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Amazon DOP-C02 is an advanced level certification exam offered by Amazon Web Services (AWS) for IT professionals who want to enhance their expertise in DevOps practices and technologies. AWS Certified DevOps Engineer - Professional certification is intended for individuals who have extensive experience with AWS services and have a thorough understanding of DevOps principles and practices. Passing DOP-C02 Exam validates the candidate's ability to design, deploy, and manage AWS services and infrastructure using DevOps methodologies.

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Amazon DOP-C02 is an exam that is designed to test the knowledge and skills of individuals seeking to become certified AWS Certified DevOps Engineers - Professionals. AWS Certified DevOps Engineer - Professional certification is awarded by Amazon Web Services (AWS), a cloud computing platform that offers a wide range of services and tools for developing, deploying, and managing applications.

The DOP-C02 Certification Exam is intended for professionals who have already achieved the AWS Certified Developer - Associate or AWS Certified SysOps Administrator - Associate certification. To be eligible for the exam, candidates must have at least two years of experience in deploying and managing AWS-based applications using DevOps practices.

Amazon AWS Certified DevOps Engineer - Professional Sample Questions (Q134-Q139):

NEW QUESTION # 134
A DevOps engineer manages an AWS CodePipeline pipeline that builds and deploys a web application on AWS. The pipeline has a source stage, a build stage, and a deploy stage. When deployed properly, the web application responds with a 200 OK HTTP response code when the URL of the home page is requested.
The home page recently returned a 503 HTTP response code after CodePipeline deployed the application. The DevOps engineer needs to add an automated test into the pipeline. The automated test must ensure that the application returns a 200 OK HTTP response code after the application is deployed. The pipeline must fail if the response code is not present during the test.
The DevOps engineer has added a CheckURL stage after the deploy stage in the pipeline.
What should the DevOps engineer do next to implement the automated test?

A. Configure the CheckURL stage to use an Amazon CloudWatch action. Configure the action to use a canary synthetic monitoring check on the application URL and to report a success or failure to CodePipeline.
B. Deploy an Amazon API Gateway HTTP API that checks the response code status of the URL and that reports success or failure to CodePipeline. Configure the CheckURL stage to use the AWS Device Farm test action and to provide the API Gateway HTTP API as an input artifact.
C. Create an AWS Lambda function to check the response code status of the URL and to report a success or failure to CodePipeline. Configure an action in the CheckURL stage to invoke the Lambda function.
D. Configure the CheckURL stage to use an AWS CodeDeploy action. Configure the action with an input artifact that is the URL of the application and to report a success or failure to CodePipeline.

Answer: C

Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
To add an automated test in AWS CodePipeline that checks the HTTP response code of a deployed application, the most straightforward and operationally efficient method is to create an AWS Lambda function that makes an HTTP request to the application URL, checks the response code, and then reports success or failure back to CodePipeline.
* The Lambda function can be invoked as an action in the pipeline stage.
* If the response code is not 200 OK, the Lambda function can return a failure, causing the pipeline stage to fail and halt further execution.
* Option A's CloudWatch synthetic canary monitors are useful for ongoing monitoring but are not natively integrated as CodePipeline actions to control pipeline flow.
* Option C incorrectly uses CodeDeploy action for testing, which is not designed for this purpose.
* Option D introduces unnecessary complexity by deploying API Gateway and Device Farm, which is not required for a simple HTTP status check.Therefore, option B provides a clean, simple, and fully automated way to enforce HTTP response validation within the pipeline.
Reference from AWS Official Documentation:
* AWS CodePipeline Custom Actions:"You can create Lambda invoke actions in your pipeline stages to run custom validation or testing functions."(AWS CodePipeline User Guide - Lambda Actions)
* AWS Lambda Function for Health Checks:"Lambda functions can be used to perform health checks or API response validations and report results back to invoking services."(AWS Lambda Developer Guide)

NEW QUESTION # 135
A highly regulated company has a policy that DevOps engineers should not log in to their Amazon EC2 instances except in emergencies. It a DevOps engineer does log in the security team must be notified within 15 minutes of the occurrence.
Which solution will meet these requirements'?

A. Set up a script on each Amazon EC2 instance to push all logs to Amazon S3 Set up an S3 event to invoke an AWS Lambda function which invokes an Amazon Athena query to run. The Athena query checks tor logins and sends the output to the security team using Amazon SNS.
B. Install the Amazon CloudWatch agent on each EC2 instance Configure the agent to push all logs to Amazon CloudWatch Logs and set up a CloudWatch metric filter that searches for user logins. If a login is found send a notification to the security team using Amazon SNS.
C. Set up AWS CloudTrail with Amazon CloudWatch Logs. Subscribe CloudWatch Logs to Amazon Kinesis Attach AWS Lambda to Kinesis to parse and determine if a log contains a user login If it does, send a notification to the security team using Amazon SNS.
D. Install the Amazon Inspector agent on each EC2 instance Subscribe to Amazon EventBridge notifications Invoke an AWS Lambda function to check if a message is about user logins If it is send a notification to the security team using Amazon SNS.

