An IT team has built an AWS CloudFormation template so others in the company can quickly and reliably deploy and terminate an application. The template creates an Amazon EC2 instance with a user data script to install the application and an Amazon S3 bucket that the application uses to serve static webpages while it is running.
All resources should be removed when the CloudFormation stack is deleted. However, the team observes that CloudFormation reports an error during stack deletion, and the S3 bucket created by the stack is not deleted.
How can the team resolve the error in the MOST efficient manner to ensure that all resources are deleted without errors?

• A.Add DeletionPolicy attribute to the S3 bucket resource, with the value Delete forcing the bucket to be removed when the stack is deleted.
• B.Identify the resource that was not deleted. From the S3 console, empty the S3 bucket and then delete it.
• C.Replace the EC2 and S3 bucket resources with a single AWS OpsWorks Stacks resource. Define a custom recipe for the stack to create and delete the EC2 instance and the S3 bucket.
• D.Add a custom resource when an AWS Lambda function with the DependsOn attribute specifying the S3 bucket, and an IAM role. Writhe the Lambda function to delete all objects from the bucket when the is Delete.
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Which of the following can be used in Cloudformation to coordinate the creation of stack resources. Choose 2 answers from the options given below

• A.AWS::CloudFormation::HoldCondition
• B.AWS::CloudFormation::WaitCondition
• C.HoldPolicyattribute
• D.CreationPolicyattribute

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You need to perform ad-hoc analysis on log data, including searching quickly for specific error codes and reference numbers. Which should you evaluate first?

• A.AWS Elasticsearch Service
• B.AWS RedShift
• C.AWS EMR
• D.AWS DynamoDB

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An online retail company based in the United States plans to expand its operations to Europe and Asia in the next six months. Its product currently runs on Amazon EC2 instances behind an Application Load Balancer. The instances run in an Amazon EC2 Auto Scaling group across multiple Availability Zones. All data is stored in an Amazon Aurora database instance.
When the product is deployed in multiple regions, the company wants a single product catalog across all regions, but for compliance purposes, its customer information and purchases must be kept in each region. How should the company meet these requirements with the LEAST amount of application changes?

• A.Use Amazon DynamoDB global tables for the product catalog and regional tables for the customer information and purchases
• B.Use Aurora for the product catalog and Amazon DynamoDB global tables for the customer information and purchases.
• C.Use Amazon Redshift for the product catalog and Amazon DynamoDB tables for the customer information and purchases.
• D.Use Aurora with read replicas for the product catalog and additional local Aurora instances in each region for the customer information and purchases.

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You are building a large, multi-tenant SaaS (software-as-a-service) application with a component that fetches data to process from a customer-specific Amazon S3 bucket in their account.
How should you ensure that your application follows security best practices and limits risk when fetching data from customer-owned Amazon S3 buckets?

• A.Have users create an Amazon S3 bucket policy that grants read-only access to the Amazon S3 bucket required by your application, and securely store the corresponding access keys in the database holding their account data.
• B.Have users create an IAM user with a policy that grants read-only access to the Amazon S3 bucket required by your application, and store the corresponding access keys in an encrypted database that holds their account data.
• C.Have users create an Amazon S3 bucket policy that grants read-only access to the Amazon S3 bucket required by your application and limits access to the public IP address of the SaaS application.
• D.Have users create a cross-account lAM role with a policy that grants read-only access to the Amazon S3 bucket required by your application to the AWS account ID running your production Sass application.

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