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Amazon DOP-C02 exam is designed for IT professionals who want to validate their skills and knowledge in developing and deploying applications on the Amazon Web Services (AWS) platform. AWS Certified DevOps Engineer - Professional certification is intended for individuals who have experience working with AWS technologies and services, and who are proficient in DevOps practices and principles. The DOP-C02 exam is the updated version of the AWS Certified DevOps Engineer - Professional certification, which was first introduced in 2018.

The Amazon DOP-C02 Exam covers a variety of topics and skills related to DevOps, including continuous integration and delivery (CI/CD), monitoring and logging, infrastructure as code, security, and automation. It is intended for individuals who have experience working with AWS services and tools and have a solid understanding of DevOps principles and practices.

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Amazon AWS Certified DevOps Engineer - Professional Sample Questions (Q17-Q22):

NEW QUESTION # 17
A DevOps engineer has implemented a Cl/CO pipeline to deploy an AWS Cloud Format ion template that provisions a web application. The web application consists of an Application Load Balancer (ALB) a target group, a launch template that uses an Amazon Linux 2 AMI an Auto Scaling group of Amazon EC2 instances, a security group and an Amazon RDS for MySQL database The launch template includes user data that specifies a script to install and start the application.
The initial deployment of the application was successful. The DevOps engineer made changes to update the version of the application with the user dat a. The CI/CD pipeline has deployed a new version of the template However, the health checks on the ALB are now failing The health checks have marked all targets as unhealthy.
During investigation the DevOps engineer notices that the Cloud Formation stack has a status of UPDATE_COMPLETE. However, when the DevOps engineer connects to one of the EC2 instances and checks /varar/log messages, the DevOps engineer notices that the Apache web server failed to start successfully because of a configuration error How can the DevOps engineer ensure that the CloudFormation deployment will fail if the user data fails to successfully finish running?

A. Use the cfn-signal helper script to signal success or failure to CloudFormation Use the WaitOnResourceSignals update policy within the CloudFormation template Set an appropriate timeout for the update policy.
B. Create a lifecycle hook on the Auto Scaling group by using the AWS AutoScaling LifecycleHook resource Create an Amazon Simple Notification Service (Amazon SNS) topic as the target to signal success or failure to CloudFormation Set an appropriate timeout on the lifecycle hook.
C. Create an Amazon CloudWatch alarm for the UnhealthyHostCount metric. Include an appropriate alarm threshold for the target group Create an Amazon Simple Notification Service (Amazon SNS) topic as the target to signal success or failure to CloudFormation
D. Use the Amazon CloudWatch agent to stream the cloud-init logs Create a subscription filter that includes an AWS Lambda function with an appropriate invocation timeout Configure the Lambda function to use the SignalResource API operation to signal success or failure to CloudFormation.

Answer: A

Explanation:
https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-attribute-updatepolicy.html

NEW QUESTION # 18
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 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.
B. 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.
C. 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.
D. 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.

Answer: B

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 # 19
A company uses a pipeline in AWS CodePipeline to deploy an application. The company created an AWS Fault Injection Service (AWS FIS) experiment template to test the resiliency of the application. A DevOps engineer needs to integrate the experiment into the pipeline.
Which solution will meet this requirement?

A. Create an Amazon EventBridge scheduler. Grant the scheduler permission to start the AWS FIS experiment. Configure a new stage in the pipeline that includes an action to invoke the EventBridge scheduler.
B. Create an AWS Lambda function to start the AWS FIS experiment. Grant the Lambda function permission to start the experiment. Create a new stage in the pipeline that has a Lambda action. Set the action to invoke the Lambda function.
C. Export the AWS FIS experiment template to an Amazon S3 bucket. Create an AWS CodeBuild unit test project that has a buildspec that starts the AWS FIS experiment. Grant the CodeBuild project access to start the experiment. Configure a new stage in the pipeline that includes an action to run the CodeBuild unit test project.
D. Configure a new stage in the pipeline that includes an AWS FIS action. Configure the action to reference the AWS FIS experiment template. Grant the pipeline access to start the experiment.

