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Amazon DVA-C02 Exam Syllabus Topics:

Section	Weight	Objectives
Security	26%	- Implement authentication and/or authorization for applications and AWS services 1. User pools and identity pools in Amazon Cognito 2. Role-based access control (RBAC) 3. Identity federation (SAML, OpenID Connect, Amazon Cognito) 4. Resource-based policies, service policies, and principal policies 5. Bearer tokens (JWT, OAuth, AWS STS) - Implement encryption by using AWS services 1. AWS Certificate Manager 2. AWS KMS 3. AWS Secrets Manager 4. Amazon S3 encryption 5. AWS CloudHSM - Manage sensitive data in application code 1. Encryption of data at rest and in transit 2. AWS Secrets Manager 3. AWS Systems Manager Parameter Store 4. Environment variables
Troubleshooting and Optimization	18%	- Instrument code for observability 1. Custom metrics 2. Structured logging 3. Amazon CloudWatch metrics 4. Amazon CloudWatch alarms 5. AWS X-Ray - Assist in a root cause analysis 1. Application logging 2. Error handling and retries 3. AWS CloudTrail 4. Amazon CloudWatch Logs 5. AWS X-Ray - Optimize applications by using AWS services and features 1. Concurrency and throttling 2. Cost optimization 3. Memory and compute optimization 4. Data storage optimization 5. Caching strategies (ElastiCache, CloudFront)
Deployment	24%	- Automate deployment testing 1. AWS CodePipeline 2. AWS CodeBuild 3. AWS CodeDeploy 4. AWS CodeCommit - Deploy code by using AWS CI/CD services 1. GitHub integration 2. AWS CodePipeline 3. Rolling deployments 4. Canary deployments 5. AWS CodeBuild 6. AWS CodeDeploy 7. Blue/green deployments 8. AWS CodeCommit - Test applications in development environments 1. AWS SAM local 2. Mocking AWS services 3. Local testing of Lambda functions - Prepare application artifacts to be deployed to AWS 1. Lambda deployment packages 2. AWS SAM 3. AWS CDK 4. AWS CloudFormation 5. Docker containers
Development with AWS Services	32%	- Develop code for applications hosted on AWS 1. AWS CLI 2. AWS SDKs 3. Amazon SQS 4. Amazon SNS 5. AWS Lambda 6. Amazon DynamoDB 7. Amazon S3 8. Amazon Cognito 9. AWS CloudFormation 10. Amazon API Gateway - Develop code for AWS serverless applications 1. AWS AppSync 2. AWS Step Functions 3. Amazon EventBridge 4. Amazon API Gateway - Use data stores in application development 1. Amazon EFS 2. Amazon RDS 3. Amazon ElastiCache 4. Amazon DynamoDB 5. Amazon S3

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Amazon AWS Certified Developer - Associate Sample Questions (Q668-Q673):

NEW QUESTION # 668
A company has a serverless application that uses Amazon API Gateway and AWS Lambda functions to expose a RESTful API. The company uses a continuous integration and continuous delivery (CI/CD) workflow to deploy the application to multiple environments. The company wants to implement automated integration tests after deployment.
A developer needs to set up the necessary infrastructure and processes to automate the deployment and integration tests for the serverless application.

A. Use AWS CloudFormation to create and deploy the application infrastructure in each application environment. Use the AWS CLI to invoke Lambda functions to perform deployment tests after each deployment.
B. Use AWS CodePipeline to create a CI/CD pipeline. Configure API Gateway stages to represent each application environment. Use AWS CloudFormation templates to manage the infrastructure for the Lambda functions and API resources. Use AWS CodeBuild to implement automated deployment tests to validate the deployments in each stage.
C. Configure API Gateway stages to represent each application environment. Use AWS SAM templates to manage the infrastructure for the Lambda functions and API resources. Use AWS CodeBuild to implement automated deployment tests to validate the deployments in each stage.
D. Configure API Gateway stages to represent each application environment. Use AWS CloudFormation to manage the infrastructure for the Lambda functions and API resources. Use AWS CodeBuild to implement automated deployment tests to validate the deployments in each stage.

Answer: B

Explanation:
Comprehensive and Detailed Step-by-Step Explanation:
* Option C: Use AWS CodePipeline for CI/CD Workflow:
* AWS CodePipelineautomates the entire CI/CD pipeline, including build, deploy, and test stages.
This minimizes manual effort and integrates well with AWS services.
* API Gateway Stages:Represent different environments, such as dev, test, and prod, allowing isolated deployment and testing.
* AWS CloudFormation Templates:Ensure that the infrastructure for Lambda and API Gateway is consistent across environments.
* AWS CodeBuild for Automated Tests:Validates the deployments in each stage, ensuring integration and functionality are tested post-deployment.
* Why Other Options Are Incorrect:
* Option A and B:While using AWS SAM or CloudFormation for infrastructure management is valid, these options lack the fully automated CI/CD pipeline provided by CodePipeline.
* Option D:Manually invoking Lambda functions using the AWS CLI introduces operational overhead and lacks the automation provided by CodePipeline.

