A company runs a database on a single Amazon EC2 instance in a development environment.
The data is stored on separate Amazon EBS volumes that are attached to the EC2 instance. An Amazon Route 53 A record has been created and configured to point to the EC2 instance. The company would like to automate the recovery of the database instance when an instance or Availability Zone (AZ) fails. The company also wants to keep its costs low. The RTO is 4 hours and RPO is 12 hours. Which solution should a DevOps Engineer implement to meet these requirements?

• A.Run the database in an Auto Scaling group with a minimum and maximum instance count of 1 in multiple AZs. Add a lifecycle hook to the Auto Scaling group and define an Amazon CloudWatch Events rule that is triggered when a lifecycle event occurs. Have the CloudWatch Events rule invoke an AWS Lambda function to detach or attach the Amazon EBS data volumes from the EC2 instance based on the event. Configure the EC2 instance UserData to mount the data volumes (retry on failure with a short delay), then start the database and update the Route 53 record.
• B.Run the database on two separate EC2 instances in different AZs with one active and the other as a standby. Attach the data volumes to the active instance. Configure an Amazon CloudWatch Events rule to invoke an AWS Lambda function on EC2 instance termination. The Lambda function launches a replacement EC2 instance. If the terminated instance was the active node, then the function attaches the data volumes to the standby node. Start the database and update the Route 53 record.
• C.Run the database in an Auto Scaling group with a minimum and maximum instance count of 1 in multiple AZs. Create an AWS Lambda function that is triggered by a scheduled Amazon CloudWatch Events rule every 4 hours to take a snapshot of the data volume and apply a tag.
  Have the instance UserData get the latest snapshot, create a new volume from it, and attach and mount the volume. Then start the database and update the Route 53 record.
• D.Run the database on two separate EC2 instances in different AZs. Configure one of the instances as a master and the other as a standby. Set up replication between the master and standby instances. Point the Route 53 record to the master. Configure an Amazon CloudWatch Events rule to invoke an AWS Lambda function upon the EC2 instance termination. The Lambda function launches a replacement EC2 instance. If the terminated instance was the active node, the function promotes the standby to master and points the Route 53 record to it.

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Your company uses an application hosted in AWS which conists of EC2 Instances. The logs of the EC2 instances need to be processed and analyzed in real time, since this is a requirement from the IT Security department. Which of the following can be used to process the logs in real time.

• A.UseCloudwatch logs to process and analyze the logs in real time
• B.UseAmazon Glacier to store the logs and then use Amazon Kinesis to process andanalyze the logs in real time
• C.UseAmazon S3 to store the logs and then use Amazon Kinesis to process and analyzethe logs in real time
• D.Useanother EC2 Instance with a larger instance type to process the logs

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Which of the following is NOT an advantage of Docker's content addressable storage model?

• A.random UUIDs improve filesystem performance
• B.improved security
• C.guarantees data integrity after push, pull, load, and save operations
• D.avoids content ID collisions

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A DevOps Engineer is building a continuous deployment pipeline for a serverless application using AWS CodePipeline and AWS CodeBuild. The source, build, and test stages have been created with the deploy stage remaining. The company wants to reduce the risk of an unsuccessful deployment by deploying to a specified subset of customers and monitoring prior to a full release to all customers.
How should the deploy stage be configured to meet these requirements?

• A.Use AWS CloudFormation to publish a new version on every stack update. Then set up a CodePipeline approval action for a Developer to test and approve the new version. Finally, use a CodePipeline invoke action to update an AWS Lambda function to use the production alias
• B.Use CodeBuild to use the AWS CLI to update the AWS Lambda function code, then publish a new version of the function and update the production alias to point to the new version of the function.
• C.Use AWS CloudFormation to define the serverless application and AWS CodeDeploy to deploy the AWS Lambda functions using DeploymentPreference: Canary10Percentl5Minutes.
• D.Use AWS CloudFormation to publish a new version on every stack update. Use the RoutingConfig property of the AWS : :Lambda: : Alias resource to update the traffic routing during the stack update.

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An online company uses Amazon EC2 Auto Scaling extensively to provide an excellent customer experience while minimizing the number of running EC2 instances. The company's self-hosted Puppet environment in the application layer manages the configuration of the instances. The IT manager wants the lowest licensing costs and wants to ensure that whenever the EC2 Auto Scaling group scales down, removed EC2 instances are deregistered from the Puppet master as soon as possible. How can the requirement be met?

• A.At instance launch time, use EC2 user data to deploy the AWS CodeDeploy agent. Use CodeDeploy to install the Puppet agent. When the Auto Scaling group scales out, run a script to register the newly deployed instances to the Puppet master. When the Auto Scaling group scales in, use the EC2 Auto Scaling lifecycle hook to trigger de-registration from the Puppet master. EC2_INSTANCE_TERMINATING
• B.Bake the AWS Systems Manager agent into the base AMI. When the Auto Scaling group scales out, use the AWS Systems Manager to install the Puppet agent, and run a script to register the newly deployed instances to the Puppet master. When the Auto Scaling group scales in, use the Systems Manager instance stop lifecycle hook to run a script to de-register the instance from the Puppet master.
• C.Bake the AWS CodeDeploy agent into the base AMI. When the Auto Scaling group scales out, use CodeDeploy to install the Puppet agent, and execute a script to register the newly deployed instances to the Puppet master. When the Auto Scaling group scales in, use the CodeDeploy ApplicationStop lifecycle hook to run a script to de-register the instance from the Puppet master.
• D.At instance launch time, use EC2 user data to deploy the AWS CodeDeploy agent. When the Auto Scaling group scales out, use CodeDeploy to install the Puppet agent, and run a script to register the newly deployed instances to the Puppet master. When the Auto Scaling group scales in, use the EC2 user data instance stop script to run a script to de-register the instance from the Puppet master.

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