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DVA-C02試験は、AWS開発に関連する広範なトピックをカバーしており、EC2、S3、RDSなどのAWSコアサービス、AWS CodeDeploy、AWS CodePipeline、AWS CloudFormationなどのAWS開発者向けツールも含まれます。さらに、この試験では、Python、Java、Node.jsなどのAWS開発で一般的に使用されるプログラミング言語の知識もテストされます。

Amazon DVA-C02試験は、Amazon Web Services（AWS）が提供するAWS Certified Developer-Associate認定試験です。AWSベースのアプリケーションの開発と維持の経験を持つ個人を対象としています。この試験は、AWSのサービスやツールを使用してクラウドベースのアプリケーションを設計、開発、展開する能力を受験者が持っているかどうかを検証します。この認定は、AWS開発者としてのキャリアを進め、クラウドベースのアプリケーションを構築することに熟練することを望む人々を対象としています。

>> DVA-C02日本語解説集 <<

DVA-C02認証pdf資料、DVA-C02試験概要

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Amazon DVA-C02 認定試験は、コンピューティング、ストレージ、データベース、ネットワーキング、セキュリティ、デプロイメントなど、AWSサービスに関連する幅広いトピックをカバーしています。この試験は、選択式の問題で構成されており、候補者のAWSサービス、ベストプラクティス、アーキテクチャパターンの理解をテストするために設計されています。

Amazon AWS Certified Developer - Associate 認定 DVA-C02 試験問題 (Q18-Q23):

質問 # 18
A developer is using AWS CodeDeploy to automate a company's application deployments to Amazon EC2.
Which application specification file properties are required to ensure the software deployments do not fail? (Select TWO.)

A. The file must be stored in Amazon S3 and referenced from the application's source code.
B. The file must be placed in the root of the directory structure of the application's source code.
C. The file must be stored in AWS CodeBuild and referenced from the application's source code.
D. The file must be a JSON-formatted file named appspec.json.
E. The file must be a YAML-formatted file named appspec.yml.

正解：B、E

解説：
Comprehensive and Detailed Step-by-Step
To ensure successful software deployments using AWS CodeDeploy, the application specification file (appspec.yml or appspec.json) must adhere to specific requirements:
File Format Requirement (Option B):
The appspec.yml file is a YAML-formatted file required for defining deployment actions and file locations. This is the modern and recommended format for application specification files.
It can also be a JSON-formatted file named appspec.json, but YAML is most commonly used and accepted.
File Placement Requirement (Option D):
The application specification file must reside in the root directory of the application's source code. This is necessary so that AWS CodeDeploy can detect and use the file during deployment.
Incorrect Options:
Option A: While a JSON-formatted file (appspec.json) is valid, this is not a mandatory requirement. YAML is also acceptable, and this option does not account for it.
Option C: The application specification file is not required to be stored in AWS CodeBuild; it must be included in the source code's directory structure.
Option E: The application specification file does not need to be stored in Amazon S3. S3 is commonly used for application artifacts, but the appspec.yml or appspec.json file must exist within the deployment package or source code root.
Reference:
AWS CodeDeploy User Guide: Application Specification File

質問 # 19
A developer is preparing to begin development of a new version of an application. The previous version of the application is deployed in a production environment. The developer needs to deploy fixes and updates to the current version during the development of the new version of the application. The code for the new version of the application is stored in AWS CodeCommit.
Which solution will meet these requirements?

A. Create a Git tag of the code that is currently deployed in production. Create a Git tag for the development of the new version. Push the two tags to the CodeCommit repository.
B. From the main branch, create a branch of the code that is currently deployed in production. Apply an IAM policy that ensures no other other users can push or merge to the branch.
C. Create a new CodeCommit repository for development of the new version of the application. Create a Git tag for the development of the new version.
D. From the main branch, create a feature branch for production bug fixes. Create a second feature branch from the main branch for development of the new version.

