Question 1

A software team is using AWS CodePipeline to automate its Java application release pipeline. The pipeline consists of a source stage, then a build stage, and then a deploy stage. Each stage contains a single action that has a runOrder value of 1.

The team wants to integrate unit tests into the existing release pipeline. The team needs a solution that deploys only the code changes that pass all unit tests.

Which solution will meet these requirements?

Options :

A : Modify the build stage. Add a test action that has a runOrder value of 1. Use AWS CodeDeploy as the action provider to run unit tests.

B : Modify the build stage. Add a test action that has a runOrder value of 2. Use AWS CodeBuild as the action provider to run unit tests.

C : Modify the deploy stage. Add a test action that has a runOrder value of 1. Use AWS CodeDeploy as the action provider to run unit tests.

D : Modify the deploy stage. Add a test action that has a runOrder value of 2. Use AWS CodeBuild as the action provider to run unit tests.

Answer: C

Question 2

An enterprise resource planning application is hosted in an Auto Scaling group of EC2 instances behind an Application Load Balancer which uses an Amazon DynamoDB table as its data store. For the application’s reporting module, there are five Lambda functions which are reading from the DynamoDB Streams of the table to count the number of products, monitor the inventory, generate reports, move new items to a Kinesis Data Firehose for analytics, and many more. The operations team discovered that in peak times, the Lambda functions are getting a stream throttling error and some of the requests fail which affects the performance of the reporting module.

Which of the following is the MOST scalable and cost-effective solution with the LEAST amount of operational overhead?

Options :

A : Refactor your architecture to use Amazon Kinesis Adapter for real-time processing of streaming data at a massive scale instead of directly consuming the stream using Lambda. Re-architect the reporting module to use Amazon Kinesis Data Analytics.

B : Use the Amazon CodeGuru service to optimize the codebase of the reporting module. Create a new global secondary index (GSI) in the DynamoDB table to improve the performance of the queries. Increase the allocated RCU of the table. Disable the Amazon DynamoDB streams and refactor the Lambda functions to directly query from the table. Refactor the reporting module to use Amazon Kinesis Data Analytics.

C : Create a new local secondary index (LSI) in the DynamoDB table to improve the performance of the queries. Double the allocated RCU of the table. Refactor the Lambda functions to directly query from the table and disable the DynamoDB streams. Increase the concurrency limits of each Lambda function to avoid throttling errors and set the ParallelizationFactor to 10. Re-architect the reporting module to use Amazon Kinesis Data Analytics.

D : Delete all of the Lambda functions and move all of the processing on an Amazon ECS Cluster with Auto Scaling enabled using AWS App Runner. Set up AWS Glue to consume the DynamoDB stream which will be processed by ECS. Re-factor the reporting module to use Amazon Kinesis Data Analytics.

Answer: A

Question 3

A leading IT consultancy firm has several Python-based Flask and Django web applications hosted in AWS. Some of their developers are freelance contractors located overseas. The firm wants to automate remediation actions for issues relating to the health of its AWS resources by using the AWS Health Dashboard and the AWS Health API. They need to automatically detect any of their own IAM access key that is accidentally or deliberately listed on a public Github repository. Once detected, the IAM access key must be immediately deleted and a notification should be sent to the DevOps team.

As a DevOps Engineer, how can you meet this requirement?

Options :

A : Set up three Lambda functions in AWS Step Functions that deletes the exposed IAM access key, summarizes the recent API activity for the exposed key using CloudTrail and sends a notification to the IT Security team using Amazon SNS. Create a CloudWatch Events rule with an aws.health event source and the AWS_RISK_CREDENTIALS_EXPOSED event to monitor any exposed IAM keys from the Internet. Set the Step Functions as the target of the CloudWatch Events rule.

B : Set up three Lambda functions in AWS Step Functions that deletes the exposed IAM access key, summarizes the recent API activity for the exposed key using CloudTrail and sends a notification to the IT Security team using Amazon SNS. Use a combination of Amazon GuardDuty and Amazon Macie to monitor any exposed IAM keys from the Internet. Set the Step Functions as the target of the CloudWatch Events rule.

