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The AWS Certified DevOps Engineer - Professional certification is recognized globally and is highly valued by employers. It demonstrates a candidate's expertise in building and managing applications on AWS and their ability to automate and optimize the CI/CD pipeline. AWS Certified DevOps Engineer - Professional certification is an excellent way to enhance your career prospects and increase your earning potential.

Amazon Web Services (AWS) is a cloud computing platform that has revolutionized the way businesses operate. It provides a wide range of services that cater to the needs of businesses of all sizes. One of the key services offered by AWS is DevOps, which is a set of practices that combines software development and IT operations. The AWS Certified DevOps Engineer - Professional (DOP-C01) exam is designed to test the skills and knowledge of professionals who work with AWS DevOps.

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Amazon AWS Certified DevOps Engineer - Professional Sample Questions (Q28-Q33):

NEW QUESTION # 28
You have an asynchronous processing application using an Auto Scaling Group and an SQS Queue. The Auto Scaling Group scales according to the depth of the job queue. The completion velocity of the jobs has gone down, the Auto Scaling Group size has maxed out, but the inbound job velocity did not increase.
What is a possible issue?

A. The routing tables changed and none of the workers can process events anymore.
B. The scaling metric is not functioning correctly.
C. Someone changed the IAM Role Policy on the instances in the worker group and broke permissions to access the queue.
D. Some of the new jobs coming in are malformed and unprocessable.

Answer: D

Explanation:
The IAM Role must be fine, as if it were broken, NO jobs would be processed since the system would never be able to get any queue messages. The same reasoning applies to the routing table change. The scaling metric is fine, as instance count increased when the queue depth increased due to more messages entering than exiting. Thus, the only reasonable option is that some of the recent messages must be malformed and unprocessable.
https://github.com/andrew-
templeton/cloudacademy/blob/fca920b45234bbe99cc0e8efb9c65134884dd48 9/questions/null

NEW QUESTION # 29
A Development team is adding a new country to an e-commerce application. This addition requires that new application features be added to the shipping component of the application. The team has not decided if all new features should be added, as some will take approximately six weeks to build. While the final decision on the shipping component features is being made, other team members are continuing to work on other features of the application.
Based on this situation, how should the application feature deployments be managed?

A. Create a new repository named "new-country". Commit all the code changes to the new repository.
B. Add the code updates as a single commit when a feature is ready. Tag this commit with "new-country."
C. Add the code updates as commits to a feature branch. Merge the commits to a release branch as features are ready.
D. Add the code updates as commits to the release branch. The team can delay the deployment until all features are ready.

Answer: D

NEW QUESTION # 30
An application running on multiple Amazon EC2 instances pulls messages from a standard Amazon SQS queue. A requirement for the application is that all messages must be encrypted at rest.
Developers are instructed to use methods that allow for centralized key management and minimize possible support requirements whenever possible.
Which of the following solutions supports these requirements?

A. Encrypt individual messages by using SQS Extended Client and the Amazon S3 encryption client.
B. Create an SQS queue, and encrypt the queue by using server-side encryption with AWS KMS.
C. Encrypt individual messages by using client-side encryption with customer managed keys, then write to the SQS queue.
D. Create an SQS queue, and encrypt the queue by using client-side encryption.

Answer: B

NEW QUESTION # 31
A Developer is maintaining a fleet of 50 Amazon EC2 Linux servers. The servers are part of an Amazon EC2 Auto Scaling group, and also use Elastic Load Balancing for load balancing.
Occasionally, some application servers are being terminated after failing ELB HTTP health checks. The Developer would like to perform a root cause analysis on the issue, but before being able to access application logs, the server is terminated.
How can log collection be automated?

A. Use Auto Scaling lifecycle hooks to put instances in a Terminating:Wait state. Create an Amazon CloudWatch Events rule for EC2 'Instance-terminate Lifecycle Action and trigger an AWS Lambda function that executes a SSM Run Command script to collect logs, push them to Amazon S3, and complete the lifecycle action once logs are collected.
B. Use Auto Scaling lifecycle hooks to put instances in a Terminating: Wait state. Create an Amazon CloudWatch subscription filter for EC2 Instance Terminate Successful and trigger a CloudWatch agent that executes a script to called logs, push them to Amazon S3, and complete the lifecycle action once logs are collected.
C. Use Auto Scaling lifecycle hooks to put instances in a Terminating: Wait state. Create a Config rule for EC2 Instance-terminate Lifecycle Action and trigger a step function that executes a script to collect logs, push them to Amazon S3, and complete the lifecycle action once logs are collected.
D. Use Auto Scaling lifecycle hooks to put instances in a Pending:Wait state. Create an Amazon CloudWatch Alarm for EC2 Instance Terminate Successful and trigger an AWS Lambda function that executes an SSM Run Command script to collect logs, push them to Amazon S3, and complete the lifecycle action once logs are collected.

Answer: C

NEW QUESTION # 32
A retail company is currently hosting a Java-based application in its on-premises data center. Management wants the DevOps Engineer to move this application to AWS. Requirements state that while keeping high availability, infrastructure management should be as simple as possible. Also, during deployments of new application versions, while cost is an important metric, the Engineer needs to ensure that at least half of the fleet is available to handle user traffic.
What option requires the LEAST amount of management overhead to meet these requirements?

A. Create an AWS CodeDeploy deployment group and associate it with an Auto Scaling group configured to launch instances across subnets in different Availability Zones. Configure an in-place deployment with a custom deployment configuration with the MinimumHealthyHosts option set to type FLEET_PERCENT and a value of 50.
B. Create an AWS Elastic Beanstalk Java-based environment using Auto Scaling and load balancing.
Configure the network setting for the environment to launch instances across subnets in different Availability Zones. Use "Rolling with additional batch" as a deployment strategy with a batch size of
50%.
C. Create an AWS CodeDeploy deployment group and associate it with an Auto Scaling group configured to launch instances across subnets in different Availability Zones. Configure an in-place deployment with a CodeDeploy.HalfAtAtime configuration for application deployments.
D. Create an AWS Elastic Beanstalk Java-based environment using Auto Scaling and load balancing.
Configure the network options for the environment to launch instances across subnets in different Availability Zones. Use "Rolling" as a deployment strategy with a batch size of 50%.

Answer: D

Explanation:
Explanation
Rolling with batches keep 100% up yoiu need 50%. With rolling deployments, Elastic Beanstalk splits the environment's EC2 instances into batches and deploys the new version of the application to one batch at a time, leaving the rest of the instances in the environment running the old version of the application.
https://docs.aws.amazon.com/elasticbeanstalk/latest/dg/using-features.rolling-version-deploy.html

NEW QUESTION # 33
......

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