You need to deploy a new application version to production. Because the deployment is high-risk, you need to roll the new version out to users over a number of hours, to make sure everything is working correctly. You need to be able to control the proportion of users seeing the new version of the application down to the percentage point. You use ELB and EC2 with Auto Scaling Groups and custom AMIs with your code pre- installed assigned to Launch Configurations. There are no database-level changes during your deployment.
You have been told you cannot spend too much money, so you must not increase the number of EC2 instances much at all during the deployment, but you also need to be able to switch back to the original version of code quickly if something goes wrong.
What is the best way to meet these requirements?

• A.Create a second ELB, Auto Scaling Launch Configuration, and Auto Scaling Group using the Launch Configuration. Create AMIs with all code pre-installed. Assign the new AMI to the second Auto Scaling Launch Configuration. Use Route53 Weighted Round Robin Records to adjust the proportion of traffic hitting the two ELBs.
• B.Use the Blue-Green deployment method to enable the fastest possible rollback if needed. Create a full second stack of instances and cut the DNS over to the new stack of instances, and change the DNS back if a rollback is needed.
• C.Create AMIs with all code pre-installed. Assign the new AMI to the Auto Scaling Launch Configuration, to replace the old one. Gradually terminate instances running the old code (launched with the old Launch Configuration) and allow the new AMIs to boot to adjust the traffic balance to the new code. On rollback, reverse the process by doing the same thing, but changing the AMI on the Launch Config back to the original code.
• D.Migrate to use AWS Elastic Beanstalk. Use the established and well-tested Rolling Deployment setting AWS provides on the new Application Environment, publishing a zip bundle of the new code and adjusting the wait period to spread the deployment over time. Re-deploy the old code bundle to rollback if needed.

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During metric analysis, your team has determined that the company's website during peak hours is experiencing response times higher than anticipated. You currently rely on Auto Scaling to make sure that you are scaling your environment during peak windows. How can you improve your Auto Scaling policy to reduce this high response time? Choose 2 answers.

• A.Push custom metrics to CloudWatch to monitor your CPU and network bandwidth from your servers, which will allow your Auto Scaling policy to have betterfine-grain insight.
• B.IncreaseyourAutoScalinggroup'snumberofmaxservers.
• C.Create a script that runs and monitors your servers; when it detects an anomaly in load, it posts to an Amazon SNS topic that triggers Elastic Load Balancing to add more servers to the load balancer.
• D.Push custom metrics to CloudWatch for your application that include more detailed information about your web application, such as how many requests it is handling and how many are waiting to be processed.

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Your application is currently running on Amazon EC2 instances behind a load balancer. Your management
has decided to use a Blue/Green deployment strategy. How should you implement this for each deployment?

• A.Set up Amazon Route 53 health checks to fail over from any Amazon EC2 instance that is currently
  being deployed to.
• B.Using AWS CloudFormation, create a test stack for validating the code, and then deploy the code to
  each production Amazon EC2 instance.
• C.Create a new load balancer with new Amazon EC2 instances, carry out the deployment, and then switch
  DNS over to the new load balancer using Amazon Route 53 after testing.
• D.Launch more Amazon EC2 instances to ensure high availability, de-register each Amazon EC2 instance
  from the load balancer, upgrade it, and test it, and then register it again with the load balancer.

Correct Answer: C

Explanation
The below diagram shows how this can be done

1) First create a new ELB which will be used to point to the new production changes.
2) Use the Weighted Route policy for Route53 to distribute the traffic to the 2 ELB's based on a 80-20% traffic
scenario. This is the normal case, the % can be changed based on the requirement.
3) Finally when all changes have been tested, Route53 can be set to 100% for the new ELB.
Option A is incorrect because this is a failover scenario and cannot be used for Blue green deployments. In
Blue Green deployments, you need to have 2 environments running side by side.
Option B is incorrect, because you need to a have a production stack with the changes which will run side by
side.
Option D is incorrect because this is not a blue green deployment scenario. You cannot control which users
will go the new EC2 instances.
For more information on blue green deployments, please refer to the below document link: from AWS
* https://dOawsstatic.com/whitepapers/AWS_Blue_Green_Deployments.pdf

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A company wants to use Amazon ECS to provide a Docker container runtime environment. For compliance reasons, all Amazon EBS volumes used in the ECS cluster must be encrypted. Rolling updates will be made to the cluster instances and the company wants the instances drained of all tasks before being terminated.
How can these requirements be met? (Choose two.)

• A.Create an IAM role that allows the action ECS::EncryptedImage. Configure the AWS CLI and a profile to use this role. Start the cluster using the AWS CLI providing the --use-encrypted-imageand --kms- keyarguments to the create-clusterECS command.
• B.Copy the default AWS CloudFormation template that ECS uses to deploy cluster instances. Modify the template resource EBS configuration setting to set 'Encrypted: True' and include the AWS KMS alias: 'aws/ ebs' to encrypt the AMI.
• C.Modify the default ECS AMI user data to create a script that executes docker rm -f {id}for all running container instances. Copy the script to the /etc/init.d/rc.d directory and execute chconfigenabling the script to run during operating system shutdown.
• D.Create an Auto Scaling lifecycle hook backed by an AWS Lambda function that uses the AWS SDK to mark a terminating instance as DRAINING. Prevent the lifecycle hook from completing until the running tasks on the instance are zero.
• E.Use AWS CodePipeline to build a pipeline that discovers the latest Amazon-provided ECS AMI, then copies the image to an encrypted AMI outputting the encrypted AMI ID. Use the encrypted AMI ID when deploying the cluster.

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Your company is planning to develop an application in which the front end is in .Net and the backend is in DynamoDB. There is an expectation of a high load on the application. How could you ensure the scalability of the application to reduce the load on the DynamoDB database? Choose an answer from the options below.

• A.Add more DynamoDB databases to handle the load.
• B.Increase write capacity of Dynamo DB to meet the peak loads
• C.Use SQS to assist and let the application pull messages and then perform the relevant operation in DynamoDB.
• D.Launch DynamoDB in Multi-AZ configuration with a global index to balance writes

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