C : Set up three Lambda functions in AWS Step Functions that deletes the exposed IAM access key, summarizes the recent API activity for the exposed key using CloudTrail and sends a notification to the IT Security team using Amazon SNS. Create an AWS Personal Health Dashboard rule for the AWS_RISK_CREDENTIALS_EXPOSED event to monitor any exposed IAM keys from the Internet. Set the Step Functions as the target of the CloudWatch Events rule.

D : Set up three Lambda functions in AWS Step Functions that deletes the exposed IAM access key, summarizes the recent API activity for the exposed key using CloudTrail and sends a notification to the IT Security team using Amazon SNS. Create an AWS Config rule for the AWS_RISK_CREDENTIALS_EXPOSED event with Multi-Account Multi-Region Data Aggregation to monitor any exposed IAM keys from the Internet. Set the Step Functions as the target of the CloudWatch Events rule.

Answer: A

Question 4

A government-sponsored health service is running their web application containing information about the clinics, hospitals, medical specialists and other medical services in the country. They also have a set of public web services which enable third-party companies to search medical data for their respective applications and clients. Lambda functions are used for the public APIs. For its database-tier, an Amazon DynamoDB table stores all of the data with an Amazon ES domain which supports the search feature and stores the indexes. A DevOps engineer has been instructed to ensure that in the event of a failed deployment, there should be no downtime and a system should be in place to prevent subsequent deployments. The service must strictly maintain full capacity during API deployment without any reduced capacity to avoid degradation of service.

How can the engineer meet the above requirements in the MOST efficient way?

Options :

A : Deploy the DynamoDB tables, Lambda functions, and Amazon ES domain using AWS CloudFormation. Deploy changes with an AWS CodeDeploy blue/green deployment. Host the web application in AWS Elastic Beanstalk and set the deployment policy to All at Once.

B : Deploy the DynamoDB tables, Lambda functions, and Amazon ES domain using AWS CloudFormation. Deploy changes with an AWS CodeDeploy in-place deployment. Host the web application in AWS Elastic Beanstalk and set the deployment policy to Rolling.

C : Deploy the DynamoDB tables, Lambda functions, and Amazon ES domain using AWS CloudFormation. Deploy changes with an AWS CodeDeploy blue/green deployment. Host the web application in AWS Elastic Beanstalk and set the deployment policy to Immutable.

D : Deploy the DynamoDB tables, Lambda functions, and Amazon ES domain using AWS CloudFormation. Deploy changes with an AWS CodeDeploy blue/green deployment. Host the web application in Amazon S3 and enable cross-region replication.

Answer: C

Question 5

A company has an on-premises application that is written in Go. A DevOps engineer must move the application to AWS. The company's development team wants to enable blue/green deployments and perform A/B testing.

Which solution will meet these requirements?

Options :

A : Deploy the application on an Amazon EC2 instance, and create an AMI of the instance. Use the AMI to create an automatic scaling launch configuration that is used in an Auto Scaling group. Use Elastic Load Balancing to distribute traffic. When changes are made to the application, a new AMI will be created, which will initiate an EC2 instance refresh.

B : Use Amazon Lightsail to deploy the application. Store the application in a zipped format in an Amazon S3 bucket. Use this zipped version to deploy new versions of the application to Lightsail. Use Lightsail deployment options to manage the deployment.

C : Use AWS CodeArtifact to store the application code. Use AWS CodeDeploy to deploy the application to a fleet of Amazon EC2 instances. Use Elastic Load Balancing to distribute the traffic to the EC2 instances. When making changes to the application, upload a new version to CodeArtifact and create a new CodeDeploy deployment.

D : Use AWS Elastic Beanstalk to host the application. Store a zipped version of the application in Amazon S3. Use that location to deploy new versions of the application. Use Elastic Beanstalk to manage the deployment options

Answer: D