AWS Compute Optimizer

Getting started with AWS Compute Optimizer

Before you can use the AWS Compute Optimizer dashboard for the first time, you must first opt in with the account you're currently signed in with. You can also use the Compute Optimizer API, AWS Command Line Interface (AWS CLI), or SDKs to opt in and out.

By allowing Compute Optimizer to evaluate the specifications and utilization metrics of your AWS resources, such as EC2 instances and Auto Scaling groups, you give Compute Optimizer permission to do so.

Controlling access

Create identities (users, groups, or roles) using AWS Identity and Use Management (IAM), and then provide those identities authorization to access the AWS Compute Optimizer console and APIs.

IAM users do not have access to the Compute Optimizer console or APIs by default. IAM policies are used to grant access to a single user, a group of users, or a role.

You can assign individual passwords to IAM users once they've been created. Then, using an account-specific sign-in page, they may log in to your account and view Compute Optimizer information.

Using Service-Linked Roles

AWS Compute Optimizer takes advantage of service-linked roles from AWS Identity and Access Management (IAM). A service-connected role is a special kind of IAM position that is directly related to Compute Optimizer. Compute Optimizer pre-defines service-linked roles, which include all of the permissions required by the service to call other AWS services on your behalf.

Because you don't have to manually provide the appropriate permissions with a service-linked role, it's easier to set up Compute Optimizer. Compute Optimizer determines the permissions of its service-linked roles, and only Compute Optimizer can assume them unless otherwise specified. The trust policy and the permissions policy are defined permissions, and the permissions policy cannot be coupled with any other IAM entity.

AWS managed policies

It's easier to use AWS managed policies to add permissions to users, groups, and roles than it is to develop policies yourself. Creating IAM customer controlled policies that provide your team only the permissions they need takes time and expertise. You may utilize our AWS managed policies to get started quickly. These policies are available in your AWS account and address common usage situations. See AWS managed policies in the IAM User Guide for additional information on AWS managed policies.

AWS managed policies are maintained and updated by AWS services. Permissions in AWS managed policies cannot be changed. To accommodate new features, services occasionally add additional permissions to an AWS managed policy. This type of change has an impact on all identities (users, groups, and roles) associated with the policy. When a new feature is released, or new operations become available, services are most likely to update an AWS managed policy. AWS managed policies do not delete permissions; therefore, policy upgrades will not break your existing permissions.

AWS also provides managed policies for job functions that span several services. The AWS managed policy ReadOnlyAccess, for example, grants read-only access to all AWS services and resources. AWS adds read-only permissions for new activities and resources when a service introduces new functionality.

Amazon S3 bucket policy

You can save your Compute Optimizer recommendations and information to an Amazon Simple Storage Service (Amazon S3) bucket as a comma-separated values (.csv) file and a JavaScript Object Notation (.json) file.

Before you create the export job, you must first build the target S3 bucket for your suggestions export. The S3 bucket is not created by Compute Optimizer. The S3 bucket you choose for your recommendations export files can't be made public, and it can't be set up as a Requester Pays bucket.

As a best practice, create a dedicated S3 bucket for Compute Optimizer export files.

Metrics analyzed 

If you activate the improved infrastructure metrics recommendation preference, AWS Compute Optimizer begins examining the specs (vCPUs, RAM, storage, and so on) and CloudWatch metrics of your running resources from the last 14 days or longer after you opt in. To create recommendations, Compute Optimizer requires at least 30 hours of continuous metrics data from your resource. Compute Optimizer provides its findings on the dashboard page when the analysis is completed, which can take up to 12 hours.

Frequently Asked Questions

What is AWS compute Optimizer?

AWS Compute Optimizer is a service that examines your AWS resources' configuration and utilization information.
 

What is Compute Optimized?

Simply defined, compute optimized means it's better suited for workloads that require more CPU but not as much memory, whereas memory optimized means it's better suitable for workloads that require a lot of memory but not as much CPU (database).
 

What is the fastest AWS instance?

Amazon EC2 M5zn instances at AWS re: Invent 2020, which employ second-generation Intel Xeon Scalable (Cascade Lake) processors with an all-core turbo clock frequency of up to 4.5 GHz, making them the fastest cloud instance available.
 

What is an E2C in AWS?

In the Amazon Web Services (AWS) Cloud, Amazon Elastic Compute Cloud (Amazon EC2) provides scalable computing power. Using Amazon EC2 reduces the requirement for upfront hardware investment, allowing you to develop and deploy apps more quickly.

Conclusion

In this article, we have extensively discussed AWS Compute Optimizer, a service that analyzes the configuration and utilisation metrics of your AWS resources.

We hope that this blog has helped you enhance your knowledge regarding AWS Compute Optimizer. Do upvote our blog to help other ninjas grow.

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