Free SAP-C02 Amazon Web Services Updates

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Question 84

A company uses AWS Organizations with a single OU named Production to manage multiple accounts All accounts are members of the Production OU Administrators use deny list SCPs in the root of the organization to manage access to restricted services.

The company recently acquired a new business unit and invited the new unit's existing AWS account to the organization Once onboarded the administrators of the new business unit discovered that they are not able to update existing AWS Config rules to meet the company's policies.

Which option will allow administrators to make changes and continue to enforce the current policies without introducing additional long-term maintenance?

Options:

Remove the organization's root SCPs that limit access to AWS Config Create AWS Service Catalog products for the company's standard AWS Config rules and deploy them throughout the organization, including the new account.

Create a temporary OU named Onboarding for the new account Apply an SCP to the Onboarding OU to allow AWS Config actions Move the new account to the Production OU when adjustments to AWS Config are complete

Convert the organization's root SCPs from deny list SCPs to allow list SCPs to allow the required services only Temporarily apply an SCP to the organization's root that allows AWS Config actions for principals only in the new account.

Create a temporary OU named Onboarding for the new account Apply an SCP to the Onboarding OU to allow AWS Config actions. Move the organization's root SCP to the Production OU. Move the new account to the Production OU when adjustments to AWS Config are complete.

Question 85

A financial services company loaded millions of historical stock trades into an Amazon DynamoDB table. The table uses on-demand capacity mode. Once each day at midnight, a few million new records are loaded into the table. Application read activity against the table happens in bursts throughout the day. and a limited set of keys are repeatedly looked up. The company needs to reduce costs associated with DynamoDB.

Which strategy should a solutions architect recommend to meet this requirement?

Options:

Deploy an Amazon ElastiCache cluster in front of the DynamoDB table.

Deploy DynamoDB Accelerator (DAX). Configure DynamoDB auto scaling. Purchase Savings Plans in Cost Explorer

Use provisioned capacity mode. Purchase Savings Plans in Cost Explorer.

Deploy DynamoDB Accelerator (DAX). Use provisioned capacity mode. Configure DynamoDB auto scaling.

Question 86

A solutions architect is redesigning a three-tier application that a company hosts on premises. The application provides personalized recommendations based on user profiles. The company already has an AWS account and has configured a VPC to host the application.

The frontend is a Java-based application that runs in on-premises VMs. The company hosts a personalization model on a physical application server and uses TensorFlow to implement the model. The personalization model uses artificial intelligence and machine learning (AI/ML). The company stores user information in a Microsoft SQL Server database. The web application calls the personalization model, which reads the user profiles from the database and provides recommendations.

The company wants to migrate the redesigned application to AWS.

Which solution will meet this requirement with the LEAST operational overhead?

Options:

Use AWS Server Migration Service (AWS SMS) to migrate the on-premises physical application server and the web application VMs to AWS. Use AWS Database Migration Service (AWS DMS) to migrate the SQL Server database to Amazon RDS for SQL Server.

Export the personalization model. Store the model artifacts in Amazon S3. Deploy the model to Amazon SageMaker and create an endpoint. Host the Java application in AWS Elastic Beanstalk. Use AWS Database Migration Service {AWS DMS) to migrate the SQL Server database to Amazon RDS for SQL Server.

Use AWS Application Migration Service to migrate the on-premises personalization model and VMs to Amazon EC2 instances in Auto Scaling groups. Use AWS Database Migration Service (AWS DMS) to migrate the SQL Server database to an EC2 instance.

Containerize the personalization model and the Java application. Use Amazon Elastic Kubernetes Service (Amazon EKS) managed node groups to deploy the model and the application to Amazon EKS Host the node groups in a VPC. Use AWS Database Migration Service (AWS DMS) to migrate the SQL Server database to Amazon RDS for SQL Server.

Answer:

Explanation:

Amazon SageMaker is a fully managed machine learning service that allows users to build, train, and deploy machine learning models quickly and easily1. Users can export their existing TensorFlow models and store the model artifacts in Amazon S3, a highly scalable and durable object storage service2. Users can then deploy the model to Amazon SageMaker and create an endpoint that can be invoked by the web application to provide recommendations3. This way, the solution can leverage the AI/ML capabilities of Amazon SageMaker without having to rewrite the personalization model.

AWS Elastic Beanstalk is a service that allows users to deploy and manage web applications without worrying about the infrastructure that runs those applications. Users can host their Java application in AWS Elastic Beanstalk and configure it to communicate with the Amazon SageMaker endpoint. This way, the solution can reduce the operational overhead of managing servers, load balancers, scaling, and application health monitoring.

AWS Database Migration Service (AWS DMS) is a service that helps users migrate databases to AWS quickly and securely. Users can use AWS DMS to migrate their SQL Server database to Amazon RDS for SQL Server, a fully managed relational database service that offers high availability, scalability, security, and compatibility. This way, the solution can reduce the operational overhead of managing database servers, backups, patches, and upgrades.

Option A is incorrect because using AWS Server Migration Service (AWS SMS) to migrate the on-premises physical application server and the web application VMs to AWS is not cost-effective or scalable. AWS SMS is a service that helps users migrate on-premises workloads to AWS. However, for this use case, migrating the physical application server and the web application VMs to AWS will not take advantage of the AI/ML capabilities of Amazon SageMaker or the managed services of AWS Elastic Beanstalk and Amazon RDS.

Option C is incorrect because using AWS Application Migration Service to migrate the on-premises personalization model and VMs to Amazon EC2 instances in Auto Scaling groups is not cost-effective or scalable. AWS Application Migration Service is a service that helps users migrate applications from on-premises or other clouds to AWS without making any changes to their applications. However, for this use case, migrating the personalization model and VMs to EC2 instances will not take advantage of the AI/ML capabilities of Amazon SageMaker or the managed services of AWS Elastic Beanstalk and Amazon RDS.

Option D is incorrect because containerizing the personalization model and the Java application and using Amazon Elastic Kubernetes Service (Amazon EKS) managed node groups to deploy them to Amazon EKS is not necessary or cost-effective. Amazon EKS is a service that allows users to run Kubernetes on AWS without needing to install, operate, and maintain their own Kubernetes control plane or nodes. However, for this use case, containerizing and deploying the personalization model and the Java application will not take advantage of the AI/ML capabilities of Amazon SageMaker or the managed services of AWS Elastic Beanstalk. Moreover, using S3 Glacier Deep Archive as a storage class for images will incur a high retrieval fee and latency for accessing them.

Question 87

A company built an application based on AWS Lambda deployed in an AWS CloudFormation stack. The last production release of the web application introduced an issue that resulted in an outage lasting several minutes. A solutions architect must adjust the deployment process to support a canary release.

Which solution will meet these requirements?

Options:

Create an alias for every new deployed version of the Lambda function. Use the AWS CLI update-alias command with the routing-config parameter to distribute the load.

Deploy the application into a new CloudFormation stack. Use an Amazon Route 53 weighted routing policy to distribute the load.

Create a version for every new deployed Lambda function. Use the AWS CLI update-function-contiguration command with the routing-config parameter to distribute the load.

Configure AWS CodeDeploy and use CodeDeployDefault.OneAtATime in the Deployment configuration to distribute the load.