Jeff’s Note #
Unlike generic dumps, ADH analyzes this scenario through the lens of a Real-World Site Reliability Engineer (SRE).
For SOA-C02 candidates, the confusion often lies in when to rely on Cost Explorer or RI purchasing versus leveraging Compute Optimizer recommendations. In production, this is about understanding exactly how to rightsize EC2 instances with minimal manual guesswork and controlling costs via saving plans or RI strategies. Let’s drill down.
The Certification Drill (Simulated Question) #
Scenario #
A fintech startup, FinEdge Analytics, has fully migrated their customer-facing application to AWS. Their application runs across several Amazon EC2 instance families for various workloads. During load testing, the SRE team notices inconsistent performance patterns on some EC2 instances, suggesting mismatched instance types for the workload profiles.
Due to strict budget constraints mandated by FinEdge’s finance department, the SRE must implement a strategy to ensure EC2 instances are sized correctly to meet workload demands without overspending or under-provisioning.
The Requirement: #
Identify the best approach the SRE should take to match EC2 instance types with workload needs, while adhering to budget and optimizing resource utilization.
The Options #
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A) Purchase regional Reserved Instances (RIs) immediately to lower costs. Analyze and implement EC2 instance resizing recommendations from Cost Explorer. After resizing, exchange the RIs to align with the new instance families.
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B) Buy availability zone–specific Reserved Instances (RIs) for the existing EC2 instances. Continuously monitor RI utilization via the AWS Billing and Cost Management console. Adjust instance sizes over time to optimize usage.
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C) Review and apply recommendations from AWS Compute Optimizer for instance sizing. Purchase Compute Savings Plans to reduce the cost of running compute resources.
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D) Examine resource utilization metrics from the AWS Cost and Usage Report. Manually resize EC2 instances accordingly. Create On-Demand Capacity Reservations for the resized instances.
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Correct Answer #
C
Quick Insight: The SOA-C02 Imperative #
- For SysOps professionals, AWS Compute Optimizer offers precise, workload-informed recommendations that are more dynamic and workload-specific than static billing data.
- Compute Savings Plans provide flexible cost reduction across different instance families without locking into one availability zone or instance type, unlike RIs.
- This combination optimizes both operational efficiency and cost adherence without manual overhead.
Content Locked: The Expert Analysis #
You’ve identified the answer. But do you know the implementation details that separate a Junior from a Senior?
The Expert’s Analysis #
Correct Answer #
Option C
The Winning Logic #
AWS Compute Optimizer analyzes actual utilization metrics of your EC2 instances and generates precise resizing recommendations—downsizing or rightsizing instances to better match your workload needs. This is critical for avoiding over-provisioning or underperformance.
Combining this with Compute Savings Plans helps FinEdge reduce costs flexibly across instance families and regions, without being locked into a single instance type or AZ like Reserved Instances often are.
- Compute Optimizer removes guesswork and provides actionable data-driven insights.
- Savings Plans deliver predictable savings while maintaining instance flexibility.
- This dual strategy aligns with both performance reliability and FinEdge’s budget policies.
The Trap (Distractor Analysis): #
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Why not A? Although Cost Explorer provides sizing recommendations, they are more generic and less workload-specific compared to Compute Optimizer. Exchanging RIs adds complexity and potential delays.
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Why not B? AZ-specific RIs reduce flexibility, risking wasted spend if workload shifts or instance types change. Simply monitoring RI utilization does not proactively optimize sizing.
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Why not D? AWS Cost and Usage Reports provide billing-centric data, not detailed performance metrics. Manually resizing without Compute Optimizer’s insights risks mis-sizing. On-Demand Capacity Reservations increase cost and reduce flexibility.
The Technical Blueprint #
# Retrieve Compute Optimizer EC2 recommendations using AWS CLI
aws compute-optimizer get-ec2-instance-recommendations \
--instance-arns arn:aws:ec2:region:account-id:instance/instance-id
# Purchase Compute Savings Plan with AWS CLI (example)
aws savingsplans purchase-savings-plan \
--savings-plan-offering-id "abcdefg-1234-5678-90ab-cdef12345678" \
--commitment 3600 \
--term 31536000 \
--payment-option ALL_UPFRONT
The Comparative Analysis #
| Option | Operational Overhead | Automation Level | Cost Impact | Flexibility | Suitability |
|---|---|---|---|---|---|
| A | Moderate | Low | Moderate savings upfront | Limited by RI type | Risky if workload changes |
| B | High | Low | Savings locked to AZ | Limited flexibility | Monitoring alone insufficient |
| C | Low | High | Significant with Savings | Highly flexible | Ideal for dynamic workloads |
| D | High | None | High cost reservation | Low flexibility | Manual and expensive approach |
Real-World Application (Practitioner Insight) #
Exam Rule #
For the exam, always pick Compute Optimizer plus Savings Plans when tasked with performance tuning and cost optimization simultaneously.
Real World #
In practice, many orgs first try Reserved Instances but often move to Savings Plans combined with Compute Optimizer for agility and easier lifecycle management.
(CTA) Stop Guessing, Start Mastering #
Disclaimer
This is a study note based on simulated scenarios for the AWS SOA-C02 exam.