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Amazon AWS Certified DevOps Engineer - Professional Sample Questions (Q101-Q106):

NEW QUESTION # 101
A company is building a web and mobile application that uses a serverless architecture powered by AWS Lambda and Amazon API Gateway. The company wants to fully automate the backend Lambda deployment based on code that is pushed to the appropriate environment branch in an AWS CodeCommit repository.
The deployment must have the following:
- Separate environment pipelines for testing and production.
- Automatic deployment that occurs for test environments only.
Which steps should be taken to meet these requirements?

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 a deployment step to deploy the Lambda functions with AWS CloudFormation.
B. 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.
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 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.

Answer: C

Explanation:
First, A&B both are in-correct: As a basic policy - do not create a repo for the same code for multiple environments. Always create a branch from the same repo. The strategy is wrong for A&B. Now C&D: D uses Lambda function with s3, whereas C uses code pipeline to store and build. Using code pipeline is a smart choice rather than using S3 as a code pipeline that offers better branching strategy and controls.

NEW QUESTION # 102
You want to build a new search tool feature for your monitoring system that will allow your information security team to quickly audit all API calls in your AWS accounts.
What combination of AWS services can you use to develop and automate the backend processes supporting this tool?
Choose 3 answers.

A. Use Amazon Cloudwatch to ship AWS CloudTrail logs to your monitoring system.
B. Use AWS CloudTrail to store API call logs in an Amazon S3 bucket. Configure an Amazon Simple Notification Service topic called "log-notification" that notifies subscribers when new logs are available.
Subscribe an Amazon SQS queue to the topic.
C. Create an Amazon CloudSearch domain for API call logs. Configure the search domain so that it can be used to index API call logs for the search tool.
D. Create Amazon Cloudwatch custom metrics for the API call logs. Configure a Cloudwatch search domain so that it can be used to index API call logs for the search tool.
E. Use AWS CloudTrail to store API call logs in an Amazon S3 bucket. Configure Amazon Simple Email Service (SES) to notify subscribers when new logs are available. Subscribe an Amazon SQS queue to the email domain.
F. Create an AWS Elastic Beanstalk application in worker role mode that uses an Amazon SQS queue to facilitate batch processing new API call log files retrieved from an Amazon S3 bucket into a search index.
G. Create an AWS Elastic Beanstalk application in worker role mode that uses an Amazon Simple Email Service (SES) domain to facilitate batch processing new API call log files retrieved from an Amazon S3 bucket into a search index.

Answer: B,C,F

NEW QUESTION # 103
A DevOps Engineer is asked to implement a strategy for deploying updates to a web application with zero downtime. The application infrastructure is defined in AWS CloudFormation and is made up of an Amazon Route 53 record, an Application Load Balancer, Amazon EC2 instances in an EC2 Auto Scaling group, and Amazon DynamoDB tables. To avoid downtime, there must be an active instance serving the application at all times.
Which strategies will ensure the deployment happens with zero downtime? (Select TWO.)

A. In the CloudFormation template, modify the AWS:: AutoScaling::DeploymentUpdates resource and add an UpdatePolicy attribute to define the required elements for a deployment with zero downtime.
B. In the CloudFormation template, modify the AWS::AutoScaling::AutoscalingGroup resource and add an UpdatePolicy attribute to define the required elements for a deployment with zero downtime.
C. Add a new Application Load Balancer and Auto Scaling group to the CloudFormation template.
Deploy new changes to the inactive Auto Scaling group. Use Route 53 to change the active Application Load Balancer.
D. Add a new Application Load Balancer and Auto Scaling group to the CloudFormation template.
Modify the AWS::AutoScaling::AutoScalingGroup resource and add an UpdatePolicy attribute to perform rolling updates.
E. In the CloudFormation template, modify the UpgradePolicy attribute for the CloudFormation stack and specify the Auto Scaling group that will be updated Configure MinSuccessfulInstancesPercent and PauseTime to ensure the deployment happens with zero downtime.

Answer: B,C

NEW QUESTION # 104
A company hosts parts of a Python-based application using AWS Elastic Beanstalk. An Elastic Beanstalk CLI is being used to create and update the environments. The Operations team detected an increase in requests in one of the Elastic Beanstalk environments that caused downtime overnight. The team noted that the policy used for AWS Auto Scaling is NetworkOut. Based on load testing metrics, the team determined that the application needs to scale CPU utilization to improve the resilience of the environments. The team wants to implement this across all environments automatically.
Following AWS recommendations, how should this automation be implemented?

A. Using ebextensions, place a script within the fileskey and place it in /opt/elasticbeanstalk/ hooks/appdeploy/preto perform an API call to modify the scaling metric to CPUUtilizationfor the Auto Scaling configuration. Use leader_onlyto place this script in only the first instance launched within the environment.
B. Using ebextensions, configure the option setting MeasureNameto CPUUtilizationwithin the aws:autoscaling:triggernamespace.
C. Using ebextensions, place a command within the container_commandskey to perform an API call to modify the scaling metric to CPUUtilizationfor the Auto Scaling configuration. Use leader_onlyto execute this command in only the first instance launched within the environment.
D. Using ebextensions, create a custom resource that modifies the AWSEBAutoScalingScaleUpPolicy and AWSEBAutoScalingScaleDownPolicyresources to use CPUUtilizationas a metric to scale for the Auto Scaling group.

Answer: B

NEW QUESTION # 105
A company is reviewing its IAM policies. One policy written by the DevOps Engineer has been flagged as too permissive. The policy is used by an AWS Lambda function that issues a stop command to Amazon EC2 instances tagged with Environment: NonProduction over the weekend.
The current policy is:

What changes should the Engineer make to achieve a policy of least permission? (Select THREE.)

Answer: B,C,E

NEW QUESTION # 106
......

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