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Amazon DOP-C02 Exam Overview:

Certification Vendor:	Amazon AWS
Exam Name:	AWS Certified DevOps Engineer - Professional
Exam Number:	DOP-C02
Passing Score:	750 (scaled score 100–1000)
Real Exam Qty:	75 (65 scored, 10 unscored)
Available Languages:	Japanese, Korean, Simplified Chinese, Traditional Chinese, English
Certificate Validity Period:	3 years
Exam Duration:	180 minutes
Exam Price:	300 USD
Exam Format:	Multiple response, Multiple choice
Related Certifications:	AWS Certified SysOps Administrator - Associate AWS Certified Developer - Associate
Recommended Training:	AWS Training and Certification AWS Certified DevOps Engineer - Professional Exam Guide
Exam Registration:	Pearson VUE Registration AWS Certification Registration
Sample Questions:	Amazon DOP-C02 Sample Questions
Exam Way:	Online proctored or onsite at testing centers
Pre Condition:	Recommended: AWS Certified Developer - Associate or AWS Certified SysOps Administrator - Associate, plus 2+ years of hands-on experience provisioning, operating, and managing AWS environments
Official Syllabus URL:	https://docs.aws.amazon.com/aws-certification/latest/devops-engineer-professional-02/devops-engineer-professional-02.html

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Amazon DOP-C02 certification exam is comprised of 75 multiple-choice and multiple-response questions, and the allotted time to complete the exam is 180 minutes. DOP-C02 exam fee is $300, and the test is available in English, Japanese, Korean, and Simplified Chinese. DOP-C02 Exam is administered at a testing center or online, depending on the candidate's preference.

Amazon AWS Certified DevOps Engineer - Professional Sample Questions (Q335-Q340):

NEW QUESTION # 335
A DevOps engineer needs to implement integration tests into an existing AWS CodePipelme CI/CD workflow for an Amazon Elastic Container Service (Amazon ECS) service. The CI/CD workflow retrieves new application code from an AWS CodeCommit repository and builds a container image. The CI/CD workflow then uploads the container image to Amazon Elastic Container Registry (Amazon ECR) with a new image tag version.
The integration tests must ensure that new versions of the service endpoint are reachable and that vanous API methods return successful response data The DevOps engineer has already created an ECS cluster to test the service Which combination of steps will meet these requirements with the LEAST management overhead? (Select THREE.)

A. Add a deploy stage to the pipeline Configure AWS CodeDeploy as the action provider
B. Add an appspec.yml file to the CodeCommit repository
C. Create an AWS Lambda function that runs connectivity checks and API calls against the service.
Integrate the Lambda function with CodePipeline by using aLambda action stage
D. Update the image build pipeline stage to output an imagedefinitions json file that references the new image tag.
E. Add a deploy stage to the pipeline Configure Amazon ECS as the action provider
F. Write a script that runs integration tests against the service. Upload the script to an Amazon S3 bucket.
Integrate the script in the S3 bucket with CodePipeline by using an S3 action stage.

Answer: C,D,E

Explanation:
Add a Deploy Stage to the Pipeline, Configure Amazon ECS as the Action Provider:
By adding a deploy stage to the pipeline and configuring Amazon ECS as the action provider, the pipeline can automatically deploy the new container image to the ECS cluster.
This ensures that the service is updated with the new image tag, making the new version of the service endpoint reachable.
Reference: AWS CodePipeline with ECS
Update the Image Build Pipeline Stage to Output an imagedefinitions.json File that References the New Image Tag:
The imagedefinitions.json file provides the necessary information about the container images and their tags for the ECS task definitions.
Updating the pipeline to output this file ensures that the correct image version is deployed.
Example imagedefinitions.json
[
{
"name": "container-name",
"imageUri": "123456789012.dkr.ecr.region.amazonaws.com/my-repo:my-tag"
}
]
Reference: CodePipeline ECS Deployment
Create an AWS Lambda Function that Runs Connectivity Checks and API Calls against the Service.
Integrate the Lambda Function with CodePipeline by Using a Lambda Action Stage:
The Lambda function can perform the necessary integration tests by making connectivity checks and API calls to the deployed service endpoint.
Integrating this Lambda function into CodePipeline ensures that these tests are run automatically after deployment, providing near-real-time feedback on the new deployment's health.
Example Lambda function integration:
actions:
- name: TestService
actionTypeId:
category: Test
owner: AWS
provider: Lambda
version: 1
runOrder: 2
configuration:
FunctionName: testServiceFunction
Reference: Integrating Lambda with CodePipeline
These steps ensure that the CI/CD workflow deploys the new container image to ECS, updates the image references, and performs integration tests, meeting the requirements with minimal management overhead.

