A company had a tight deadline to migrate its on-premises environment to AWS. It moved over Microsoft SQL Servers and Microsoft Windows Servers using the virtual machine import/export service and rebuild other applications native to the cloud. The team created both Amazon EC2 databases and used Amazon RDS.
Each team in the company was responsible for migrating their applications, and they have created individual accounts for isolation of resources. The company did not have much time to consider costs, but now it would like suggestions on reducing its AWS spend.
Which steps should a Solutions Architect take to reduce costs?

• A.Enable AWS Business Support and review AWS Trusted Advisor's cost checks. Create Amazon EC2 Auto Scaling groups for applications that experience fluctuating demand. Save AWS Simple Monthly Calculator reports in Amazon S3 for trend analysis. Create a master account under Organizations and have teams join for consolidating billing.
• B.Create an AWS Lambda function that changes the instance size based on Amazon CloudWatch alarms.
  Reserve instances based on AWS Simple Monthly Calculator suggestions. Have an AWS Well-Architected framework review and apply recommendations. Create a master account under Organizations and have teams join for consolidated billing.
• C.Create a budget and monitor for costs exceeding the budget. Create Amazon EC2 Auto Scaling groups for applications that experience fluctuating demand. Create an AWS Lambda function that changes instance sizes based on Amazon CloudWatch alarms. Have each team upload their bill to an Amazon S3 bucket for analysis of team spending. Use Spot instances on nightly batch processing jobs.
• D.Enable Cost Explorer and AWS Business Support Reserve Amazon EC2 and Amazon RDS DB instances. Use Amazon CloudWatch and AWS Trusted Advisor for monitoring and to receive cost-savings suggestions. Create a master account under Organizations and have teams join for consolidated billing.

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A company used Amazon EC2 instances to deploy a web fleet to host a blog site. The EC2 instances are behind an Application Load Balancer (ALB) and are configured in an Auto Scaling group. The web application stores all blog content on an Amazon EFS volume.
The company recently added a feature for bloggers to add video to their posts, attracting 10 times the previous user traffic. At peak times of day, users report buffering and timeout issues while attempting to reach the site or watch videos.
Which is the MOST cost-efficient and scalable deployment that will resolve the issues for users?

• A.Reconfigure Amazon EFS to enable maximum I/O.
• B.Update the blog site to use instance store volumes for storage. Copy the site contents to the volumes at launch and to Amazon S3 at shutdown.
• C.Configure an Amazon CloudFront distribution. Point the distribution to an S3 bucket, and migrate the videos from EFS to Amazon S3.
• D.Set up an Amazon CloudFront distribution for all suite contents, and point the distribution at the ALB.

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A company uses a load balancer to distribute traffic to Amazon EC2 instances in a single Availability Zone The company is concerned about security and wants a solutions architect to re-architect the solution to meet the following requirements:
* Inbound requests must be filtered for common vulnerability attacks
* Rejected requests must be sent to a third-party auditing application
* All resources should be highly available
Which solution meets these requirements?

• A.Configure an Application Load Balancer (ALB) and add the EC2 instances as targets Create a web ACL in WAF Create an AWS WAF using the web ACL and ALB name and enable logging with Amazon CloudWatch Logs Use an AWS Lambda function to frequently push the logs to the third-party auditing application
• B.Configure a Multi-AZ Auto Scaling group using the application's AMI Create an Application Load Balancer (ALB) and select the previously created Auto Scaling group as the target Create an Amazon Kinesis Data Firehose with a destination of the third-party auditing application Create a web ACL in WAF Create an AWS WAF using the WebACL and ALB then enable logging by selecting the Kinesis Data Firehose as the destination Subscribe to AWS Managed Rules in AWS Marketplace, choosing the WAF as the subscriber.
• C.Configure an Application Load Balancer (ALB) along with a target group adding the EC2 instances as targets Create an Amazon Kinesis Data Firehose with the destination of the third-party auditing application Create a web ACL in WAF Create an AWS WAF using the web ACL and ALB then enable logging by selecting the Kinesis Data Firehose as the destination Subscribe to AWS Managed Rules in AWS Marketplace, choosing the WAF as the subscriber.
• D.Configure a Multi-AZ Auto Scaling group using the application's AMI. Create an Application Load Balancer (ALB) and select the previously created Auto Scaling group as the target Use Amazon Inspector to monitor traffic to the ALB and EC2 instances Create a web ACL in WAF Create an AWS WAF using the web ACL and ALB Use an AWS Lambda function to frequently push the Amazon Inspector report to the third-party auditing application