Answer: B

Explanation:
https://aws.amazon.com/blogs/security/how-to-monitor-and-visualize-failed-ssh-access-attempts-to-amazon-ec2-linux-instances/

NEW QUESTION # 136
A business has an application that consists of five independent AWS Lambda functions.
The DevOps engineer has built a CI/CD pipeline using AWS CodePipeline and AWS CodeBuild that builds tests packages and deploys each Lambda function in sequence. The pipeline uses an Amazon EventBridge rule to ensure the pipeline starts as quickly as possible after a change is made to the application source code.
After working with the pipeline for a few months the DevOps engineer has noticed the pipeline takes too long to complete.
What should the DevOps engineer implement to BEST improve the speed of the pipeline?

A. Create a custom CodeBuild execution environment that includes a symmetric multiprocessing configuration to run the builds in parallel.
B. Modify each CodeBuild protect to run within a VPC and use dedicated instances to increase throughput.
C. Modify the CodeBuild projects within the pipeline to use a compute type with more available network throughput.
D. Modify the CodePipeline configuration to run actions for each Lambda function in parallel by specifying the same runorder.

Answer: D

Explanation:
https://docs.aws.amazon.com/codepipeline/latest/userguide/reference-pipeline-structure.html AWS doc: "To specify parallel actions, use the same integer for each action you want to run in parallel. For example, if you want three actions to run in sequence in a stage, you would give the first action the runOrder value of 1, the second action the runOrder value of 2, and the third the runOrder value of 3. However, if you want the second and third actions to run in parallel, you would give the first action the runOrder value of 1 and both the second and third actions the runOrder value of 2."

NEW QUESTION # 137
A company is running an application on Amazon Elastic Kubernetes Service (Amazon EKS). The company needs to implement comprehensive logging for the control plane and the nodes. The company must analyze API requests to the Kubernetes control plane and must monitor container performance on the nodes.
Which solution will meet these requirements with the LEAST operational overhead?

A. Enable control plane logging for the EKS cluster. Send the logs to Amazon CloudWatch. Use CloudWatch Container Insights to collect logs for the nodes and the containers. Use CloudWatch Logs Insights to query and analyze the logs for the control plane and the nodes.
B. Enable AWS CloudTrail for control plane logging. Deploy Logstash as a ReplicaSet on the nodes to collect logs from the nodes. Use Amazon OpenSearch to store and analyze the logs for the control plane and the nodes.
C. Enable API server control plane logging for the EKS cluster. Send the logs to Amazon S3. Deploy Kubernetes Event Exporter to the nodes to collect logs from the nodes. Send the logs to Amazon S3.
Use Amazon Athena to query logs for the control plane and the nodes. Use Amazon QuickSight for visualization.
D. Use AWS Distro for OpenTelemetry to collect logs for the control plane and the nodes. Stream all the logs to Amazon Data Firehose. Use Amazon Redshift to analyze the aggregated log data for the control plane and the nodes.

Answer: A

Explanation:
Comprehensive and Detailed Explanation From Exact Extract of DevOps Engineer documents only:
The requirement is to log and analyze Kubernetes control plane activity, including API requests, and to monitor container performance on the worker nodes with the least operational overhead.
Option B is correct because:
* Amazon EKS control plane logging can send control plane logs, including API server logs, to Amazon CloudWatch.
* CloudWatch Container Insights provides monitoring and performance visibility for containers, pods, nodes, and clusters.
* CloudWatch Logs Insights can be used to query and analyze both control plane and node-related logs.
* This is the most managed and lowest-overhead solution among the options.
Why the other options are incorrect:
A). CloudTrail is not the primary solution for Kubernetes control plane logs such as API server logs, and deploying Logstash increases operational overhead significantly.
C). Sending logs to Amazon S3 and analyzing them with Athena and QuickSight is more operationally complex and less direct than using native CloudWatch integrations.
D). AWS Distro for OpenTelemetry with Firehose and Redshift adds substantial complexity and operational overhead compared to native EKS and CloudWatch capabilities.

NEW QUESTION # 138
A DevOps engineer is building a multistage pipeline with AWS CodePipeline to build, verify, stage, test, and deploy an application. A manual approval stage is required between the test stage and the deploy stage. The development team uses a custom chat tool with webhook support that requires near-real-time notifications.
How should the DevOps engineer configure status updates for pipeline activity and approval requests to post to the chat tool?

A. Modify the pipeline code to send the event details to the chat webhook URL at the end of each stage. Parameterize the URL so that each pipeline can send to a different URL based on the pipeline environment.
B. Create an Amazon CloudWatch Logs subscription that filters on CodePipeline Pipeline Execution State Change. Publish subscription events to an Amazon Simple Notification Service (Amazon SNS) topic. Subscribe the chat webhook URL to the SNS topic, and complete the subscription validation.
C. Create an Amazon EventBridge rule that filters on CodePipeline Pipeline Execution State Change. Publish the events to an Amazon Simple Notification Service (Amazon SNS) topic. Create an AWS Lambda function that sends event details to the chat webhook URL. Subscribe the function to the SNS topic.
D. Create an AWS Lambda function that is invoked by AWS CloudTrail events. When a CodePipeline Pipeline Execution State Change event is detected, send the event details to the chat webhook URL.

Answer: C

Explanation:
https://aws.amazon.com/premiumsupport/knowledge-center/sns-lambda-webhooks-chime-slack-teams/

NEW QUESTION # 139
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