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Amazon DVA -C02 (AWS Certified Developer -Associate) 인증 시험은 AWS (Amazon Web Services) 플랫폼에서 애플리케이션을 개발하고 유지 관리하는 전문 지식을 시연하려는 개인을 위해 설계되었습니다. 이 시험은 AWS 기술을 사용하여 클라우드 기반 솔루션 설계, 개발 및 배포에 대한 최소 1 년의 경험을 가진 개발자를위한 것입니다.

최신 AWS Certified Associate DVA-C02 무료샘플문제 (Q110-Q115):

질문 # 110
A company needs to harden its container images before the images are in a running state. The company's application uses Amazon Elastic Container Registry (Amazon ECR) as an image registry. Amazon Elastic Kubernetes Service (Amazon EKS) for compute, and an AWS CodePipeline pipeline that orchestrates a continuous integration and continuous delivery (CI/CD) workflow.
Dynamic application security testing occurs in the final stage of the pipeline after a new image is deployed to a development namespace in the EKS cluster. A developer needs to place an analysis stage before this deployment to analyze the container image earlier in the CI/CD pipeline.
Which solution will meet these requirements with the MOST operational efficiency?

A. Add an action to the deployment stage of the pipeline so that the action occurs before the deployment to the EKS cluster. Configure ECR basic image scanning to scan on image push. Use an AWS Lambda function as the action provider. Configure the Lambda function to check the scan results and to fail the pipeline if there are findings.
B. Create a new CodePipeline stage that occurs after source code has been retrieved from its repository.
Run a security scanner on the latest revision of the source code. Fail the pipeline if there are findings.
C. Create a new CodePipeline stage that occurs after the container image is built. Configure ECR basic image scanning to scan on image push. Use an AWS Lambda function as the action provider. Configure the Lambda function to check the scan results and to fail the pipeline if there are findings.
D. Build the container image and run the docker scan command locally. Mitigate any findings before pushing changes to the source code repository. Write a pre-commit hook that enforces the use of this workflow before commit.

정답：C

설명：
Explanation
The solution that will meet the requirements with the most operational efficiency is to create a new CodePipeline stage that occurs after the container image is built. Configure ECR basic image scanning to scan on image push. Use an AWS Lambda function as the action provider. Configure the Lambda function to check the scan results and to fail the pipeline if there are findings. This way, the container image is analyzed earlier in the CI/CD pipeline and any vulnerabilities are detected and reported before deploying to the EKS cluster.
The other options either delay the analysis until after deployment, which increases the risk of exposing insecure images, or perform analysis on the source code instead of the container image, which may not capture all the dependencies and configurations that affect the security posture of the image.

질문 # 111
For a deployment using AWS Code Deploy, what is the run order of the hooks for in-place deployments?

A. ApplicationStop -> BeforeInstall -> AfterInstall -> ApplicationStart
B. BeforeInstall -> ApplicationStop -> ValidateService -> ApplicationStart
C. ApplicationStop -> BeforeInstall -> ValidateService -> ApplicationStart
D. BeforeInstall -> ApplicationStop -> ApplicationStart -> AfterInstall

정답：A

설명：
For in-place deployments, AWS CodeDeploy uses a set of predefined hooks that run in a specific order during each deployment lifecycle event. The hooks are ApplicationStop, BeforeInstall, AfterInstall, ApplicationStart, and ValidateService. The run order of the hooks for in-place deployments is as follows:
ApplicationStop: This hook runs first on all instances and stops the current application that is running on the instances.
BeforeInstall: This hook runs after ApplicationStop on all instances and performs any tasks required before installing the new application revision.
AfterInstall: This hook runs after BeforeInstall on all instances and performs any tasks required after installing the new application revision.
ApplicationStart: This hook runs after AfterInstall on all instances and starts the new application that has been installed on the instances.
ValidateService: This hook runs last on all instances and verifies that the new application is running properly on the instances.

질문 # 112
A company runs a payment application on Amazon EC2 instances behind an Application Load Balance. The EC2 instances run in an Auto Scaling group across multiple Availability Zones. The application needs to retrieve application secrets during the application startup and export the secrets as environment variables. These secrets must be encrypted at rest and need to be rotated every month.
Which solution will meet these requirements with the LEAST development effort?

A. Save the secrets as strings in AWS Systems Manager Parameter Store and use the default AWS Key Management Service (AWS KMS) key. Configure an Amazon EC2 user data script to retrieve the secrets during the startup and export as environment variables. Configure an AWS Lambda function to rotate the secrets in Parameter Store every month.
B. Store the secrets in AWS Secrets Manager. Provision a new customer master key. Use the key to encrypt the secrets. Enable automatic rotation. Configure an Amazon EC2 user data script to programmatically retrieve the secrets during the startup and export as environment variables.
C. Save the secrets in a text file and store the text file in Amazon S3. Provision a customer managed key. Use the key for secret encryption in Amazon S3. Read the contents of the text file and read the export as environment variables. Configure S3 Object Lambda to rotate the text file every month.
D. Save the secrets as base64 encoded environment variables in the application properties.
Retrieve the secrets during the application startup. Reference the secrets in the application code.
Write a script to rotate the secrets saved as environment variables.

정답：B

질문 # 113
A company runs a web application on Amazon EC2 instances behind an Application Load Balancer. The application uses Amazon DynamoDB as its database. The company wants to ensure high performance for reads and writes.
Which solution will meet these requirements MOST cost-effectively?

A. Use DynamoDB on-demand capacity mode for the table. Specify a maximum throughput higher than the expected peak read and write capacity units.
B. Create an Amazon DynamoDB Accelerator (DAX) cluster. Configure the application to use the DAX endpoint.
C. Configure auto-scaling for the DynamoDB table with a target utilization of 70%. Set the minimum and maximum capacity units based on the expected workload.
D. Use DynamoDB provisioned throughput mode for the table. Create an Amazon CloudWatch alarm on the ThrottledRequests metric. Invoke an AWS Lambda function to increase provisioned capacity.

정답：C

설명：
Comprehensive Detailed Explanation with all AWS Reference
Why Option A is Correct:
Auto-scaling with a target utilization ensures the DynamoDB table dynamically adjusts capacity based on workload, maintaining high performance while optimizing cost. Setting a reasonable target utilization minimizes overprovisioning and throttling risks.
Why Other Options are Incorrect:
Option B: On-demand capacity is costlier than provisioned throughput for predictable workloads.
Option C: Using manual CloudWatch alarms and Lambda for scaling is less efficient and adds operational overhead.
Option D: DAX accelerates read performance but does not improve write performance.
AWS Documentation Reference:
DynamoDB Auto Scaling

질문 # 114
An engineer created an A/B test of a new feature on an Amazon CloudWatch Evidently project.
The engineer configured two variations of the feature (Variation A and Variation B) for the test.
The engineer wants to work exclusively with Variation A. The engineer needs to make updates so that Variation A is the only variation that appears when the engineer hits the application's endpoint.
Which solution will meet this requirement?

A. Add an experiment to the project. Set the identifier of the experiment to Variation B. Set the variation to 0%.
B. Add an override to the feature. Set the identifier of the override to the engineer's user ID. Set the variation to Variation A.
C. Add an override to the feature. Set the identifier of the override to Variation A. Set the variation to
100%.
D. Add an experiment to the project. Set the identifier of the experiment to the AWS account's account ISet the variation to Variation A.

정답：B

설명：
Overrides let you pre-define the variation for selected users. to always receive the editable variation.
https://aws.amazon.com/blogs/aws/cloudwatch-evidently/

질문 # 115
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