正解：D

解説：
A feature branch is a branch that is created from the main branch to work on a specific feature or task1. Feature branches allow developers to isolate their work from the main branch and avoid conflicts with other changes1. Feature branches can be merged back to the main branch when the feature or task is completed and tested1.
In this scenario, the developer needs to maintain two parallel streams of work: one for fixing and updating the current version of the application that is deployed in production, and another for developing the new version of the application. The developer can use feature branches to achieve this goal.
The developer can create a feature branch from the main branch for production bug fixes. This branch will contain the code that is currently deployed in production, and any fixes or updates that need to be applied to it. The developer can push this branch to the CodeCommit repository and use it to deploy changes to the production environment.
The developer can also create a second feature branch from the main branch for development of the new version of the application. This branch will contain the code that is under development for the new version, and any changes or enhancements that are part of it. The developer can push this branch to the CodeCommit repository and use it to test and deploy the new version of the application in a separate environment.
By using feature branches, the developer can keep the main branch stable and clean, and avoid mixing code from different versions of the application. The developer can also easily switch between branches and merge them when needed.

質問 # 20
A company hosts a stateless web application with low data storage in a single AWS Region. The company wants to increase the resiliency of the application to include a multi-Region presence.
The company wants to set the recovery time objective (RTO) and recovery point objective (RPO) to hours. The company needs a low-cost and low-complexity disaster recovery (DR) strategy.
Which DR strategy should the company use?

A. Pilot light
B. Multi-site active-active
C. Warm standby
D. Backup and restore

正解：A

解説：
The pilot light strategy keeps a minimal version of the environment in another Region and scales up during a disaster. It achieves an RTO and RPO of hours at a low cost and complexity.

質問 # 21
A developer is automating a new application deployment with AWS SAM. The new application has one AWS Lambda function and one Amazon S3 bucket. The Lambda function must access the S3 bucket to only read objects.
How should the developer configure AWS SAM to grant the necessary read permission to the S3 bucket?

A. Reference a second Lambda authorizer function.
B. Create an Amazon SQS topic for only S3 object reads. Reference the topic in the template.
C. Add the S3ReadPolicy template to the Lambda function's execution role.
D. Add a custom S3 bucket policy to the Lambda function.

正解：C

解説：
Step-by-Step Breakdown:
Requirement Summary:
* UseAWS SAMto deploy:
* 1 Lambda Function
* 1 S3 Bucket
* Lambda needsread-only accessto the S3 bucket
* Solution must be expressed viaAWS SAM template
Option A: Reference a second Lambda authorizer function
* #Incorrect: Lambda authorizers are used inAPI Gateway for authentication, not for granting S3 permissions.
Option B: Add a custom S3 bucket policy to the Lambda function
* #Incorrect: Bucket policiescontrol who can access the bucket, not what the Lambda function can do.
* The permission must be granted to the Lambda'sIAM execution role.
Option C: Create an Amazon SQS topic for only S3 object reads
* #Incorrect: SQS cannot read objects from S3 and is not relevant to this scenario.
Option D: Add the S3ReadPolicy template to the Lambda function's execution role
* #Correct: AWS SAM providesmanaged policy templateslike AmazonS3ReadOnlyAccess and shortcuts like S3ReadPolicy.
* You can apply these to the Lambda's execution role using the Policies: section in your SAM template.
Example SAM YAML:
yaml
CopyEdit
Resources:
MyFunction:
Type: AWS::Serverless::Function
Properties:
CodeUri: my-code/
Handler: app.handler
Runtime: python3.11
Policies:
- S3ReadPolicy:
BucketName: !Ref MyBucket
MyBucket:
Type: AWS::S3::Bucket
Properties:
BucketName: my-personal-bucket-name
* SAM Policy Templates:https://docs.aws.amazon.com/serverless-application-model/latest
/developerguide/serverless-policy-templates.html
* Example using S3ReadPolicy:https://docs.aws.amazon.com/serverless-application-model/latest
/developerguide/serverless-policy-templates.html#s3-readpolicy

質問 # 22
A developer must use multi-factor authentication (MFA) to access data in an Amazon S3 bucket that is in another AWS account. Which AWS Security Token Service (AWS STS) API operation should the developer use with the MFA information to meet this requirement?

A. AssumeRoleWithSAML
B. AssumeRole
C. AssumeRoleWithWebidentity
D. GetFederationToken

正解：B

解説：
* AWS STS AssumeRole: The central operation for assuming temporary security credentials, commonly used for cross-account access.
* MFA Integration: The AssumeRole call can include MFA information to enforce multi-factor authentication.
* Credentials for S3 Access: The returned temporary credentials would provide the necessary permissions to access the S3 bucket in the other account.
References:
* AWS STS AssumeRole Documentation: https://docs.aws.amazon.com/STS/latest/APIReference
/API_AssumeRole.html

質問 # 23
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