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Amazon DVA-C02 Exam Syllabus Topics:

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

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Amazon AWS Certified Developer - Associate Sample Questions (Q798-Q803):

NEW QUESTION # 798
A developer needs to use Amazon DynamoDB to store customer orders. The developer's company requires all customer data to be encrypted at rest with a key that the company generates.
What should the developer do to meet these requirements?

A. Store the key by using AW5 KMS. Choose an AVVS KMS customer managed key during creation of the DynamoDB table. Provide the Amazon Resource Name (ARN) of the AWS KMS key.
B. Store the key by using AWS KMS. Choose an AWS KMS AWS managed key during creation of the DynamoDB table. Provide the Amazon Resource Name (ARN) of the AWS KMS key.
C. Store the key by using AWS KMS. Create the DynamoDB table with default encryption. Include the kms:Encrypt parameter with the Amazon Resource Name (ARN) of the AWS KMS key when using the DynamoDB SDK.
D. Create the DynamoDB table with encryption set to None. Code the application to use the key to decrypt the data when the application reads from the table. Code the application to use the key to encrypt the data when the application writes to the table.

Answer: A

Explanation:
Requirement Summary:
* Storecustomer ordersin DynamoDB
* Must encrypt data at rest
* Company wants to use akey it generates(i.e., customer managed key)
Evaluate Options:
A: Set encryption to None, manually encrypt/decrypt in code
* #Overhead and error-prone
* Alsonon-compliantwith AWS encryption best practices
#B. Use customer managed KMS key
* #Exactly meets the requirement: customer generates and controls the key
* During table creation, you can specify aKMS CMK ARN
C: Default encryption + kms:Encrypt in SDK
* #Misunderstanding: DynamoDB handles encryptionautomatically
* You don't need to call kms:Encrypt manually in SDK
D: Use AWS managed key
* #Does not meet the requirement of usingcustom company-generated key
* DynamoDB encryption: https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/EncryptionAtRest.html
* KMS customer managed keys: https://docs.aws.amazon.com/kms/latest/developerguide/concepts.html#customer-cmk

NEW QUESTION # 799
A developer has an application that uses WebSocket APIs in Amazon API Gateway. The developer wants to use an API Gateway Lambda authorizer to control access to the application.
The developer needs to add credential caching and reduce repeated usage of secret keys and authorization tokens on every request.
Which combination of steps should the developer take to meet these requirements? (Choose two.)

A. Use a token-based Lambda authorizer.
B. Use a request parameter-based Lambda authorizer.
C. Use VPC endpoint policies for the WebSocket APIs.
D. Configure an integration request mapping template to reference the context map from the APIGateway Lambda authorizer.
E. Configure an integration request mapping template to reference the identity API key value from the API Gateway Lambda authorizer.

Answer: A,D

NEW QUESTION # 800
A developer works in an environment with multiple AWS accounts that have AWS Lambda functions processing the same 100 KB payloads. The developer wants to centralize the point of origin of the payloads to one account and have all the Lambda functions be invoked whenever the initiating event occurs in the parent account.
How can the developer design the workflow in the MOST efficient way, so all the multi-account Lambda functions get invoked when the event occurs?

A. Use a worker on an Amazon EC2 instance to poll for the payload event. Invoke all Lambda functions using the Lambda Invoke API after using cross-account IAM roles with the AWS STS AssumeRole API call.
B. Set up an Amazon SQS queue with the queue policy permitting the ReceiveMessage action for multi- account Lambda functions. Then send the payload to the SQS queue using the sqs:SendMessage permission and poll the queue using multi-account Lambda functions.
C. Subscribe all the multi-account Lambda functions to an Amazon SNS topic and make an SNS Publish API call with the payload to the SNS topic.
D. Create a Lambda function in the parent account and use cross-account IAM roles with the AWS STS AssumeRole API call to make AWS Lambda invoke the API call to invoke all the cross-account Lambda functions.

Answer: C

Explanation:
Amazon SNS is the most efficient fanout service for this requirement. A single publish operation can distribute the same message payload to multiple subscribers, including Lambda functions. Because the payload is 100 KB, it is within the SNS message size limit, making direct fanout practical. This centralizes the event origin in the parent account and avoids custom orchestration code. Using STS AssumeRole and manually invoking every Lambda function creates unnecessary code, permissions management, and retry complexity. SQS is a queueing service where messages are consumed, not broadcast to all consumers; multiple Lambda functions polling the same queue would compete for messages rather than each receive every payload. An EC2 worker is the worst option because it adds server management and polling overhead.
SNS topic subscriptions are the intended pub/sub design.

NEW QUESTION # 801
A company runs an application on AWS The application uses an AWS Lambda function that is configured with an Amazon Simple Queue Service (Amazon SQS) queue called high priority queue as the event source A developer is updating the Lambda function with another SQS queue called low priority queue as the event source The Lambda function must always read up to 10 simultaneous messages from the high priority queue before processing messages from low priority queue. The Lambda function must be limited to 100 simultaneous invocations.
Which solution will meet these requirements'?

A. Set the event source mapping maximum concurrency to 10 for the high priority queue and to 90 for the low priority queue
B. Set the event source mapping batch size to 10 for the high priority queue and to 90 for the low priority queue
C. Set the event source mapping batch window to 10 for the high priority queue and to 90 for the low priority queue
D. Set the delivery delay to 0 seconds for the high priority queue and to 10 seconds for the low priority queue

Answer: A

Explanation:
* Lambda Concurrency: The 'maximum concurrency' setting in event source mappings controls the maximum number of simultaneous invocations Lambda allows for that specific source.
* Prioritizing Queues: Setting a lower maximum concurrency for the 'high priority queue' ensures it's processed first while allowing more concurrent invocations from the 'low priority queue'.
* Batching: Batch size settings affect the number of messages Lambda retrieves from a queue per invocation, which is less relevant to the prioritization requirement.
References:
* Lambda Event Source Mappings: https://docs.aws.amazon.com/lambda/latest/dg/invocation- eventsourcemapping.html
* Lambda Concurrency: https://docs.aws.amazon.com/lambda/latest/dg/configuration-concurrency.html

NEW QUESTION # 802
A developer created an AWS Lambda function to process data in an application. The function pulls large objects from an Amazon S3 bucket, processes the data, and loads the processed data into a second S3 bucket. Application users have reported slow response times. The developer checks the logs and finds that Lambda function invocations run much slower than expected. The function itself is simple and has a small deployment package. The function initializes quickly. The developer needs to improve the performance of the application. Which solution will meet this requirement with the LEAST operational overhead?

A. Configure the function to use ephemeral storage. Upload the objects and process data in the /tmp directory.
B. Store the data in an Amazon EFS file system. Mount the file system to a local directory in the function.
C. Create an Amazon EventBridge rule to schedule invocations of the function every minute.
D. Create a Lambda layer to package the function dependencies. Add the layer to the function.

Answer: A

Explanation:
Configuring the Lambda function to use ephemeral storage and processing data in the /tmp directory improves performance by leveraging local storage during execution.
Ephemeral Storage: Lambda provides temporary storage (up to 10 GB) in the /tmp directory for each invocation, which is faster than pulling data directly from S3 multiple times.
Performance Boost: Data can be downloaded to /tmp, processed locally, and uploaded to the destination S3 bucket, minimizing S3 network calls.
Low Overhead: This approach requires only minimal changes to the function's configuration.

NEW QUESTION # 803
......

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