Free Amazon Web Services SAP-C02 Practice Exam with Questions & Answers | Set: 7

Use an SCP to deny the creation of resources that do not have the required tags. Create a tag policy that Includes the tag values that the company has assigned to each OU. Attach the tag policies to the OUs.

Use an SCP to deny the creation of resources that do not have the required tags. Create a tag policy that includes the tag values that the company has assigned to each OU. Attach the tag policies to the organization ' s management account.

Use an SCP to allow the creation of resources only when the resources have the required tags. Create a tag policy that includes the tag values that the company has assigned to each OU. Attach the tag policies to the OUs.

Use an SCP to deny the creation of resources that do not have the required tags. Define the list of tags. Attach the SCP to the OUs

Create an Amazon EventBridge (Amazon CloudWatch Events) rule. Define a pattern with the detail-type value set to AWS API Call via CloudTrail and an eventName of CreateUser.

Configure CloudTrail to send a notification for the CreateUser event to an Amazon Simple Notification Service (Amazon SNS) topic.

Invoke a container that runs in Amazon Elastic Container Service (Amazon ECS) with AWS Fargate technology to remove access

Invoke an AWS Step Functions state machine to remove access.

Use Amazon Simple Notification Service (Amazon SNS) to notify the security team.

Use Amazon Pinpoint to notify the security team.

Store the database credentials in AWS Systems Manager Parameter Store by using a SecureString parameter that is encrypted by an AWS Key Management Service (AWS KMS) customer managed key. Attach a role to each Lambda function to provide access to the SecureString parameter. Restrict access to the Securestring parameter and the customer managed key so that only the IT security team can access the parameter and the key.

Encrypt the database credentials by using the AWS Key Management Service (AWS KMS) default Lambda key. Store the credentials in the environment variables of each Lambda function. Load the credentials from the environment variables in the Lambda code. Restrict access to the KMS key o that only the IT security team can access the key.

Store the database credentials in the environment variables of each Lambda function.Encrypt the environment variables by using an AWS Key Management Service (AWS KMS) customer managed key. Restrict access to the customer managed key so that only the IT security team can access the key.

Store the database credentials in AWS Secrets Manager as a secret that is associated with an AWS Key Management Service (AWS KMS) customermanaged key. Attach a role to each Lambda function to provide access to the secret. Restrict access to the secret and the customer managed key so that only the IT security team can access the secret and the key.

For the API Gateway method, set the authorization to AWS_IAM. Then, give the IAM user or role execute-api:Invoke permission on the REST API resource. Enable the API caller to sign requests with AWS Signature when accessing the endpoint. Use AWS X-Ray to trace and analyze user requests to API Gateway.

For the API Gateway resource, set CORS to enabled and only return the company ' s domain in Access-Control-Allow-Origin headers. Then, give the IAM user or role execute-api:Invoke permission on the REST API resource. Use Amazon CloudWatch to trace and analyze user requests to API Gateway.

Create an AWS Lambda function as the custom authorizer, ask the API client to pass the key and secret when making the call, and then use Lambda to validate the key/secret pair against the IAM system. Use AWS X-Ray to trace and analyze user requests to API Gateway.

Create a client certificate for API Gateway. Distribute the certificate to the AWS users and roles that need to access the endpoint. Enable the API caller to pass the client certificate when accessing the endpoint. Use Amazon CloudWatch to trace and analyze user requests to API Gateway.

Create and deploy nested AWS CloudFormation stacks with the parent stack consisting of the AWS CloudFront distribution and API Gateway, and the child stack containing the Lambda function. For changes to Lambda, create an AWS CloudFormation change set and deploy; if errors are triggered, revert the AWS CloudFormation change set to the previous version.

Use AWS SAM and built-in AWS CodeDeploy to deploy the new Lambda version, gradually shift traffic to the new version, and use pre-traffic and post-traffic test functions to verify code. Rollback if Amazon CloudWatch alarms are triggered.

