AWS Service for Analyzing Historical Utilization and Making Compute Recommendations

AWS Machine Learning-based Tool

Question

Which AWS service is a machine learning-based tool that analyzes metrics of historical utilization and makes recommendations of compute service(s) to be used for the workload?

Answers

Explanations

Click on the arrows to vote for the correct answer

A. B. C. D.

Answer: D.

Option A is INCORRECT because AWS Outpost is a fully managed service that provides a seamless hybrid experience by facilitating the running of AWS services and infrastructure on-premises.

AWS outpost does not provide recommendations for using the compute services after analyzing the past utilization metrics.

Option B is INCORRECT as AWS Well-Architected Tool is a tool that provides advice on architecting the workload in the cloud.

This tool also enables customers to review their architecture against the best practices.

Option C is INCORRECT because AWS Management Console is a web-based user interface that helps users to access and manage all the aspects of all the available AWS services.

This is a management and governance tool.

Option D is CORRECT.

AWS Compute Optimizer is a machine learning-based tool that analyzes metrics of historical utilization and makes recommendations of compute service(s) to be used for the workload.

Reference:

https://aws.amazon.com/outposts/ https://aws.amazon.com/well-architected-tool/ https://aws.amazon.com/console/ https://aws.amazon.com/compute-optimizer/

The correct answer is D. AWS Compute Optimizer.

AWS Compute Optimizer is a machine learning-based service that helps in making informed decisions about which compute services to use for your workload based on historical utilization metrics. Compute Optimizer analyzes the resource utilization data of your workloads such as CPU, memory, and network, to identify the optimal AWS compute resources that best match your workload requirements.

Compute Optimizer provides recommendations for Amazon EC2 instance types, Amazon EC2 Auto Scaling groups, and Amazon ECS task definitions. It considers various factors such as performance, cost optimization, and availability to provide personalized recommendations. You can use these recommendations to optimize the performance and cost of your applications running on AWS.

Compute Optimizer also provides an API that you can use to access the recommendations programmatically, and integrate with your existing systems.

In summary, AWS Compute Optimizer is a machine learning-based tool that analyzes metrics of historical utilization and makes recommendations of compute services to be used for the workload, based on performance, cost optimization, and availability.