SAA-C03: Design Cost-Optimized Architectures
Design Cost-Optimized Architectures is one of the skill areas tested on the Solutions Architect – Associate (SAA-C03) exam. Below are free SAA-C03 practice questions with worked answers and a concept diagram — each with a plain-language explanation. Practice the first 10 questions of SAA-C03 free, no signup.
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2 free SAA-C03 Design Cost-Optimized Architectures questions
A hospital network writes nightly database exports to an Amazon S3 bucket using S3 Standard. Billing staff open the exports daily during the first 30 days for reconciliation, after which the files are never read again, but regulations require the hospital to retain them permanently. The finance team wants the lowest possible storage bill. What should a solutions architect recommend?
- Enable S3 Intelligent-Tiering on the bucket and let it move objects between access tiers based on observed usage.
- Create an S3 Lifecycle rule that transitions objects to S3 One Zone-Infrequent Access 30 days after creation.
- ✓ Create an S3 Lifecycle rule that transitions objects to S3 Glacier Deep Archive 30 days after creation.
- Create an S3 Lifecycle rule that transitions objects to S3 Standard-Infrequent Access 30 days after creation.
The access pattern is already known and stops completely at 30 days, so a lifecycle rule straight into S3 Glacier Deep Archive gives the cheapest per-gigabyte storage Amazon S3 offers, and its multi-hour retrieval time is irrelevant for files nobody reads. Intelligent-Tiering charges a per-object monitoring fee to discover a pattern the hospital can already describe, and its automatic tiers cost more than Deep Archive. Standard-Infrequent Access is priced for data that is still occasionally read and costs several times more per gigabyte than Deep Archive. One Zone-Infrequent Access is cheaper than Standard-IA but stores only one Availability Zone copy, a poor choice for records that must survive indefinitely, and it is still far more expensive than Deep Archive.
A data engineering team runs a 48-hour regression suite against an Amazon RDS for PostgreSQL instance once a month. Nothing else connects to the database in between runs, and the team must keep the exact same instance class during each run so timing results stay comparable. What is the cheapest way to run this schedule?
- Attach an Auto Scaling policy to the DB instance so it scales itself down as soon as each regression run finishes.
- ✓ Take a snapshot when the run finishes, delete the DB instance, and restore that snapshot to the same instance class before the next run.
- Stop the DB instance when the run finishes and start it again when the next month's run begins.
- Resize the DB instance to a small burstable class after each run and resize it back up before the next one.
Deleting the instance after taking a snapshot leaves only snapshot storage to pay for, and restoring that snapshot to the same class before the next run preserves both the data and the performance profile. Stopping the instance looks appealing but Amazon RDS automatically starts a stopped instance again after seven days, so with a monthly cadence the team would pay instance hours for most of every month. Resizing down still bills for a running instance every hour of the other 28 days. Amazon RDS has no Auto Scaling for instance size at all, only storage autoscaling, so there is no policy that shrinks compute after a test run.
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