A company has a legacy application running on AWS. The application can only run on one Amazon EC2 instance at a time. Application metadata is stored in Amazon S3 and must be retrieved if the instance is restarted. The instance should be automatically restarted or relaunched if performance degrades.
Which solution will satisfy those requirements?

• A.Create an Amazon Cloud Watch alarm to monitor the EC2 instance. When the StatusCheckfailed system alarm is triggered use the recover action to stop and start the instance. Use a trigger in Amazon S3 to push the metadata to the instance when it is back up and running
• B.Use the Auto Recovery feature in Amazon EC2 to automatically stop and start the EC2 instance in case of a failure .Use a trigger in Amazon S3 to push the metadata to the instance when it is back up and running
• C.Use the auto healing feature in AWS OpsWorks to stop and start the EC2 instance. Use a lifecycle event in OpsWorks to pull the data from Amazon S3 and update it on the instance.
• D.Use AWS CloudFormation to create an EC2 instance that includes the user-data property for the EC2 resource. Add a command in user data to retrieve the application metadata from Amazon S3.

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You need your API backed by DynamoDB to stay online during a total regional AWS failure. You can
tolerate a couple minutes of lag or slowness during a large failure event, but the system should recover
with normal operation after those few minutes. What is a good approach?

• A.Set up DynamoDB cross-region replication in a master-standby configuration, with a single standby in
  another region. Create an Auto Scaling Group behind an ELB in each of the two regions DynamoDB is
  running in. Add a Route53 Latency DNS Record with DNS Failover, using the ELBs in the two regions as
  the resource records.
• B.Set up a DynamoDB Multi-Region table. Create an Auto Scaling Group behind an ELB in each of the
  two regions DynamoDB is running in. Add a Route53 Latency DNS Record with DNS Failover, using the
  ELBs in the two regions as the resource records.
• C.Set up a DynamoDB Multi-Region table. Create a cross-region ELB pointing to a cross-region Auto
  Scaling Group, and direct a Route53 Latency DNS Record with DNS Failover to the cross-region ELB.
• D.Set up DynamoDB cross-region replication in a master-standby configuration, with a single standby in
  another region. Create a cross-region ELB pointing to a cross-region Auto Scaling Group, and direct a
  Route53 Latency DNS Record with DNS Failover to the cross-region ELB.

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You work for a company that automatically tags photographs using artificial neural networks (ANNs), which run on GPUs using C++. You receive millions of images at a time, but only 3 times per day on average. These images are loaded into an AWS S3 bucket you control for you in a batch, and then the customer publishes a JSON-formatted manifest into another S3 bucket you control as well. Each image takes 10 milliseconds to process using a full GPU. Your neural network software requires 5 minutes to bootstrap. Image tags are JSON objects, and you must publish them to an S3 bucket. Which of these is the best system architectures for this system?

• A.Create an OpsWorks Stack with two Layers. The first contains lifecycle scripts for launching and bootstrapping an HTTP API on G2 instances for ANN image processing, and the second has an always-on instance which monitors the S3 manifest bucket for new files. When a new file is detected, request instances to boot on the ANN layer. When the instances are booted and the HTTP APIs are up, submit processing requests to individual instances.
• B.Make an S3 notification configuration which publishes to AWS Lambda on the manifest bucket.
  Make the Lambda create a CloudFormation Stack which contains the logic to construct an autoscaling worker tier of EC2 G2 instances with the ANN code on each instance. Create an SQS queue of the images in the manifest. Tear the stack down when the queue is empty.
• C.Deploy your ANN code to AWS Lambda as a bundled binary for the C++ extension. Make an S3 notification configuration on the manifest, which publishes to another AWS Lambda running controller code. This controller code publishes all the images in the manifest to AWS Kinesis.
  Your ANN code Lambda Function uses the Kinesis as an Event Source. The system automatically scales when the stream contains image events.
• D.Create an Auto Scaling, Load Balanced Elastic Beanstalk worker tier Application and Environment.
  Deploy the ANN code to G2 instances in this tier. Set the desired capacity to 1. Make the code periodically check S3 for new manifests. When a new manifest is detected, push all of the images in the manifest into the SQS queue associated with the Elastic Beanstalk worker tier.

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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.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.
• C.Using AWS CloudFormation, create a test stack for validating the code, and then deploy the code to each production Amazon EC2 instance.
• D.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.

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An AWS CodePipeline pipeline has implemented a code release process. The pipeline is integrated with AWS CodeDeploy to deploy versions of an application to multiple Amazon EC2 instances for each CodePipeline stage.
During a recent deployment, the pipeline failed due to a CodeDeploy issue. The DevOps team wants to improve monitoring and notifications during deployment to decrease resolution times.
What should the DevOps Engineer do to create notifications when issues are discovered?

• A.Implement AWS CloudTrail to record CodePipeline and CodeDeploy API call information, create an AWS Lambda function to evaluate code deployment issues, and create an Amazon SNS topic to notify stakeholders of deployment issues.
• B.Implement AWS CloudWatch Events for CodePipeline and CodeDeploy, create an AWS Lambda function to evaluate code deployment issues, and create an Amazon SNS topic to notify stakeholders of deployment issues.
• C.Implement AWS CloudWatch Events for CodePipeline and CodeDeploy, create an Amazon Inspector assessment target to evaluate code deployment issues, and create an Amazon SNS topic to notify stakeholders of deployment issues.
• D.Implement AWS CloudWatch Logs for CodePipeline and CodeDeploy, create an AWS Config rule to evaluate code deployment issues, and create an Amazon SNS topic to notify stakeholders of deployment issues.

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