Refactor the AWS CLI scripts into a single script that deploys the new Lambda version. When deployment is completed, the script tests execute. If errors are detected, revert to the previous Lambda version.

Create and deploy an AWS CloudFormation stack that consists of a new API Gateway endpoint that references the new Lambda version. Change the CloudFront origin to the new API Gateway endpoint, monitor errors and if detected, change the AWS CloudFront origin to the previous API Gateway endpoint.

Use Amazon EFS and a cron job to perform the transformations. Notify using SNS.

Use Amazon EMR to perform the transformations and notify via SNS.

Use Amazon S3 as storage with AWS Glue triggered by S3 events for transformations, and notify via SQS.

Use Amazon EFS with a time-based AWS Glue job every 5 minutes.

Create an Amazon Aurora MySQL Serverless v1 DB instance. Migrate the RDS DB instance to the Aurora Serverless v1 DB instance. Update the connection settings in the application to point to the Aurora reader endpoint.

Create an RDS proxy. Configure the existing RDS endpoint as a target. Update the connection settings in the application to point to the RDS proxy endpoint.

Create a two-node Amazon Aurora MySQL DB cluster. Migrate the RDS DB instance to the Aurora DB cluster. Create an RDS proxy. Configure the existing RDS endpoint as a target. Update the connection settings in the application to point to the RDS proxy endpoint.

Create an Amazon S3 bucket. Export the database to Amazon S3 by using AWS Database Migration Service (AWS DMS). Configure Amazon Athena to use the S3 bucket as a data store. Install the latest Open Database Connectivity (ODBC) driver for the application. Update the connection settings in the application to point to the Athena endpoint

Configure the S3 bucket to be a Requester Pays bucket.

Use S3 Transfer Acceleration to upload the videos to the S3 bucket.

Create an S3 Lifecycle configuration to expire incomplete multipart uploads 7 days after initiation.

Create an S3 Lifecycle configuration to transition objects to S3 Glacier Instant Retrieval after 1 day.

Create an S3 Lifecycle configuration to transition objects to S3 Standard-Infrequent Access (S3 Standard-IA) after 180 days.

Turn on Amazon ECR basic scanning. Enable scan on push for all repositories. Configure Amazon EventBridge rules to capture scan completion events and route the findings to AWS Security Hub CSPM. Use ECR lifecycle policies to automatically delete images that have critical vulnerabilities.

Create AWS Lambda functions that are invoked by ECR image push events. Configure the Lambda functions to pull images and scan the images by using open-source tools. Store the scan results in Amazon DynamoDB. Create Amazon CloudWatch dashboards to visualize vulnerability trends across repositories.

Turn on Amazon ECR basic scanning and enhanced scanning. Configure manual scan triggers for basic scanning and enhanced scanning. Use AWS Systems Manager Parameter Store to maintain a list of approved base images. Create AWS Config rules to check that only approved images are deployed to production environments and automatically remediate non-compliant resources.

Turn on Amazon ECR enhanced scanning. Integrate enhanced scanning with Amazon Inspector. Configure continuous scanning for repositories. Use Amazon Inspector to track the deployment status of container images. Configure Amazon EventBridge rules to capture Amazon Inspector findings and route the findings to the company’s existing event-driven workflow.

Configure automated backups on Amazon RDS. In the case of disruption, promote an automated backup to be a standalone DB instance. Direct database traffic to the promoted DB instance. Create a replacement read replica that has the promoted DB instance as its source.

Configure global tables and read replicas on Amazon RDS. Activate the cross-Region scope. In the case of disruption, use AWS Lambda to copy the read replicas from one Region to another Region.

Configure global tables and automated backups on Amazon RDS. In the case of disruption, use AWS Lambda to copy the read replicas from one Region to another Region.

Configure read replicas on Amazon RDS. In the case of disruption, promote a cross-Region and read replica to be a standalone DB instance. Direct database traffic to the promoted DB instance. Create a replacement read replica that has the promoted DB instance as its source.

