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Amazon DVA-C02 Exam Syllabus Topics:

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

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Amazon AWS Certified Developer - Associate Sample Questions (Q372-Q377):

NEW QUESTION # 372
A developer wants to store information about movies. Each movie has a title, release year, and genre. The movie information also can include additional properties about the cast and production crew. This additional information is inconsistent across movies. For example, one movie might have an assistant director, and another movie might have an animal trainer.
The developer needs to implement a solution to support the following use cases:
For a given title and release year, get all details about the movie that has that title and release year.
For a given title, get all details about all movies that have that title.
For a given genre, get all details about all movies in that genre.
Which data store configuration will meet these requirements?

A. On an Amazon RDS DB instance, create a table that contains columns for title, release year, and genre.
Configure the title as the primary key.
B. On an Amazon RDS DB instance, create a table where the primary key is the title and all other data is encoded into JSON format as one additional column.
C. Create an Amazon DynamoDB table. Configure the table with a primary key that consists of the genre as the partition key and the release year as the sort key. Create a global secondary index that uses the title as the partition key.
D. Create an Amazon DynamoDB table. Configure the table with a primary key that consists of the title as the partition key and the release year as the sort key. Create a global secondary index that uses the genre as the partition key and the title as the sort key.

Answer: D

Explanation:
Amazon DynamoDB is a fully managed NoSQL database service that provides fast and consistent performance with seamless scalability. The developer can create a DynamoDB table and configure the table with a primary key that consists of the title as the partition key and the release year as the sort key. This will enable querying for a given title and release year efficiently. The developer can also create a global secondary index that uses the genre as the partition key and the title as the sort key. This will enable querying for a given genre efficiently. The developer can store additional properties about the cast and production crew as attributes in the DynamoDB table. These attributes can have different data types and structures, and they do not need to be consistent across items.

NEW QUESTION # 373
A company has an ecommerce application. To track product reviews, the company's development team uses an Amazon DynamoDB table.
Every record includes the following
* A Review ID a 16-digrt universally unique identifier (UUID)
* A Product ID and User ID 16 digit UUlDs that reference other tables
* A Product Rating on a scale of 1-5
* An optional comment from the user
The table partition key is the Review ID. The most performed query against the table is to find the 10 reviews with the highest rating for a given product.
Which index will provide the FASTEST response for this query"?

A. A global secondary index (GSl) with Product ID as the partition key and Review ID as the sort key
B. A global secondary index (GSl) with Product ID as the partition key and Product Rating as the sort key
C. A local secondary index (LSI) with Review ID as the partition key and Product ID as the sort key
D. A local secondary index (LSI) with Product ID as the partition key and Product Rating as the sort key

Answer: B

Explanation:
Explanation
This solution allows the fastest response for the query because it enables the query to use a single partition key value (the Product ID) and a range of sort key values (the Product Rating) to find the matching items. A global secondary index (GSI) is an index that has a partition key and an optional sort key that are different from those on the base table. A GSI can be created at any time and can be queried or scanned independently of the base table. A local secondary index (LSI) is an index that has the same partition key as the base table, but a different sort key. An LSI can only be created when the base table is created and must be queried together with the base table partition key. Using a GSI with Product ID as the partition key and Review ID as the sort key will not allow the query to use a range of sort key values to find the highest ratings. Using an LSI with Product ID as the partition key and Product Rating as the sort key will not work because Product ID is not the partition key of the base table. Using an LSI with Review ID as the partition key and Product ID as the sort key will not allow the query to use a single partition key value to find the matching items.

NEW QUESTION # 374
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. 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.
B. 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.
C. 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.
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: A

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 # 375
A company has an Amazon S3 bucket that contains sensitive data. The data must be encrypted in transit and at rest. The company encrypts the data in the S3 bucket by using an AWS Key Management Service (AWS KMS) key. A developer needs to grant several other AWS accounts the permission to use the S3 GetObject operation to retrieve the data from the S3 bucket.
How can the developer enforce that all requests to retrieve the data provide encryption in transit?

A. Define a role-based policy on the other accounts' roles to deny access when a request meets the condition of "aws:SecureTransport": "false".
B. Define a resource-based policy on the S3 bucket to allow access when a request meets the condition "aws:SecureTransport": "false".
C. Define a resource-based policy on the KMS key to deny access when a request meets the condition of "aws:SecureTransport": "false".
D. Define a resource-based policy on the S3 bucket to deny access when a request meets the condition "aws:SecureTransport": "false".

Answer: D

Explanation:
Amazon S3 supports resource-based policies, which are JSON documents that specify the permissions for accessing S3 resources. A resource-based policy can be used to enforce encryption in transit by denying access to requests that do not use HTTPS. The condition key aws:SecureTransport can be used to check if the request was sent using SSL. If the value of this key is false, the request is denied; otherwise, the request is allowed. Reference: How do I use an S3 bucket policy to require requests to use Secure Socket Layer (SSL)?

NEW QUESTION # 376
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": ["${www.amazon.com:user_name}"],
"dynamodb:Attributes": ["user_id"]
}
}
D. "Condition": {
"ForAllValues:StringEquals": {
"dynamodb:LeadingKeys": ["${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
Reference:
AWS DynamoDB Condition Keys Documentation

NEW QUESTION # 377
......

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