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Amazon DVA-C02 Exam Syllabus Topics:

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

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Amazon AWS Certified Developer - Associate Sample Questions (Q240-Q245):

NEW QUESTION # 240
A developer is building a web application. The application will read temperature information from an Amazon DynamoDB table and will display the information for users. Each record is 5 KB to 7 KB in size. The application can request up to 80 items each second. The application must always return the most recent temperature values from the table. How much read throughput is required to meet this load?

A. 560 read capacity units (RCUs)
B. 40 read capacity units (RCUs)
C. 160 read capacity units (RCUs)
D. 80 read capacity units (RCUs)

Answer: C

Explanation:
Each item size is up to 7 KB, which requires 2 read capacity units (RCUs) per strongly consistent read because 1 RCU covers up to 4 KB for strongly consistent reads. For 80 items per second:
80 items × 2 RCUs = 160 RCUs.

NEW QUESTION # 241
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 for high-volume read-only requests. Sample at a higher rate for all requests that handle user interactions or transactions.
B. Disable sampling for high-volume read-only requests. Sample at a lower rate for all requests that handle user interactions or transactions.
C. Disable sampling and trace all requests for requests that handle user interactions or transactions. Sample high-volume read-only requests at a lower rate.
D. Disable sampling and trace all requests for requests that handle user interactions or transactions. Sample high-volume read-only requests at a higher rate.

Answer: C

NEW QUESTION # 242
A developer built an application by using multiple AWS Lambda functions. The Lambda functions must access dynamic configuration data at runtime. The data is maintained as a 6 KB JSON document in AWS AppConfig. The configuration data needs to be updated without requiring the redeployment of the application.
The developer needs a solution that will give the Lambda functions access to the dynamic configuration data.
What should the developer do to meet these requirements with the LEAST development effort?

A. Migrate the configuration file to a Lambda deployment package. Read the file from the file system at runtime.
B. Migrate the document from AWS AppConfig to a Lambda environment variable. Read the document at the runtime.
C. Use the AWS X-Ray SDK to call the AWS AppConfig APIs. Retrieve the configuration file at runtime.
D. Configure the AWS AppConfig Agent Lambda extension. Access the dynamic configuration data by calling the extension on a local host.

Answer: D

NEW QUESTION # 243
An AWS Lambda function requires read access to an Amazon S3 bucket and requires read/write access to an Amazon DynamoDB table The correct 1AM policy already exists What is the MOST secure way to grant the Lambda function access to the S3 bucket and the DynamoDB table?

A. Attach the existing 1AM policy to the Lambda function.
B. Create an 1AM user with programmatic access Attach the existing 1AM policy to the user. Add the user access key ID and secret access key as environment variables in the Lambda function.
C. Create an 1AM role for the Lambda function Attach the existing 1AM policy to the role Attach the role to the Lambda function
D. Add the AWS account root user access key ID and secret access key as encrypted environment variables in the Lambda function

Answer: C

Explanation:
* Principle of Least Privilege: Granting specific permissions through an IAM role is more secure than directly attaching policies to a function or using root user credentials.
* IAM Roles for Lambda: Designed to provide temporary credentials to Lambda functions, enhancing security.
* Reusability: The existing IAM policy ensures the correct S3 and DynamoDB access is granted.
References:
* IAM Roles for Lambda Documentation: https://docs.aws.amazon.com/lambda/latest/dg/lambda-intro- execution-role.html
* IAM Best Practices: https://docs.aws.amazon.com/IAM/latest/UserGuide/best-practices.html

NEW QUESTION # 244
A developer is receiving an intermittent ProvisionedThroughputExceededException error from an application that is based on Amazon DynamoDB. According to the Amazon CloudWatch metrics for the table, the application is not exceeding the provisioned throughput. What could be the cause of the issue?

A. The DynamoDB table is exceeding the provisioned scaling operations.
B. The DynamoDB table storage size is larger than the provisioned size.
C. The application is exceeding capacity on a particular hash key.
D. The application is exceeding capacity on a particular sort key.

Answer: C

Explanation:
DynamoDB distributes throughput across partitions based on the hash key. Ahot partition(caused by high usage of a specific hash key) can result in a ProvisionedThroughputExceededException, even if overall usage is below the provisioned capacity.
* Why Option B is Correct:
* Partition-Level Limits: Each partition has a limit of 3,000 read capacity units or 1,000 write capacity units per second.
* Hot Partition: Excessive use of a single hash key can overwhelm its partition.
* Why Not Other Options:
* Option A: DynamoDB storage size does not affect throughput.
* Option C: Provisioned scaling operations are unrelated to throughput errors.
* Option D: Sort keys do not impact partition-level throughput.

NEW QUESTION # 245
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