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Amazon DVA-C02 Exam Syllabus Topics:

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

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Amazon AWS Certified Developer - Associate Sample Questions (Q275-Q280):

NEW QUESTION # 275
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?

A. Access on all buckets except the "DOC-EXAMPLE-BUCKET" bucket
B. Access on all buckets that start with "DOC-EXAMPLE-BUCKET" except the
"DOC-EXAMPLE-BUCKET/secrets" bucket
C. Access on all objects in the "DOC-EXAMPLE-BUCKET" bucket except on objects that start with
"secrets"
D. Access on all objects in the "DOC-EXAMPLE-BUCKET" bucket along with access to all S3 actions for objects in the "DOC-EXAMPLE-BUCKET" bucket that start with "secrets"

Answer: C

Explanation:
Explanation
The IAM policy shown in the image is a resource-based policy that grants or denies access to an S3 bucket based on certain conditions. The first statement allows access to any S3 action on any object in the
"DOC-EXAMPLE-BUCKET" bucket when the request is made over HTTPS (the value of aws:SecureTransport is true). The second statement denies access to the s3:GetObject and s3:PutObject actions on any object in the "DOC-EXAMPLE-BUCKET/secrets" prefix when the request is made over HTTP (the value of aws:SecureTransport is false). Therefore, the policy allows access on all objects in the
"DOC-EXAMPLE-BUCKET" bucket except on objects that start with "secrets". Reference: Using IAM policies for Amazon S3

NEW QUESTION # 276
A company has an application that uses an AWS Lambda function to process customer orders. The company notices that the application processes some orders more than once.
A developer needs to update the application to prevent duplicate processing.
Which solution will meet this requirement with the LEAST implementation effort?

A. Implement a de-duplication mechanism that uses Amazon DynamoDB as the control database.
Configure the Lambda function to check for the existence of a unique identifier before processing each event.
B. Configure the Lambda function to retry failed invocations. Implement a retry mechanism that has a fixed delay between attempts to handle duplicate events.
C. Create a custom Amazon ECS task to perform idempotency checks. Use AWS Step Functions to integrate the ECS task with the Lambda function.
D. Use Amazon Athena to query processed events to identify duplicate records. Add processing logic to the Lambda function to handle the duplication scenarios that the query identifies.

Answer: A

Explanation:
Requirement Summary:
* Orders are being processedmore than once
* Need to preventduplicate processing
* Looking forleast implementation effort
Key Concept:
* Lambda + Event-driven patternscan occasionally result induplicate invocations(at-least-once delivery model)
* You needidempotency(i.e., prevent repeated processing of same event)
Evaluate Options:
#A. Use DynamoDB for de-duplication
* #Simple and widely used approach
* Store a unique orderId as the primary key
* Before processing,check if order exists
* If yes # skip
* If no # process and store the ID
* #Minimal code changes required
B: ECS + Step Functions
* #Overkill for basic de-duplication
* Adds significant complexity
C: Retry logic with fixed delay
* #Doesn't prevent duplication -makes it worse
* Retrying might trigger thesame message again
D: Athena to identify duplicates
* #Reactive solution, not preventative
* Not suitable for real-time event de-duplication
* Lambda idempotency:https://docs.aws.amazon.com/lambda/latest/dg/invocation-retries.html
* Using DynamoDB for idempotent design: https://aws.amazon.com/blogs/compute/how-to-design- idempotent-APIs-on-aws/

NEW QUESTION # 277
A company uses AWS X-Ray to monitor a serverless application. The components of the application have different request rates. The user interactions and transactions are important to trace, but they are low in volume. The background processes such as application health checks, polling, and connection maintenance generate high volumes of read-only requests.
Currently, the default X-Ray sampling rules are universal for all requests. Only the first request per second and some additional requests are recorded. This setup is not helping the company review the requests based on service or request type.
A developer must configure rules to trace requests based on service or request properties. The developer must trace the user interactions and transactions without wasting effort recording minor background tasks.
Which solution will meet these requirements?

A. Disable sampling and trace all requests for requests that handle user interactions or transactions.
Sample high-volume read-only requests at a lower rate.
B. Disable sampling and trace all requests for requests that handle user interactions or transactions.
Sample high-volume read-only requests at a higher rate.
C. Disable sampling for high-volume read-only requests. Sample at a higher rate for all requests that handle user interactions or transactions.
D. Disable sampling for high-volume read-only requests. Sample at a lower rate for all requests that handle user interactions or transactions.

Answer: A

NEW QUESTION # 278
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": ["username", "userid"]
}
}
C. "Condition": {
"ForAllValues:StringEquals": {
"dynamodb:LeadingKeys": ["${www.amazon.com:user_id}"],
"dynamodb:Attributes": ["user_name"]
}
}
D. "Condition": {
"ForAllValues:StringEquals": {
"dynamodb:LeadingKeys": ["${www.amazon.com:user_name}"],
"dynamodb:Attributes": ["user_id"]
}
}

Answer: C

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
Reference:
AWS DynamoDB Condition Keys Documentation

NEW QUESTION # 279
A developer needs to perform geographic load testing of an API. The developer must deploy resources to multiple AWS Regions to support the load testing of the API.
How can the developer meet these requirements without additional application code?

A. Create an AWS Systems Manager document that defines the resources. Use the document to create the resources in the desired Regions.
B. Create an AWS CloudFormation template that defines the load test resources. Use the AWS CLI deploy command to create a stack from the template in each Region.
C. Create and deploy an AWS Lambda function in each desired Region. Configure the Lambda function to create a stack from an AWS CloudFormation template in that Region when the function is invoked.
D. Create an AWS CloudFormation template that defines the load test resources. Use the AWS CLI create-stack-set command to create a stack set in the desired Regions.

Answer: D

Explanation:
Explanation
AWS CloudFormation is a service that allows developers to model and provision AWS resources using templates. A CloudFormation template can define the load test resources, such as EC2 instances, load balancers, and Auto Scaling groups. A CloudFormation stack set is a collection of stacks that can be created and managed from a single template in multiple Regions and accounts. The AWS CLI create-stack-set command can be used to create a stack set from a template and specify the Regions where the stacks should be created. Reference: Working with AWS CloudFormation stack sets

NEW QUESTION # 280
......

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