Upload the container images to AWS Lambda as functions. Configure a concurrency limit for the associated Lambda functions to handle the expected peak load. Configure two separate Lambda integrations within Amazon API Gateway: one for production and one for testing.

Upload the container images to Amazon Elastic Container Registry (Amazon ECR). Configure two auto scaled Amazon Elastic Container Service (Amazon ECS) clusters with the Fargate launch type to handle the expected load. Deploy tasks from the ECR images. Configure two separate Application Load Balancers to direct traffic to the ECS clusters.

Upload the container images to Amazon Elastic Container Registry (Amazon ECR). Configure two auto scaled Amazon Elastic Kubernetes Service (Amazon EKS) clusters with the Fargate launch type to handle the expected load. Deploy tasks from the ECR images. Configure two separate Application Load Balancers to direct traffic to the EKS clusters.

Upload the container images to AWS Elastic Beanstalk. In Elastic Beanstalk, create separate environments and deployments for production and testing. Configure two separate Application Load Balancers to direct traffic to the Elastic Beanstalk deployments.

Create an AWS CodeCommit repository for each package that the data scientists need to access. Configure code synchronization between the PyPl repositoryand the CodeCommit repository. Create a VPC endpoint for CodeCommit.

Create a NAT gateway in the VPC. Configure VPC routes to allow access to the internet with a network ACL that allows access to only the PyPl repositoryendpoint.

Create a NAT instance in the VPC. Configure VPC routes to allow access to the internet. Configure SageMaker notebook instance firewall rules that allow access to only the PyPI repository endpoint.

Create an AWS CodeArtifact domain and repository. Add an external connection for public:pypi to the CodeArtifact repository. Configure the Python client touse the CodeArtifact repository. Create a VPC endpoint for CodeArtifact.

Create a weekly cron job in Amazon EventBridge. Use the cron job to invoke an AWS Lambda function to update the EC2 instances from the NAS server.

Configure an Amazon Elastic Block Store (Amazon EBS) Multi-Attach volume for the EC2 instances to share for content access. Write code to synchronize the EBS volume with the NAS server weekly.

Mount an Amazon Elastic File System (Amazon EFS) file system to the on-premises servers to act as the NAS server. Copy the blog data to the EFS file system. Mount the EFS file system to the EC2 instances to serve the content.

Order an AWS Snowball Edge Storage Optimized device. Copy the static data artifacts to the device. Ship the device to AWS.

Order an AWS Snowcone SSD device. Copy the static data artifacts to the device. Ship the device to AWS.

Implement the REST API using a Network Load Balancer (NLB). Run the business logic on an Amazon EC2 instance behind the NLB. Store player session data in Amazon Aurora Serverless.

Implement the REST API using an Application Load Balancer (ALB). Run the business logic in AWS Lambda. Store player session data in Amazon DynamoDB with on-demand capacity.

Implement the REST API using Amazon API Gateway. Run the business logic in AWS Lambda. Store player session data in Amazon DynamoDB with on- demand capacity.

Implement the REST API using AWS AppSync. Run the business logic in AWS Lambda. Store player session data in Amazon Aurora Serverless.

Create a new Elastic Beanstalk application. Select a load-balanced environment type. Select all Availability Zones. Add a scale-out rule that will run if the maximum CPU utilization is over 85% for 5 minutes.

Create a second Elastic Beanstalk environment. Apply the traffic-splitting deployment policy. Specify a percentage of incoming traffic to direct to the new environment in the average CPU utilization is over 85% for 5 minutes.

Modify the existing environment ' s capacity configuration to use a load-balanced environment type. Select all Availability Zones. Add a scale-out rule that will run if the average CPU utilization is over 85% for 5 minutes.

Select the Rebuild environment action with the load balancing option Select an Availability Zones Add a scale-out rule that will run if the sum CPU utilization is over 85% for 5 minutes.