NEW QUESTION # 669
A company is planning to securely manage one-time fixed license keys in AWS. The company's development team needs to access the license keys in automaton scripts that run in Amazon EC2 instances and in AWS CloudFormation stacks.
Which solution will meet these requirements MOST cost-effectively?

A. AWS Secrets Manager secrets with a tag that is named SecretString
B. Amazon S3 with encrypted files prefixed with "config"
C. AWS Systems Manager Parameter Store SecureString parameters
D. CloudFormation NoEcho parameters

Answer: C

Explanation:
https://docs.aws.amazon.com/systems-manager/latest/userguide/systems-manager-parameter- store.html

NEW QUESTION # 670
A company is using Amazon API Gateway to invoke a new AWS Lambda function The company has Lambda function versions in its PROD and DEV environments. In each environment, there is a Lambda function alias pointing to the corresponding Lambda function version API Gateway has one stage that is configured to point at the PROD alias The company wants to configure API Gateway to enable the PROD and DEV Lambda function versions to be simultaneously and distinctly available Which solution will meet these requirements?

A. Use an environment variable for the Lambda function alias in API Gateway. Republish PROD and create a new stage for development. Create API gateway environment variables for PROD and DEV stages. Point each stage variable to the PROD Lambda function alias to the DEV Lambda function alias.
B. Use an API Gateway stage variable to configure the Lambda function alias Republish PROD and create a new stage for development Create API Gateway stage variables for PROD and DEV stages Point each stage variable to the PROD Lambda function alias and to the DEV Lambda function alias
C. Enable a Lambda authorizer for the Lambda function alias in API Gateway Republish PROD and create a new stage for DEV Create API Gateway stage variables for the PROD and DEV stages. Point each stage variable to the PROD Lambda authorizer to the DEV Lambda authorizer.
D. Set up a gateway response in API Gateway for the Lambda function alias. Republish PROD and create a new stage for DEV. Create gateway responses in API Gateway for PROD and DEV Lambda aliases

Answer: B

Explanation:
Explanation
The best solution is to use an API Gateway stage variable to configure the Lambda function alias. This allows you to specify the Lambda function name and its alias or version using the syntax function_name:${stageVariables.variable_name} in the Integration Request. You can then create different stages in API Gateway, such as PROD and DEV, and assign different values to the stage variable for each stage. This way, you can invoke different Lambda function versions or aliases based on the stage that you are using, without changing the function name in the Integration Request. References
* Using API Gateway stage variables to manage Lambda functions
* How to point AWS API gateway stage to specific lambda function alias?
* Setting stage variables using the Amazon API Gateway console
* Amazon API Gateway stage variables reference

NEW QUESTION # 671
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 new CodeCommit repository for development of the new version of the application. Create a Git tag for the development of the new version.
B. 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.
C. 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.
D. 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.

Answer: C

Explanation:
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.

NEW QUESTION # 672
A gaming application stores scores for players in an Amazon DynamoDB table that has four attributes:
user_id, user_name, user_score, and user_rank. The users are allowed to update their names only. A user is authenticated by web identity federation.
Which set of conditions should be added in the policy attached to the role for the dynamodb:PutItem API call?

A. "Condition": {"ForAllValues:StringEquals": {"dynamodb:LeadingKeys": ["${www.amazon.com:
user_id}"],"dynamodb:Attributes": ["user_name", "user_id"]}}
B. "Condition": {"ForAllValues:StringEquals": {"dynamodb:LeadingKeys": ["${www.amazon.com:
user_name}"],"dynamodb:Attributes": ["user_id"]}}
C. "Condition": {"ForAllValues:StringEquals": {"dynamodb:LeadingKeys": ["${www.amazon.com:user_name}"],"dynamodb:Attributes": ["username", "userid"]}}
D. "Condition": {"ForAllValues:StringEquals": {"dynamodb:LeadingKeys": ["${www.amazon.com:
user_id}"],"dynamodb:Attributes": ["user_name"]}}

Answer: D

Explanation:
The correct policy condition ensures that:
The LeadingKeys condition restricts operations to the authenticated user's user_id.
The Attributes condition limits the updatable attributes to user_name.
Explanation of Choices:
Option A: Correctly enforces both the key restriction (dynamodb:LeadingKeys) and ensures only the user_name attribute can be updated.
Option B, C, D: Use incorrect conditions, such as referencing user_name in the LeadingKeys or including other attributes like user_id in updatable fields.
Reference:AWS DynamoDB Condition Keys Documentation

NEW QUESTION # 673
......

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