A. Use AWS CodePipeline to create a pipeline. Add an action to the pipeline to invoke an AWS Lambda function after the source stage. Have the Lambda function invoke the source-code analysis tool on premises against the source input from CodePipeline. The function then waits for the execution to complete and places the output in a specified Amazon S3 location.

B. Use AWS CodePipeline to create a pipeline, then create a custom action type. Create a job worker for the on-premises server that polls CodePipeline for job requests, initiates the tests, and returns the results. Configure the pipeline to invoke the custom action after the source stage.

C. Use AWS CodePipeline to create a pipeline. Add a step after the source stage to make an HTTPS request to the on-premises hosted web service that invokes a test with the source code analysis tool. When the analysis is complete, the web service sends the results back by putting the results in an Amazon S3 output location provided by CodePipeline.

D. Use AWS CodePipeline to create a pipeline. Create a shell script that copies the input source code to a location on premises. Invoke the source code analysis tool and return the results to CodePipeline. Invoke the shell script by adding a custom script action after the source stage.

A. Tag the Amazon EC2 instances depending on the deployment group. Then place a script into the application revision that calls the metadata service and the EC2 API to identify which deployment group the instance is part of. Use this information to configure the log level settings. Reference the script as part of the Afterinstall lifecycle hook in the appspec.yml file.

B. Create a script that uses the CodeDeploy environment variable DEPLOYMENT_GROUP_NAME to identify which deployment group the instances is part of. Use this information to configure the log level settings. Reference this script as part of the BeforeInstall lifecycle hook in the appspec.yml file

C. Create a CodeDeploy custom environment variable for each environment. Then place a script into the application revision that checks this environment variable to identify which deployment group the instance is part of. Use this information to configure the log level settings. Reference this script as part of the ValidateService lifecycle hook in the appspec.yml file.

D. Create a script that uses the CodeDeploy environment variable DEPLOYMENT_GROUP_ID to identify which deployment group the instance is part of to configure the log level settings. Reference this script as part of the Install lifecycle hook in the appspec.yml file.

A. Create a custom AMI with the Node.js environment and application stack using Chef recipes. Use the AMI in an Auto Scaling group and set up scheduled scaling for the required times, then set up an Amazon EC2 IAM role that provides permission to access DynamoDB.

B. Create a Docker file that uses the Chef recipes for the application environment based on an official Node.js Docker image. Create an Amazon ECS cluster and a service for the application environment, then create a task based on this Docker image. Use scheduled scaling to scale the containers at the appropriate times and attach a task-level IAM role that provides permission to access DynamoDB.

C. Configure AWS OpsWorks stacks and use custom Chef cookbooks. Add the Git repository information where the custom recipes are stored, and add a layer in OpsWorks for the Node.js application server. Then configure the custom recipe to deploy the application in the deploy step. Configure time-based instances and attach an Amazon EC2 IAM role that provides permission to access DynamoDB.

D. Configure AWS OpsWorks stacks and push the custom recipes to an Amazon S3 bucket and configure custom recipes to point to the S3 bucket. Then add an application layer type for a standard Node.js application server and configure the custom recipe to deploy the application in the deploy step from the S3 bucket. Configure time-based instances and attach an Amazon EC2 IAM role that provides permission to access DynamoDB.

A. Create an AWS Lambda function to delete the IAM access key. Send AWS CloudTrail logs to AWS CloudWatch logs. Create a CloudWatch Logs metric filter for the AWS_RISK_CREDENTIALS_EXPOSED event with two actions: first, run the Lambda function; second, use Amazon SNS to send a notification to the Security team.

B. Create an AWS Lambda function to delete the IAM access key. Create an AWS Config rule for changes to aws.health and the AWS_RISK_CREDENTIALS_EXPOSED event with two actions: first, run the Lambda function; second, use Amazon SNS to send a notification to the Security team.

C. Use AWS Step Functions to create a function to delete the IAM access key, and then use Amazon SNS to send a notification to the Security team. Create an AWS Personal Health Dashboard rule for the AWS_RISK_CREDENTIALS_EXPOSED event; set the target of the Personal Health Dashboard rule to Step Functions.

D. Use AWS Step Functions to create a function to delete the IAM access key, and then use Amazon SNS to send a notification to the Security team. Create an Amazon CloudWatch Events rule with an aws.health event source and the AWS_RISK_CREDENTIALS_EXPOSED event; set the target of the CloudWatch Events rule to Step Functions.

A. Create an Amazon CloudWatch Events rule for the CloudTrail StopLogging event. Create an AWS Lambda function that uses the AWS SDK to call StartLogging on the ARN of the resource in which StopLogging was called. Add the Lambda function ARN as a target to the CloudWatch Events rule.

B. Deploy the AWS-managed CloudTrail-enabled AWS Config rule, set with a periodic interval of 1 hour. Create an Amazon CloudWatch Events rule for AWS Config rules compliance change. Create an AWS Lambda function that uses the AWS SDK to call StartLogging on the ARN of the resource in which StopLogging was called. Add the Lambda function ARN as a target to the CloudWatch Events rule.

C. Create an Amazon CloudWatch Events rule for a scheduled event every 5 minutes. Create an AWS Lambda function that uses the AWS SDK to call StartLogging on a CloudTrail trail in the AWS account. Add the Lambda function ARN as a target to the CloudWatch Events rule.

D. Launch a t2.nano instance with a script running every 5 minutes that uses the AWS SDK to query CloudTrail in the current account. If the CloudTrail trail is disabled, have the script re-enable the trail.

A. Create an Amazon CloudWatch Events rule that triggers an AWS Lambda function when a new file is delivered. Configure the Lambda function to perform an MD5 hash check on the file, store the name and location of the file, and post the returned hash to an Amazon DynamoDB table. The Security team can use the values stored in DynamoDB to verify the file authenticity.

