SAA-C03 - Design Cost-Optimized Architectures (20% of the exam) - Section 4.4

Reduce compute cost through right-sizing, serverless adoption and AWS Compute Optimizer recommendations.

Use AWS Compute Optimizer recommendations, which analyse CloudWatch metrics to flag over-provisioned EC2 instances and suggest smaller types with equivalent performance at lower cost. Weigh migrating suitable workloads to AWS Lambda, billed only on invocation count and duration, against the overhead of always-on instances, and configure Auto Scaling to remove idle capacity during low-demand periods.

AWS Compute OptimizerRight-sizingAWS Lambda costAuto Scaling

Practice question for this objective

Free sampleDesign Cost-Optimized Architecturesmedium

A company runs a production EC2 fleet whose CPU and memory utilisation has never been measured. AWS Compute Optimizer is enabled and reports many instances as over-provisioned, with recommendations to move to smaller instance sizes and, for some, to a different instance family. The team wants to act on these data-driven findings to cut compute cost while still meeting each workload's observed demand. Which two actions directly implement the Compute Optimizer right-sizing recommendations? Select TWO.

  • APurchase three-year All Upfront Reserved Instances for the current over-provisioned instance sizes to lock in the deepest committed discount immediately.
  • BMove the over-provisioned production instances onto EC2 Spot Instances so the whole fleet draws from discounted spare capacity instead.
  • CResize over-provisioned instances down to the smaller instance types Compute Optimizer recommends after confirming the new size meets observed CPU and memory demand. Correct
  • DEnable an Auto Scaling group with a high desired capacity so additional instances absorb any demand the smaller instances cannot handle.
  • EInstall the CloudWatch agent to collect memory metrics, then migrate the flagged instances to the recommended instance family informed by that fuller utilisation picture. Correct
Acting on AWS Compute Optimizer findings means right-sizing instances to recommended smaller types and families, supplying memory metrics so recommendations reflect true demand. Compute Optimizer analyses utilisation and recommends smaller sizes or different families; the corrective actions are to resize down to the recommended type and to feed it memory data via the CloudWatch agent so family and size advice reflects real demand. Reserved Instances, Spot and scaling out change pricing or capacity but do not implement the right-sizing the recommendations call for.

Why A is wrong: Reserved Instances cut the rate but committing to the oversized footprint locks in waste, and buying before right-sizing is the opposite of acting on the recommendations.

Why B is wrong: Spot suits interruptible, stateless workloads and risks reclaim on a production fleet, so it changes the pricing model rather than implementing the size and family right-sizing advice.

Why C is correct: Right-sizing to the recommended smaller type removes paid-for idle capacity while still covering the measured workload, which is the core action Compute Optimizer findings drive.

Why D is wrong: Scaling out adds instances and cost rather than reducing the size of existing over-provisioned ones, so it does not implement the right-sizing recommendation.

Why E is correct: Memory is not a default EC2 metric, so the agent gives Compute Optimizer the memory data to refine family and size recommendations, and migrating to the recommended family completes the right-sizing.

See more SAA-C03 practice questions, answers explained.

Exam traps in Design Cost-Optimized Architectures

Answers that look right on this material and are not. Each one is a distractor from a different question in the SAA-C03 bank for this domain.

  • Enable AWS Cost Explorer rightsizing reports, which forecast next month's bill and group the EC2 spend by linked account for finance.

    Why it is wrong: Cost Explorer does surface a rightsizing view and is finance-friendly, but its core job is cost visualisation and forecasting rather than the detailed per-instance type analysis Compute Optimizer provides.

  • Buy Reserved Instances for the two EC2 servers so the always-on capacity that backs the internal API is charged at a committed lower rate.

    Why it is wrong: Reserved Instances cut the rate for capacity you keep running, but the team would still pay for two idle servers all day, so it lowers the bill without removing the idle waste.

  • Switch the fleet to burstable T-family instances of the same vCPU count and rely on accrued CPU credits to sustain the steady throughput the service requires.

    Why it is wrong: Burstable instances suit spiky low-average workloads, but a steady-throughput service exhausts CPU credits and is throttled, so this does not preserve the same throughput.

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