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Amazon DVA-C02 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Deployment	24%	- Implement CI/CD pipelines 1. Use AWS CodePipeline, CodeBuild, CodeDeploy 2. Automate deployment and testing workflows - Deploy applications on AWS 1. Deploy to AWS Lambda, Amazon EC2, Elastic Beanstalk 2. Perform safe updates and rollbacks - Prepare application artifacts for deployment 1. Use infrastructure as code (AWS CloudFormation, AWS SAM) 2. Package code and dependencies
Topic 2: Troubleshooting and Optimization	18%	- Optimize application performance 1. Improve latency and throughput 2. Optimize resource usage and costs - Debug and resolve errors 1. Resolve integration and configuration problems 2. Identify and fix code defects - Troubleshoot application issues 1. Analyze logs, metrics, and traces 2. Use Amazon CloudWatch, AWS X-Ray for monitoring
Topic 3: Development with AWS Services	32%	- Interact with AWS data services 1. Work with Amazon DynamoDB, Amazon S3 2. Implement caching and data storage strategies - Write code for applications hosted on AWS 1. Develop serverless applications 2. Use AWS SDKs and APIs 3. Implement architectural patterns - Integrate AWS services into applications 1. Implement messaging and event-driven workflows 2. Use AWS Lambda, API Gateway, Amazon EventBridge
Topic 4: Security	26%	- Secure application data 1. Implement encryption at rest and in transit 2. Manage secrets and credentials securely - Apply security best practices 1. Validate application security configurations 2. Follow AWS Well-Architected Framework security principles - Implement authentication and authorization 1. Manage IAM roles, policies, and permissions 2. Use Amazon Cognito for identity management

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Amazon AWS Certified Developer - Associate Sample Questions (Q336-Q341):

NEW QUESTION # 336
A company's website runs on an Amazon EC2 instance and uses Auto Scaling to scale the environment during peak times. Website users across the world ate experiencing high latency flue lo sialic content on theEC2 instance. even during non-peak hours.
When companion of steps mill resolves the latency issue? (Select TWO)

A. Double the Auto Scaling group's maximum number of servers
B. Create an Amazon Cloudfront distribution to cache the static content
C. Scale vertically by resizing the EC2 instances
D. Host the application code on AWS lambda
E. Store the application's sialic content in Amazon S3

Answer: B,E

Explanation:
Explanation
The combination of steps that will resolve the latency issue is to create an Amazon CloudFront distribution to cache the static content and store the application's static content in Amazon S3. This way, the company can use CloudFront to deliver the static content from edge locations that are closer to the website users, reducing latency and improving performance. The company can also use S3 to store the static content reliably and cost-effectively, and integrate it with CloudFront easily. The other options either do not address the latency issue, or are not necessary or feasible for the given scenario.

NEW QUESTION # 337
A developer is creating a template that uses AWS CloudFormation to deploy an application. The application is serverless and uses Amazon API Gateway, Amazon DynamoDB, and AWS Lambda.
Which AWS service or tool should the developer use to define serverless resources in YAML?

A. AWS Cloud Development Kit (AWS CDK)
B. AWS Serverless Application Model (AWS SAM)
C. CloudFormation serverless intrinsic functions
D. AWS Elastic Beanstalk

Answer: B

Explanation:
AWS Serverless Application Model (AWS SAM) is an open-source framework that enables developers to build and deploy serverless applications on AWS. AWS SAM uses a template specification that extends AWS CloudFormation to simplify the definition of serverless resources such as API Gateway, DynamoDB, and Lambda. The developer can use AWS SAM to define serverless resources in YAML and deploy them using the AWS SAM CLI.

NEW QUESTION # 338
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.

Answer: A

NEW QUESTION # 339
A developer is configuring AWS CodeDeploy to deploy an existing application to on-premises servers. The developer has a copy of all application source files and configurations in a directory on a local development machine. How can the developer prepare an application revision to be ready for deployment?

A. Use the AWS CLI create-deployment command.
B. Create an AppSpec file locally. Upload the file to Amazon S3.
C. Add an AppSpec file to the root of the application's directory. Bundle the directory into an archive file. Upload the bundle to Amazon S3.
D. Use the AppSpec editor in the CodeDeploy console to specify the AppSpec file for the application revision.

Answer: C

Explanation:
To prepare an application revision for CodeDeploy, the developer must include an AppSpec file in the root of the application directory, bundle the entire directory into an archive (such as a .zip file), and upload this archive to Amazon S3. This package is then used by CodeDeploy for deployment.

NEW QUESTION # 340
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.

Answer: B

NEW QUESTION # 341
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