B. Enable the CloudTrail file integrity feature on an Amazon S3 bucket. Create an IAM policy that grants the Security team access to the file integrity logs stored in the S3 bucket.

C. Enable the CloudTrail file integrity feature on the trail. Use the digest file created by CloudTrail to verify the integrity of the delivered CloudTrail files.

D. Create an AWS Lambda function that is triggered each time a new file is delivered to the CloudTrail bucket. Configure the Lambda function to execute an MD5 hash check on the file, and store the result on a tag in an Amazon S3 object. The Security team can use the information on the tag to verify the integrity of the file.

A. Configure a new AWS CodePipeline service. Create a CodeCommit repository for each environment. Set up CodePipeline to retrieve the source code from the appropriate repository. Set up the deployment step to deploy the Lambda functions with AWS CloudFormation.

B. Create two AWS CodePipeline configurations for test and production environments. Configure the production pipeline to have a manual approval step. Create a CodeCommit repository for each environment. Set up each CodePipeline to retrieve the source code from the appropriate repository. Set up the deployment step to deploy the Lambda functions with AWS CloudFormation.

C. Create two AWS CodePipeline configurations for test and production environments. Configure the production pipeline to have a manual approval step. Create one CodeCommit repository with a branch for each environment. Set up each CodePipeline to retrieve the source code from the appropriate branch in the repository. Set up the deployment step to deploy the Lambda functions with AWS CloudFormation.

D. Create an AWS CodeBuild configuration for test and production environments. Configure the production pipeline to have a manual approval step. Create one CodeCommit repository with a branch for each environment. Push the Lambda function code to an Amazon S3 bucket. Set up the deployment step to deploy the Lambda functions from the S3 bucket.

A. Add a manual approval action after the last deploy action of the pipeline. Use Amazon SNS to inform the team of the stage being triggered. Next, add a test action using CodeBuild to do the required tests. At the end of the pipeline, add a deploy action to deploy the application to the next stage.

B. Add a test action after the last deploy action of the pipeline. Configure the action to use CodeBuild to perform the required tests. If these tests are successful, mark the action as successful. Add a manual approval action that uses Amazon SNS to notify the team, and add a deploy action to deploy the application to the next stage.

C. Create a new pipeline that uses a source action that gets the code from the same repository as the first pipeline. Add a deploy action to deploy the code to a test environment. Use a test action using AWS Lambda to test the deployment. Add a manual approval action by using Amazon SNS to notify the team, and add a deploy action to deploy the application to the next stage.

D. Add a test action after the last deployment action. Use a Jenkins server on Amazon EC2 to do the required tests and mark the action as successful if the tests pass. Create a manual approval action that uses Amazon SQS to notify the team and add a deploy action to deploy the application to the next stage.

A. Create primary and secondary Amazon S3 buckets in two separate Availability Zones that are at least 500 miles apart. Use a bucket policy to enforce access to the buckets only through HTTPS. Use a bucket policy to enforce Amazon S3 SSE-C on all objects uploaded to the bucket. Configure cross-region replication between the two buckets.

B. Create primary and secondary Amazon S3 buckets in two separate AWS Regions that are at least 500 miles apart. Use a bucket policy to enforce access to the buckets only through HTTPS. Use a bucket policy to enforce S3-Managed Keys (SSE-S3) on all objects uploaded to the bucket. Configure cross-region replication between the two buckets.

C. Create primary and secondary Amazon S3 buckets in two separate AWS Regions that are at least 500 miles apart. Use an IAM role to enforce access to the buckets only through HTTPS. Use a bucket policy to enforce Amazon S3-Managed Keys (SSE-S3) on all objects uploaded to the bucket. Configure cross- region replication between the two buckets.

D. Create primary and secondary Amazon S3 buckets in two separate Availability Zones that are at least 500 miles apart. Use a bucket policy to enforce access to the buckets only through HTTPS. Use a bucket policy to enforce AWS KMS encryption on all objects uploaded to the bucket. Configure cross-region replication between the two buckets. Create a KMS Customer Master Key (CMK) in the primary region for encrypting objects.

A. Use an Application Load Balancer and an in-place deployment. Associate the Auto Scaling group with the deployment group. Use the Automatically copy Auto Scaling group option, and use CodeDeployDefault.OneAtAtime as the deployment configuration. Instruct AWS CodeDeploy to terminate the original instances in the deployment group, and use the AllowTraffic hook within appspec.yml to delete the temporary files.

B. Use an Application Load Balancer and a blue/green deployment. Associate the Auto Scaling group and the Application Load Balancer target group with the deployment group. Use the Automatically copy Auto Scaling group option, create a custom deployment configuration with minimum healthy hosts defined as 50%, and assign the configuration to the deployment group. Instruct AWS CodeDeploy to terminate the original instances in the deployment group, and use the BeforeBlockTraffic hook within appspec.yml to delete the temporary files.

C. Use an Application Load Balancer and a blue/green deployment. Associate the Auto Scaling group and the Application Load Balancer target group with the deployment group. Use the Automatically copy Auto Scaling group option, and use CodeDeployDefault.HalfAtAtime as the deployment configuration. Instruct AWS CodeDeploy to terminate the original instances in the deployment group, and use the BeforeAllowTraffic hook within appspec.yml to delete the temporary files.

D. Use an Application Load Balancer and an in-place deployment. Associate the Auto Scaling group and Application Load Balancer target group with the deployment group. Use the Automatically copy Auto Scaling group option, and use CodeDeployDefault.AllatOnce as a deployment configuration. Instruct AWS CodeDeploy to terminate the original instances in the deployment group, and use the BlockTraffic hook within appspec.yml to delete the temporary files.