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To take the Amazon DOP-C02 Exam, candidates must have a good understanding of various DevOps practices and tools, including continuous integration, continuous delivery, automation, monitoring, and infrastructure as code. They should also be familiar with AWS services such as EC2, S3, RDS, and CloudFormation, and should be able to use them to build and deploy complex systems.
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Amazon AWS Certified DevOps Engineer - Professional Sample Questions (Q12-Q17):
NEW QUESTION # 12
A company wants to set up a continuous delivery pipeline. The company stores application code in a private GitHub repository. The company needs to deploy the application components to Amazon Elastic Container Service (Amazon ECS). Amazon EC2, and AWS Lambda. The pipeline must support manual approval actions.
Which solution will meet these requirements?
- A. Use AWS CodePipeline with Amazon ECS. Amazon EC2, and Lambda as deploy providers.
- B. Use AWS CodePipeline with AWS Elastic Beanstalk as the deploy provider.
- C. Use AWS CodeDeploy with GitHub integration to deploy the application.
- D. Use AWS CodePipeline with AWS CodeDeploy as the deploy provider.
Answer: D
Explanation:
Explanation
https://docs.aws.amazon.com/codedeploy/latest/userguide/deployment-steps.html
NEW QUESTION # 13
A DevOps engineer needs to configure a blue green deployment for an existing three-tier application. The application runs on Amazon EC2 instances and uses an Amazon RDS database The EC2 instances run behind an Application Load Balancer (ALB) and are in an Auto Scaling group.
The DevOps engineer has created a launch template and an Auto Scaling group for the blue environment. The DevOps engineer also has created a launch template and an Auto Scaling group for the green environment.
Each Auto Scaling group deploys to a matching blue or green target group. The target group also specifies which software blue or green gets loaded on the EC2 instances. The ALB can be configured to send traffic to the blue environments target group or the green environments target group. An Amazon Route 53 record for www example com points to the ALB.
The deployment must move traffic all at once between the software on the blue environment's EC2 instances to the newly deployed software on the green environments EC2 instances What should the DevOps engineer do to meet these requirements?
- A. Start a rolling restart of the Auto Scaling group for the green environment to deploy the new software on the green environment's EC2 instances When the rolling restart is complete, update the Route 53 DNS to point to the green environments endpoint on the ALB.
- B. Update the launch template to deploy the green environment's software on the blue environment's EC2 instances Keep the target groups and Auto Scaling groups unchanged in both environments Perform a rolling restart of the blue environment's EC2 instances.
- C. Use an AWS CLI command to update the ALB to send traffic to the green environment's target group.
Then start a rolling restart of the Auto Scaling group for the green environment to deploy the new software on the green environment's EC2 instances.
- D. Start a rolling restart to the Auto Scaling group tor the green environment to deploy the new software on the green environment's EC2 instances When the rolling restart is complete, use an AWS CLI command to update the ALB to send traffic to the green environment's target group.
Answer: D
Explanation:
This solution will meet the requirements because it will use a rolling restart to gradually replace the EC2 instances in the green environment with new instances that have the new software version installed. A rolling restart is a process that terminates and launches instances in batches, ensuring that there is always a minimum number of healthy instances in service. This way, the green environment can be updated without affecting the availability or performance of the application. When the rolling restart is complete, the DevOps engineer can use an AWS CLI command to modify the listenerrules of the ALB and change the default action to forward traffic to the green environment's target group. This will switch the traffic from the blue environment to the green environment all at once, as required by the question.
NEW QUESTION # 14
A company has an application that is using a MySQL-compatible Amazon Aurora Multi-AZ DB cluster as the database. A cross-Region read replica has been created for disaster recovery purposes. A DevOps engineer wants to automate the promotion of the replica so it becomes the primary database instance in the event of a failure.
Which solution will accomplish this?
- A. Create an AWS Lambda function to modify the application's AWS CloudFormation template to promote the replica, apply the template to update the stack, and point the application to the newly promoted instance. Create an Amazon CloudWatch alarm to invoke this Lambda function after the failure event occurs.
- B. Configure a latency-based Amazon Route 53 CNAME with health checks so it points to both the primary and replica endpoints. Subscribe an Amazon SNS topic to Amazon RDS failure notifications from AWS CloudTrail and use that topic to invoke an AWS Lambda function that will promote the replica instance as the primary.
- C. Create an Aurora custom endpoint to point to the primary database instance. Configure the application to use this endpoint. Configure AWS CloudTrail to run an AWS Lambda function to promote the replica instance and modify the custom endpoint to point to the newly promoted instance.
- D. Store the Aurora endpoint in AWS Systems Manager Parameter Store. Create an Amazon EventBridge event that detects the database failure and runs an AWS Lambda function to promote the replica instance and update the endpoint URL stored in AWS Systems Manager Parameter Store. Code the application to reload the endpoint from Parameter Store if a database connection fails.
Answer: D
Explanation:
Explanation
EventBridge is needed to detect the database failure. Lambda is needed to promote the replica as it's in another Region (manual promotion, otherwise). Storing and updating the endpoint in Parameter store is important in updating the application. Look at High Availability section of Aurora FAQ:
https://aws.amazon.com/rds/aurora/faqs/
NEW QUESTION # 15
A DevOps team uses AWS CodePipeline, AWS CodeBuild, and AWS CodeDeploy to deploy an application.
