hardmultiple choiceObjective-mapped

Exhibit

DynamoDB access pattern report:
- TableName: SessionState
- Read pattern: GetItem on the same 500 keys during active sessions
- Read frequency: 1.2 million reads/minute during peak periods
- Cacheability: yes, stale data up to 5 seconds is acceptable

CloudWatch metrics:
- ConsumedReadCapacityUnits: 92% of provisioned limit
- SuccessfulRequestLatency p95: 7.5 ms
- ThrottledRequests: intermittent during peaks

Application note:
- Writes are comparatively rare and do not need multi-Region replication.

Based on the exhibit, an application repeatedly reads the same DynamoDB items with extremely low latency requirements. The business can tolerate data that is a few seconds stale. Which architecture change best improves read performance?

Question 1hardmultiple choice
Full question →

Based on the exhibit, an application repeatedly reads the same DynamoDB items with extremely low latency requirements. The business can tolerate data that is a few seconds stale. Which architecture change best improves read performance?

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.

DAX is designed for repeated, read-heavy DynamoDB access patterns where a small amount of staleness is acceptable. It can dramatically reduce read latency and offload the table during peak demand.

B

Distractor review

Increase the table's sort key cardinality while keeping the same read pattern.

Changing sort key cardinality does not help if the application repeatedly reads the same items. The bottleneck is repeated reads, not range query design.

C

Distractor review

Switch the table to provisioned mode with auto scaling disabled.

Disabling auto scaling removes an important safety mechanism and does not reduce latency. It may also worsen throttling during peaks if capacity is not manually tuned.

D

Distractor review

Move the session data to Amazon EFS so the application can read it from shared files.

EFS is a file system, not a low-latency key-value cache. Moving the data would change the data model and would not provide the same read performance characteristics as DAX.

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. — The workload is a classic candidate for DAX: the same items are read repeatedly, the application needs very low latency, and a few seconds of staleness is acceptable. DAX caches DynamoDB read results and can absorb a large share of the traffic, reducing both latency and consumed read capacity on the table. This directly addresses the exhibit's peak-time throttling and high read utilization. Sort key changes do not reduce repeated GetItem load on the same keys. Disabling auto scaling removes flexibility and can worsen peak throttling. EFS is the wrong storage model for cache-like DynamoDB access and would introduce a new architecture without improving the read path.

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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