster in front of the table and send repeated read traffic through it. — The exhibit highlights repeated reads of the same dashboard items, a hot tenant, and an acceptable tolerance for brief staleness. That combination makes DAX the best fit because it caches hot DynamoDB items in memory and serves repeated eventually consistent reads with much lower latency. Since the table is already on-demand and not throttling globally, adding capacity would not address the real problem. The fastest win is to cache the repeated reads, not to resize the table. Why others are wrong: On-demand capacity is already handling the overall load, so more capacity does not directly solve repeated-read latency. A GSI can help with access pattern changes, but it does not provide a read cache and can increase write work. S3 is not an appropriate replacement for a low-latency, frequently updated operational data store and would make the user experience slower, not faster.

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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