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Amazon DVA-C02 Exam Syllabus Topics:

SectionWeightObjectives
Development with AWS Services32%- Use data stores in application development
  • 1. Amazon RDS
  • 2. Amazon DynamoDB
  • 3. Amazon S3
  • 4. Amazon ElastiCache
  • 5. Amazon EFS
- Develop code for applications hosted on AWS
  • 1. Amazon DynamoDB
  • 2. Amazon S3
  • 3. AWS CloudFormation
  • 4. Amazon SQS
  • 5. Amazon API Gateway
  • 6. AWS Lambda
  • 7. AWS CLI
  • 8. Amazon SNS
  • 9. Amazon Cognito
  • 10. AWS SDKs
- Develop code for AWS serverless applications
  • 1. Amazon EventBridge
  • 2. Amazon API Gateway
  • 3. AWS AppSync
  • 4. AWS Step Functions
Security26%- Implement encryption by using AWS services
  • 1. Amazon S3 encryption
  • 2. AWS CloudHSM
  • 3. AWS Certificate Manager
  • 4. AWS Secrets Manager
  • 5. AWS KMS
- Implement authentication and/or authorization for applications and AWS services
  • 1. Resource-based policies, service policies, and principal policies
  • 2. User pools and identity pools in Amazon Cognito
  • 3. Role-based access control (RBAC)
  • 4. Bearer tokens (JWT, OAuth, AWS STS)
  • 5. Identity federation (SAML, OpenID Connect, Amazon Cognito)
- Manage sensitive data in application code
  • 1. Environment variables
  • 2. AWS Secrets Manager
  • 3. AWS Systems Manager Parameter Store
  • 4. Encryption of data at rest and in transit
Troubleshooting and Optimization18%- Optimize applications by using AWS services and features
  • 1. Data storage optimization
  • 2. Memory and compute optimization
  • 3. Concurrency and throttling
  • 4. Cost optimization
  • 5. Caching strategies (ElastiCache, CloudFront)
- Instrument code for observability
  • 1. AWS X-Ray
  • 2. Amazon CloudWatch metrics
  • 3. Structured logging
  • 4. Amazon CloudWatch alarms
  • 5. Custom metrics
- Assist in a root cause analysis
  • 1. AWS X-Ray
  • 2. Application logging
  • 3. Error handling and retries
  • 4. Amazon CloudWatch Logs
  • 5. AWS CloudTrail
Deployment24%- Test applications in development environments
  • 1. Mocking AWS services
  • 2. Local testing of Lambda functions
  • 3. AWS SAM local
- Deploy code by using AWS CI/CD services
  • 1. AWS CodeCommit
  • 2. AWS CodeBuild
  • 3. Canary deployments
  • 4. AWS CodePipeline
  • 5. Rolling deployments
  • 6. Blue/green deployments
  • 7. GitHub integration
  • 8. AWS CodeDeploy
- Automate deployment testing
  • 1. AWS CodeCommit
  • 2. AWS CodeBuild
  • 3. AWS CodePipeline
  • 4. AWS CodeDeploy
- Prepare application artifacts to be deployed to AWS
  • 1. AWS SAM
  • 2. AWS CloudFormation
  • 3. Lambda deployment packages
  • 4. AWS CDK
  • 5. Docker containers

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Amazon AWS Certified Developer - Associate Sample Questions (Q453-Q458):

NEW QUESTION # 453
A financial services company builds a credit card transaction processing application that uses an Amazon API Gateway HTTP API and AWS Lambda functions. The application logs all requests and request parameters to Amazon CloudWatch. The application makes the logs accessible to developer AWS accounts and a separate fraud detection AWS account by using a cross-account IAM role.
The company requires that only the fraud detection account be able to view customer credit card numbers that are associated with the transactions. Developers at the company must not be able to use the credit card numbers for testing or debugging.
The developers create the following data protection policy document snippet:
{
"Name": "data-protection-policy",
"Description": "Credit card redaction",
"Version": "2021-06-01",
"Statement": [{
"Sid": "redact-policy",
"DataIdentifier": [
"arn:aws:dataprotection::aws:data-identifier/CreditCardNumber"
],
"Operation": {
"Deidentify": {
"MaskConfig": {}
}
}
}]
}
Which combination of actions must the developers take to comply with the new policy? (Select TWO.)