NEW QUESTION # 336
A company deploys updates to its Amazon API Gateway API several times a week by using an AWS CodePipeline pipeline. As part of the update process the company exports the JavaScript SDK for the API from the API. Gateway console and uploads the SDK to an Amazon S3 bucket The company has configured an Amazon CloudFront distribution that uses the S3 bucket as an origin Web client then download the SDK by using the CloudFront distribution's endpoint. A DevOps engineer needs to implement a solution to make the new SDK available automatically during new API deployments.
Which solution will meet these requirements?

A. Create an Amazon EventBridge rule that reacts to Create. Deployment events from aws apigateway.Configure the rule to invoke an AWS Lambda function to download the SDK from API. Gateway upload the SDK to the S3 bucket and call the S3 API to invalidate the cache for the SDK path.
B. Create an Amazon EventBridge rule that reacts to UpdateStage events from aws apigateway Configure the rule to invoke an AWS Lambda function to download the SDK from API Gateway upload the SDK to the S3 bucket and call the CloudFront API to create an invalidation for the SDK path.
C. Create a CodePipeline action immediately after the deployment stage of the API Configure the action to use the CodePipelme integration with API. Gateway to export the SDK to Amazon S3 Create another action that uses the CodePipeline integration with Amazon S3 to invalidate the cache for the SDK path.
D. Create a CodePipeline action immediately after the deployment stage of the API. Configure the action to invoke an AWS Lambda function. Configure the Lambda function to download the SDK from API Gateway, upload the SDK to the S3 bucket and create a CloudFront invalidation for the SDK path.

Answer: D

Explanation:
Explanation
This solution would allow the company to automate the process of updating the SDK and making it available to web clients. By adding a CodePipeline action immediately after the deployment stage of the API, the Lambda function will be invoked automatically each time the API is updated. The Lambda function should be able to download the new SDK from API Gateway, upload it to the S3 bucket and also create a CloudFront invalidation for the SDK path so that the latest version of the SDK is available for the web clients. This is the most straight forward solution and it will meet the requirements.

NEW QUESTION # 337
A company has a web application that is hosted on Amazon EC2 instances. The company is deploying the application into multiple AWS Regions. The application consists of dynamic content such as WebSocket-based real-time product updates. The company uses Amazon Route 53 to manage all DNS records. Which solution will provide multi-Region access to the application with the LEAST latency?

A. Deploy a Network Load Balancer (NLB) in front of the EC2 instances in each Region. Deploy an AWS Global Accelerator standard accelerator with an endpoint group for each NLB. Create a Route 53 alias record that points to the accelerator's DNS address.
B. Deploy a Network Load Balancer (NLB) in front of the EC2 instances in each Region. Create a Route 53 A record with a multivalue answer routing policy. Add IP addresses of the NLBs as the value of the record.
C. Deploy an Application Load Balancer (ALB) in front of the EC2 instances in each Region. Create a Route 53 A record with a latency-based routing policy. Add IP addresses of the ALBs as the value of the record.
D. Deploy an Application Load Balancer (ALB) in front of the EC2 instances in each Region. Deploy an Amazon CloudFront distribution with an origin group that contains the ALBs as origins. Create a Route 53 alias record that points to the CloudFront distribution's DNS address.

Answer: C

NEW QUESTION # 338
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. 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.
D. 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.

Answer: C

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 # 339
A company is launching an application that stores raw data in an Amazon S3 bucket. Three applications need to access the data to generate reports. The data must be redacted differently for each application before the applications can access the data.
Which solution will meet these requirements?

A. Create an S3 bucket for each application. Configure S3 Same-Region Replication (SRR) from the raw data's S3 bucket to each application's S3 bucket. Configure each application to consume data from its own S3 bucket.
B. Create an S3 access point that uses the raw data's S3 bucket as the destination. For each application, create an S3 Object Lambda access point that uses the S3 access point. Configure the AWS Lambda function for each S3 Object Lambda access point to redact data when objects are retrieved. Configure each application to consume data from its own S3 Object Lambda access point.
C. Create an Amazon Kinesis data stream. Create an AWS Lambda function that is invoked by object creation events in the raw data's S3 bucket. Program the Lambda function to redact data for each application. Publish the data on the Kinesis data stream. Configure each application to consume data from the Kinesis data stream.
D. For each application, create an S3 access point that uses the raw data's S3 bucket as the destination.
Create an AWS Lambda function that is invoked by object creation events in the raw data's S3 bucket.
Program the Lambda function to redact data for each application. Store the data in each application's S3 access point. Configure each application to consume data from its own S3 access point.

Answer: B

Explanation:
Explanation
The best solution is to use S3 Object Lambda1, which allows you to add your own code to S3 GET, LIST, and HEAD requests to modify and process data as it is returned to an application2. This way, you can redact the data differently for each application without creating and storing multiple copies of the data or running proxies.
The other solutions are less efficient or scalable because they require replicating the data to multiple buckets, streaming the data through Kinesis, or storing the data in S3 access points.
References: 1: Amazon S3 Features | Object Lambda | AWS 2: Transforming objects with S3 Object Lambda - Amazon Simple Storage Service

NEW QUESTION # 340
......

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