SAA-C03 Design High-Performing Architectures Practice Question
A financial analytics firm runs a nightly batch job on a fleet of Amazon EC2 instances that read millions of small JSON objects from an Amazon S3 bucket and write aggregated results to another S3 bucket. The job currently takes over six hours and the team wants to reduce this time without modifying the application code. The S3 buckets are in the same AWS Region as the EC2 instances. Which action will most effectively improve the performance of the batch job?
⚠ Common exam trap
The trap here is assuming that S3 Transfer Acceleration or Cross-Region Replication will speed up same-Region access, when the real bottleneck is per-prefix request rate and parallelism.
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
✓
Increase the number of EC2 instances and ensure the S3 keys are distributed across multiple prefixes.
The batch job's performance is constrained by the rate at which it can read and write objects to S3. S3 scales horizontally, but the achievable request rate depends on the number of distinct key prefixes and the level of concurrency. By adding more EC2 instances and distributing keys across multiple prefixes, the job can parallelize requests and fully utilize S3's scalability, dramatically reducing the six-hour runtime without modifying application logic.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Increase the number of EC2 instances and ensure the S3 keys are distributed across multiple prefixes.
Why this is correct
S3 automatically scales to high request rates, but the achieved throughput depends on the number of prefixes and the parallelism of requests. By adding more EC2 instances and spreading object keys across many prefixes, the job can issue more concurrent GET and PUT requests, each prefix supporting thousands of requests per second. This directly reduces the overall processing time without code changes.
- ✗
Switch the batch job to use S3 Select to retrieve only the necessary fields from each JSON object.
Why it's wrong here
S3 Select allows filtering of object content using SQL expressions, reducing data transferred, but it does not increase the number of requests that can be processed per second. The bottleneck is likely the request rate, not the amount of data per object. For millions of small objects, S3 Select adds per-request overhead and does not address the need for higher parallelism and prefix distribution.
- ✗
Configure the EC2 instances to use S3 Transfer Acceleration for all requests.
Why it's wrong here
S3 Transfer Acceleration speeds up uploads and downloads over long distances by routing through AWS edge locations, but the EC2 instances and S3 bucket are in the same Region, so the optimization provides little benefit. Additionally, Transfer Acceleration is designed for large transfers over the public internet, not for high-volume small-object operations within a Region. It also incurs extra cost without addressing the request-per-second limits.
- ✗
Enable S3 Cross-Region Replication to a bucket in a different Region and redirect the job to the replica.
Why it's wrong here
Cross-Region Replication copies objects asynchronously to another Region, which introduces latency and does not increase the request throughput for the source bucket. The batch job would still read from the same source or a replica that may not be fully synchronized. This approach adds complexity and data transfer costs while failing to address the fundamental per-prefix request rate limits.
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
Go deeper
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Amazon Web Services exam blueprint
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