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A company recently transformed its legacy infrastructure provisioning scripts to AWS CloudFormation templates. The newly developed templates are hosted in the company's private GitHub repository. Since adopting CloudFortmation, the company has encountered several issues with updates to the CloudFormation templates, causing execution or creating environment Management is concerned by the increase in errors and has asked a Solutions architect to design the automated testing of CloudFortmation template updates.
What should the Solution Architecture do to meet these requirements?

• A.Use AWS CodePipeline to create and execute a change set from the CloudFormation templates stores in the GitHub repository. Configure a CodePipeline action to be deployment with testing scripts run by AWS CodeBuild.
• B.Mirror the GitHub repository to AWS CodeCommit using AWS Lambda. Use AWS CodeDeploy to create a change set from the CloudFormation templates and execute it. Have CodeDeploy test the deployment with testing scripts run by AWS CodeBuild.
• C.Mirror the GitHub repository to AWS CodeCommit using AWS Lambda. Use AWS CodeBuild to create a change set from the CloudFormation templates and executes it, Have CodeBuild test the deployment with testing scripts
• D.Use AWS CodePipeline too create a change set from the CloudFormation templates stored in the private GitHub repository Execute the change set using AWS CodeDeploy Include a CodePipeline action to test the deployment with testing scripts run by AWS CodeBuild

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A company is running a data-intensive application on AWS. The application runs on a cluster of hundreds of Amazon EC2 instances. A shared file system also runs on several EC2 instances that store 200 TB of data. The application reads and modifies the data on the shared file system and generates a report. The job runs once monthly, reads a subset of the files from the shared file system, and takes about 72 hours to complete. The compute instances scale in an Auto Scaling group, but the instances that host the shared file system run continuously. The compute and storage instances are all in the same AWS Region.
A solutions architect needs to reduce costs by replacing the shared file system instances. The file system must provide high performance access to the needed data for the duration of the 72-hour run.
Which solution will provide the LARGEST overall cost reduction while meeting these requirements?

• A.Migrate the data from the existing shared file system to an Amazon S3 bucket that uses the S3 Intelligent-Tiering storage class. Before the job runs each month, use Amazon FSx for Lustre to create a new file system with the data from Amazon S3 by using lazy loading. Use the new file system as the shared storage for the duration of the job. Delete the file system when the job is complete.
• B.Migrate the data from the existing shared file system to an Amazon S3 bucket. Before the job runs each month, use AWS Storage Gateway to create a file gateway with the data from Amazon S3. Use the file gateway as the shared storage for the job. Delete the file gateway when the job is complete.
• C.Migrate the data from the existing shared file system to an Amazon S3 bucket that uses the S3 Standard storage class. Before the job runs each month, use Amazon FSx for Lustre to create a new file system with the data from Amazon S3 by using batch loading. Use the new file system as the shared storage for the duration of the job. Delete the file system when the job is complete.
• D.Migrate the data from the existing shared file system to a large Amazon Elastic Block Store (Amazon EBS) volume with Multi-Attach enabled. Attach the EBS volume to each of the instances by using a user data script in the Auto Scaling group launch template. Use the EBS volume as the shared storage for the duration of the job. Detach the EBS volume when the job is complete.

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