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Amazon DVA-C02 Exam Syllabus Topics:

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

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Amazon AWS Certified Developer - Associate Sample Questions (Q709-Q714):

NEW QUESTION # 709
A company is developing a new ecommerce platform on AWS. The company wants to implement an event-driven architecture for the company's order processing system. The system needs to perform the following steps when a customer places an order:
1. Update inventory in the company's warehouse management system
2. Send a confirmation email message to the customer
3. Notify the company's shipping department to prepare the customer's
package
4. Update the customer's order history
A developer at the company wants to ensure loose coupling between services so that the company can easily add new steps in future.
Which solution will meet these requirements?

A. Use AWS Step Functions to orchestrate the workflow. Configure an AWS Lambda function for each step in the process to directly invoke the API for each order processing step.
B. Configure the order processing system to publish an event for each order that is placed to an Amazon EventBridge event bus. Set up separate rules and targets for each order processing step.
C. Use Amazon SNS to publish order events. Create a separate subscription for each order processing step. Configure an AWS Lambda function to process each subscription.
D. Use Amazon SQS to create a queue for orders. Configure an AWS Lambda function to process the queue and to directly call the APIs for each order processing step.

Answer: B

Explanation:
Amazon EventBridge supports event-driven architectures with loose coupling by allowing the order system to publish an order event to an event bus. Separate rules and targets can independently handle inventory updates, customer emails, shipping notifications, and order history updates, while making it easy to add new processing steps later without changing the order publisher.

NEW QUESTION # 710
A company is creating a new application that gives users the ability to upload and share short video files. The average size of the video files is 10 MB. After a user uploads a file, a message needs to be placed into an Amazon Simple Queue Service (Amazon SQS) queue so the file can be processed. The files need to be accessible for processing within 5 minutes.
Which solution will meet these requirements MOST cost-effectively?

A. Write the files to Amazon S3 Glacier Deep Archive. Add the S3 location of the files to the SQS queue.
B. Write messages that contain the contents of the uploaded files to the SQS queue.
C. Write the files to Amazon S3 Standard. Add the S3 location of the files to the SQS queue.
D. Write the files to an Amazon Elastic Block Store (Amazon EBS) General Purpose SSD volume. Add the EBS location of the files to the SQS queue.

Answer: C

NEW QUESTION # 711
A bookstore has an ecommerce website that stores order information in an Amazon DynamoDB table named BookOrders. The DynamoDB table contains approximately one million records.
The table uses OrderID as a partition key. There are no other indexes.
A developer wants to build a new reporting feature to retrieve all records from the table for a specified customer, based on a CustomerID property.

A. Create a DynamoDB global secondary index (GSI) on the table. Use CustomerID as the sort key. Use a filter expression to perform a scan operation on the table to match on the specified CustomerID value.
B. Create a DynamoDB local secondary index (LSI) on the table. Use CustomerID as the sort key. Run a PartiQL query on the table with a SELECT statement where CustomerID equals the specified CustomerID value.
C. Create a DynamoDB global secondary index (GSI) on the table. Use CustomerID as the partition key.
Use the specified CustomerID value to run a query on the table.
D. Create a DynamoDB local secondary index (LSI) on the table. Use CustomerID as the partition key.Use the specified CustomerID value to run a query on the table.

Answer: C

Explanation:
Comprehensive and Detailed Step-by-Step Explanation:
The requirement is to query records by CustomerID, which is not the current partition key (OrderID). To achieve this efficiently:
* Option A: Create a GSI with CustomerID as the Partition Key:
* A Global Secondary Index (GSI) allows developers to create a different partition key and optional sort key for querying the data.
* By creating a GSI with CustomerID as the partition key, the developer can query the table efficiently using CustomerID as the primary lookup key.
* This avoids scanning the entire table and matches the requirement.
* Why Other Options Are Incorrect:
* Option B: Using CustomerID as a sort key for the GSI and performing a scan operation is inefficient. Queries are optimized, but scans are not.
* Option C and D: Local Secondary Indexes (LSI) are only valid when the partition key remains the same as the base table. Since OrderID is the base table's partition key, using CustomerID as the partition key or sort key in an LSI is not valid.
References:
Amazon DynamoDB Documentation: GSIs

