SAA-C03 Design Cost-Optimized Architectures Practice Question
A team serves static web assets (JS, CSS, images) from an Amazon S3 origin through CloudFront. Recently, the S3 origin has received a high number of requests for the same files, increasing origin data transfer costs. CloudFront access logs show many cache misses, and each request includes a unique query string used only for tracking (for example, ?utm=...). The application does not require query-string-specific content. What CloudFront change will most directly reduce origin fetches and cost?
⚠ Common exam trap
Many exam-takers think enabling Origin Shield (Option C) or changing storage classes (Option D) will solve the problem, but they overlook the fundamental issue of cache key fragmentation caused by unique query strings, which is directly addressed by adjusting the cache policy.
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
✓
Update the CloudFront cache policy to exclude query strings from the cache key so that requests differing only by tracking query parameters reuse the same cached object.
CloudFront's cache policy controls which parts of a request (including query strings) are included in the cache key. By excluding the tracking query strings (e.g., `?utm=...`) from the cache key, CloudFront will treat all requests for the same file as identical, serving the cached object regardless of the query string. This directly reduces the number of origin fetches (cache misses) and lowers S3 data transfer costs, as the application does not require query-string-specific content.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Update the CloudFront cache policy to exclude query strings from the cache key so that requests differing only by tracking query parameters reuse the same cached object.
Why this is correct
CloudFront cache misses increase when the cache key includes values that vary per request. If the tracking query string is part of the cache key, each unique ?utm value generates a separate cache entry even though the underlying object (JS/CSS/image) is identical, causing repeated origin fetches. Excluding query strings from the cache key collapses those variations into a single cached object, increasing the cache hit rate and reducing origin fetches and origin data transfer.
- ✗
Lower the minimum TTL and set Cache-Control headers to no-store to force CloudFront to revalidate more often.
Why it's wrong here
Setting Cache-Control: no-store or aggressively lowering the minimum TTL tells CloudFront not to cache the object (or to treat it as immediately stale). This forces every request to go to the S3 origin for validation or a full fetch, eliminating the benefit of edge caching. Instead of reducing origin fetches, this increases them because even repeated identical requests will miss the cache, driving up S3 GET requests and data transfer costs.
- ✗
Enable Origin Shield to ensure all origin fetches go through a single regional shield with no other configuration changes.
Why it's wrong here
Origin Shield can reduce origin load in some scenarios by improving cache coordination, but it does not change what constitutes a unique cache object. If query strings remain in the cache key, CloudFront will still treat each unique tracking query string as a different cache object, so cache misses and origin fetches will remain high.
- ✗
Switch the S3 origin from S3 to a different storage class optimized for request rates, keeping the cache key the same.
Why it's wrong here
Changing the S3 storage class does not address the root cause: CloudFront cache fragmentation caused by query strings in the cache key. Even with a different storage class, CloudFront will still generate separate cache entries (and therefore origin fetches) for each unique query string.
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 by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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