Answer: A,C

Explanation:
To meet the requirement that developers cannot view credit card numbers while the fraud detection account can, the solution must (1) ensure the sensitive data is masked at ingestion/storage in CloudWatch Logs, and (2) allow only an authorized principal to view unmasked values.
First, the developers must attach the data protection policy to the CloudWatch log group that receives the API Gateway HTTP API access logs (and/or the Lambda log group if credit card numbers can appear there).
A CloudWatch Logs data protection policy is applied at the log group level and instructs CloudWatch Logs to identify sensitive data using managed data identifiers (for example, CreditCardNumber) and then apply the configured de-identification action (here, masking). Without attaching the policy to the log group, the masking/redaction behavior will not be enforced for newly ingested log events, and developers could still see raw request parameters.
Second, to permit only the fraud detection account to reveal the masked values when necessary, the IAM role that the fraud detection account assumes must have the specific CloudWatch Logs permission to unmask protected data. Granting logs:Unmask to that role enables authorized access to view the sensitive values while keeping them masked for everyone else who lacks that permission (such as developer accounts assuming other roles).
Options A and E are not required for CloudWatch Logs data protection enforcement; the core controls are log- group policy attachment (to perform masking) and IAM authorization (to permit unmasking only for the fraud role). Therefore, the correct combination is C (apply the policy to the log group that captures the HTTP API logs) and B (grant logs:Unmask to the fraud detection role).


NEW QUESTION # 454
A company has developed an application that uses AWS Lambda functions to process messages from an Amazon SQS queue. One of the Lambda functions makes a call to an external API that is expected to encounter temporary service unavailability.
A developer needs to configure the function to retry failed messages from an Amazon SQS dead-letter queue.
The developer notices that the Lambda function is re-processing some messages in the queue more than once.
Which solution will resolve this issue?

Answer: D

Explanation:
Comprehensive Detailed Explanation with all AWS References
* Why Option B is Correct:Setting the visibility timeout ensures that once a message is being processed, it is temporarily hidden from other consumers. The Lambda function must delete processed messages to avoid re-processing when the visibility timeout expires.
* Why Other Options are Incorrect:
* Option A: Message retention affects how long messages stay in the queue, not how they are processed.
* Option C: Receive message wait time optimizes long polling but does not prevent re-processing.
* Option D: Delivery delay introduces latency for new messages and does not address message re- processing.
* AWS Documentation References:
* Using SQS Visibility Timeout


NEW QUESTION # 455
A development team is creating a serverless application that uses AWS Lambda functions. The team wants to streamline a testing workflow by sharing test events across multiple developers within the same AWS account. The team wants to ensure all developers can use consistent test events without compromising security.

Answer: A

Explanation:
Comprehensive and Detailed Step-by-Step Explanation:
Option A: Use Amazon S3 for Shared Test Events:
Storing JSON test event files in an S3 bucket provides a centralized, cost-effective, and highly available solution.
Granular IAM policies can restrict access to specific developers or roles, ensuring security while maintaining consistency for shared test events.
This solution has minimal operational overhead and integrates easily with existing workflows.
Why Other Options Are Incorrect:
Option B: Using DynamoDB and a Lambda function introduces unnecessary complexity for a relatively simple requirement. S3 provides a simpler and more cost-efficient solution.
Option C: AWS Lambda test events are not inherently shareable across developers, making this option invalid.
Option D: Using a Git repository adds operational overhead and requires developers to clone/update repositories for access, which is more cumbersome compared to S3.
References:
Amazon S3 for Centralized Storage


NEW QUESTION # 456
A developer is building a web and mobile application and needs a solution to deploy the application code. The solution must be compatible with the developer's Git source control repository. When the developer adds a new branch, the solution must create a separate deployment.
Which solution will meet these requirements with the LEAST operational overhead?

Answer: C

Explanation:
The requirements describe a Git-driven workflow where each new branch automatically gets its own deployment with minimal setup and management. AWS Amplify is designed for exactly this use case for web (and supporting mobile backends): it integrates directly with Git providers and offers continuous deployment. Amplify's feature branch deployments automatically create a separate deployment (and typically a distinct preview URL) for each connected branch, enabling developers to test and review changes per branch without manually provisioning environments.
With Amplify, the developer connects the repository once, selects the branches to deploy, and Amplify automatically builds and deploys the application whenever code changes are pushed. When a new branch is added, Amplify can be configured to deploy it as a separate environment, providing isolated testing, previewing, and validation. This dramatically reduces operational overhead because Amplify manages build settings, hosting, SSL, and branch-based environments without needing custom CI/CD wiring.
Option A (ECR + ECS + GitHub Actions) can support branch deployments, but it requires substantial operational work: container build pipelines, task/service management, networking, scaling, and environment isolation per branch. Option B (Elastic Beanstalk) can manage deployments, but branch-based automatic deployments are not as native; creating separate environments and managing application versions typically requires more manual steps or additional automation. Option C (Lambda aliases) is not a general-purpose web
/mobile deployment approach and does not naturally map "new Git branch" to an isolated deployment environment without significant custom tooling.
Therefore, D is the best fit with the least operational overhead: use AWS Amplify with feature branch deployments to automatically create and manage separate deployments for Git branches.


NEW QUESTION # 457
A developer has written the following IAM policy to provide access to an Amazon S3 bucket:

Which access does the policy allow regarding the s3:GetObject and s3:PutObject actions?

Answer: C

Explanation:
https://aws.amazon.com/blogs/security/iam-policies-and-bucket-policies-and-acls-oh-my-controlling-access-to-s3-resources/


NEW QUESTION # 458
......

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