NEW QUESTION # 712
A company has a web application that is hosted on AWS. The application is behind an Amazon CloudFront distribution. A developer needs a dashboard to monitor error rates and anomalies of the CloudFront distribution as frequently as possible.
Which combination of steps should the developer take to meet these requirements? (Choose two.)

A. Set up Amazon Kinesis Data Firehose to send the logs to AWS CloudTrail. Create CloudTrail metrics, alarms, and dashboards.
B. Set up Amazon Kinesis Data Streams to send the logs to Amazon OpenSearch Service by using an AWS Lambda function. Make a dashboard in OpenSearch Dashboards.
C. Stream the CloudFront distribution logs to an Amazon S3 bucket. Detect anomalies and error rates by using Amazon Athena.
D. Stream the CloudFront distribution logs to Amazon Kinesis Data Firehose.
E. Enable real-time logs on the CloudFront distribution. Create a data stream in Amazon Kinesis Data Streams.

Answer: B,E

NEW QUESTION # 713
A developer has an application that pushes files from an on-premises local server to an Amazon S3 bucket.
The application uses an AWS access key and a secret key that are stored on the server for authentication. The application calls AWS STS to assume a role with access to perform the S3 PUT operation to upload the file.
The developer is migrating the server to an Amazon EC2 instance. The EC2 instance is configured with an IAM instance profile in the same AWS account that owns the S3 bucket.
What is the MOST secure solution for the developer to use to migrate the automation code?

A. Remove the access key, the secret key, and the code that calls the STS AssumeRole operation. Create a new access key and secret key. Use the new keys to access the S3 bucket.
B. Remove the access key and the secret key. Use the STS AssumeRole operation to add permissions to access the S3 bucket.
C. Remove the code that calls the STS AssumeRole operation. Use the same access key and secret key from the server to access the S3 bucket.
D. Remove the access key, the secret key, and the code that calls the STS AssumeRole operation. Use an IAM instance profile role that grants access to the S3 bucket.

Answer: D

Explanation:
The most secure approach on Amazon EC2 is to avoid long-term static credentials entirely and rely on IAM roles for Amazon EC2 (instance profiles). When an EC2 instance is associated with an instance profile, AWS automatically provides temporary security credentials to the instance through the instance metadata service (IMDS). The AWS SDK and CLI can retrieve and rotate these credentials automatically, eliminating the need to store an access key and secret key on disk. This reduces the risk of credential leakage and removes the operational burden of key rotation.
In this scenario, the EC2 instance is already configured with an IAM instance profile in the same account as the S3 bucket. Because the bucket is in the same account and the instance profile can be granted the required permissions, there is no security benefit to keeping a separate stored access key/secret key or performing an additional STS AssumeRole hop. The simplest and most secure design is to attach an IAM policy to the instance profile role that allows the required s3:PutObject (and any related actions such as s3:PutObjectAcl if needed) on the specific bucket/prefix. The application code can then call S3 directly using the AWS SDK, which will automatically use the instance profile credentials.
Option A continues to use long-lived static credentials stored on the server, which is less secure than instance profiles. Option D is the same problem with different keys: still long-lived credentials that must be protected and rotated. Option B removes stored keys but keeps an AssumeRole call; although AssumeRole uses temporary credentials, it adds complexity and is unnecessary here because the instance already has an IAM role and the S3 bucket is in the same account.
Therefore, the most secure solution is C: remove static keys and the AssumeRole code and use the instance profile role with least-privilege S3 permissions.

NEW QUESTION # 714
......

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