Answer: B

NEW QUESTION # 20
A DevOps engineer is using AWS CodeDeploy across a fleet of Amazon EC2 instances in an EC2 Auto Scaling group. The associated CodeDeploy deployment group, which is integrated with EC2 Auto Scaling, is configured to perform in-place deployments with codeDeployDefault.oneAtATime During an ongoing new deployment, the engineer discovers that, although the overall deployment finished successfully, two out of five instances have the previous application revision deployed. The other three instances have the newest application revision What is likely causing this issue?

A. EC2 Auto Scaling launched two new instances while the new deployment had not yet finished, causing the previous version to be deployed on the affected instances.
B. The CodeDeploy agent was not installed in two affected instances.
C. A failed Afterinstall lifecycle event hook caused the CodeDeploy agent to roll back to the previous version on the affected instances
D. The two affected instances failed to fetch the new deployment.

Answer: C

Explanation:
When AWS CodeDeploy performs an in-place deployment, it updates the instances with the new application revision one at a time, as specified by the deployment configuration codeDeployDefault.oneAtATime. If a lifecycle event hook, such as AfterInstall, fails during the deployment, CodeDeploy will attempt to roll back to the previous version on the affected instances. This is likely what happened with the two instances that still have the previous application revision deployed. The failure of the AfterInstall lifecycle event hook triggered the rollback mechanism, resulting in those instances reverting to the previous application revision.
Reference:
AWS CodeDeploy documentation on redeployment and rollback procedures1.
Stack Overflow discussions on re-deploying older revisions with AWS CodeDeploy2.
AWS CLI reference guide for deploying a revision2.

NEW QUESTION # 21
A company provides an application to customers. The application has an Amazon API Gateway REST API that invokes an AWS Lambda function. On initialization, the Lambda function loads a large amount of data from an Amazon DynamoDB table. The data load process results in long cold-start times of 8-10 seconds. The DynamoDB table has DynamoDB Accelerator (DAX) configured.
Customers report that the application intermittently takes a long time to respond to requests. The application receives thousands of requests throughout the day. In the middle of the day, the application experiences 10 times more requests than at any other time of the day. Near the end of the day, the application's request volume decreases to 10% of its normal total.
A DevOps engineer needs to reduce the latency of the Lambda function at all times of the day.
Which solution will meet these requirements?

A. Configure provisioned concurrency on the Lambda function. Configure AWS Application Auto Scaling on the Lambda function with provisioned concurrency values set to a minimum of 1 and a maximum of 100.
B. Configure provisioned concurrency on the Lambda function with a concurrency value of 1. Delete the DAX cluster for the DynamoDB table.
C. Configure reserved concurrency on the Lambda function. Configure AWS Application Auto Scaling on the API Gateway API with a reserved concurrency maximum value of 100.
D. Configure reserved concurrency on the Lambda function with a concurrency value of 0.

Answer: A

Explanation:
The following are the steps that the DevOps engineer should take to reduce the latency of the Lambda function at all times of the day:
Configure provisioned concurrency on the Lambda function.
Configure AWS Application Auto Scaling on the Lambda function with provisioned concurrency values set to a minimum of 1 and a maximum of 100.
The provisioned concurrency setting ensures that there is always a minimum number of Lambda function instances available to handle requests. The Application Auto Scaling setting will automatically scale the number of Lambda function instances up or down based on the demand for the application.
This solution will ensure that the Lambda function is able to handle the increased load during the middle of the day, while also keeping the cold-start latency low.
The following are the reasons why the other options are not correct:
Option A is incorrect because it will not reduce the cold-start latency of the Lambda function.
Option B is incorrect because it will not scale the number of Lambda function instances up or down based on demand.
Option D is incorrect because it will only configure reserved concurrency on the API Gateway API, which will not affect the Lambda function.

NEW QUESTION # 22
......

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