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CLF-C02 · Question #40

Which AWS service uses AWS Compute Optimizer to provide sizing recommendations based on workload metrics?

The correct answer is A. Amazon EC2. Explanation Amazon EC2 is the correct answer because AWS Compute Optimizer analyzes CloudWatch utilization metrics from EC2 instances and Auto Scaling groups to deliver machine learning-based recommendations for optimal instance types and sizes, helping reduce costs and improve p

Submitted by helene.fr· Mar 6, 2026Cloud Technology and Services

Question

Which AWS service uses AWS Compute Optimizer to provide sizing recommendations based on workload metrics?

Options

  • AAmazon EC2
  • BAmazon RDS
  • CAmazon Lightsail
  • DAWS Step Functions

How the community answered

(22 responses)
  • A
    86% (19)
  • B
    5% (1)
  • C
    9% (2)

Explanation

Explanation

Amazon EC2 is the correct answer because AWS Compute Optimizer analyzes CloudWatch utilization metrics from EC2 instances and Auto Scaling groups to deliver machine learning-based recommendations for optimal instance types and sizes, helping reduce costs and improve performance.

Amazon RDS (B) has its own built-in recommendations through the RDS console and Performance Insights, but it is not integrated with AWS Compute Optimizer - Optimizer focuses on compute resources, not managed databases.

Amazon Lightsail (C) is a simplified, fixed-bundle service for smaller workloads and does not integrate with Compute Optimizer, as it abstracts away the granular resource configuration that Optimizer requires.

AWS Step Functions (D) is a serverless workflow orchestration service that has no relevance to compute sizing recommendations, as it coordinates tasks rather than managing underlying compute resources.

Memory Tip

Think of "Compute" Optimizer = EC2 (Compute)" - the word Compute in the service name is your direct clue. Compute Optimizer was purpose-built to right-size compute instances (EC2, Lambda, and EBS), not databases or workflow tools.

Topics

#AWS Compute Optimizer#EC2 optimization#Sizing recommendations#Workload metrics

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