The application is a REST API that uses AWS Lambda functions and Amazon API Gateway Recent deployments have introduced errors that have affected many customers.
The DevOps team needs a solution that reverts to the most recent stable version of the application when an error is detected. The solution must affect the fewest customers possible.
Which solution Will meet these requirements With the MOST operational efficiency?
- A. Set the deployment configuration in CodeDeploy to LambdaAllAtOnce Configure manual rollbacks on the deployment group. Create an Amazon Simple Notification Service (Amazon SNS) topc to send notifications every time a deployrnent fads. Configure the SNS topc to Invoke a new Lambda function that stops the current deployment and starts the most recent successful deployment
- B. Set the deployment configuration in CodeDepIoy to LambdaAlIAtOnce Configure automatic rollbacks on the deployment group Create an Amazon CloudWatch alarm that detects HTTP Bad Gateway errors on API Gateway Configure the deployment group to roll back when the number of alarms meets the alarm threshold
- C. Set the deployment configuration in CodeDeploy to LambdaCanaryIOPercentIOMinutes Configure manual rollbacks on the deployment group Create a metric filter on an Amazon CloudWatch log group for API Gateway to monitor HTTP Bad Gateway errors. Configure the metric filter to Invoke a new Lambda function that stops the current eployment and starts the most recent successful deployment
- D. Set the deployment configuration in CodeDeploy to LambdaCanary10Percent10Minutes. Configure automatic rollbacks on the deployment group Create an Amazon CloudWatch alarm that detects HTTP Bad Gateway errors on API Gateway Configure the deployment group toroll back when the number of alarms meets the alarm threshold
Answer: D
Explanation:
* Option A is incorrect because setting the deployment configuration to LambdaAllAtOnce means that the new version of the application will be deployed to all Lambda functions at once, affecting all customers. This does not meet the requirement of affecting the fewest customers possible. Moreover, configuring automatic rollbacks on the deployment group is not operationally efficient, as it requires manual intervention to fix the errors and redeploy the application.
* Option B is correct because setting the deployment configuration to
LambdaCanary10Percent10Minutes means that the new version of the application will be deployed to
10 percent of the Lambda functions first, and then to the remaining 90 percent after 10 minutes. This minimizes the impact of errors on customers, as only 10 percent of them will be affected by a faulty deployment. Configuring automatic rollbacks on the deployment group also meets the requirement of reverting to the most recent stable version of the application when an error is detected. Creating a CloudWatch alarm that detects HTTP Bad Gateway errors on API Gateway is a valid way to monitor the health of the application and trigger a rollback if needed.
* Option C is incorrect because setting the deployment configuration to LambdaAllAtOnce means that the new version of the application will be deployed to all Lambda functions at once, affecting all customers. This does not meet the requirement of affecting the fewest customers possible. Moreover, configuring manual rollbacks on the deployment group is not operationally efficient, as it requires human intervention to stop the current deployment and start a new one. Creating an SNS topic to send notifications every time a deployment fails is not sufficient to detect errors in the application, as it does not monitor the API Gateway responses.
* Option D is incorrect because configuring manual rollbacks on the deployment group is not operationally efficient, as it requires human intervention to stop the current deployment and start a new one. Creating a metric filter on a CloudWatchlog group for API Gateway to monitor HTTP Bad Gateway errors is a valid way to monitor the health of the application, but invoking a new Lambda function to perform a rollback is unnecessary and complex, as CodeDeploy already provides automatic rollback functionality.
References:
* AWS CodeDeploy Deployment Configurations
* [AWS CodeDeploy Rollbacks]
* Amazon CloudWatch Alarms
NEW QUESTION # 16
A company wants to migrate its content sharing web application hosted on Amazon EC2 to a serverless architecture. The company currently deploys changes to its application by creating a new Auto Scaling group of EC2 instances and a new Elastic Load Balancer, and then shifting the traffic away using an Amazon Route
53 weighted routing policy.
For its new serverless application, the company is planning to use Amazon API Gateway and AWS Lambda.
The company will need to update its deployment processes to work with the new application. It will also need to retain the ability to test new features on a small number of users before rolling the features out to the entire user base.
Which deployment strategy will meet these requirements?
- A. Use AWS Elastic Beanstalk to deploy API Gateway and Lambda functions. When code needs to be changed, deploy a new version of the API and Lambda functions. Shift traffic gradually using an Elastic Beanstalk blue/green deployment.
- B. Use AWS OpsWorks to deploy API Gateway in the service layer and Lambda functions in a custom layer. When code needs to be changed, use OpsWorks to perform a blue/green deployment and shift traffic gradually.
- C. Use AWS CDK to deploy API Gateway and Lambda functions. When code needs to be changed, update the AWS CloudFormation stack and deploy the new version of the APIs and Lambda functions. Use a Route 53 failover routing policy for the canary release strategy.
- D. Use AWS CloudFormation to deploy API Gateway and Lambda functions using Lambda function versions. When code needs to be changed, update the CloudFormation stack with the new Lambda code and update the API versions using a canary release strategy. Promote the new version when testing is complete.
Answer: D
Explanation:
Explanation
https://docs.aws.amazon.com/serverless-application-model/latest/developerguide/automating-updates-to-serverle
NEW QUESTION # 17
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