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Amazon DVA-C02 Exam Syllabus Topics:

Section	Weight	Objectives
Deployment	24%	- Deploy applications on AWS 1. Perform safe updates and rollbacks 2. Deploy to AWS Lambda, Amazon EC2, Elastic Beanstalk - Implement CI/CD pipelines 1. Use AWS CodePipeline, CodeBuild, CodeDeploy 2. Automate deployment and testing workflows - Prepare application artifacts for deployment 1. Use infrastructure as code (AWS CloudFormation, AWS SAM) 2. Package code and dependencies
Security	26%	- Secure application data 1. Implement encryption at rest and in transit 2. Manage secrets and credentials securely - Apply security best practices 1. Validate application security configurations 2. Follow AWS Well-Architected Framework security principles - Implement authentication and authorization 1. Manage IAM roles, policies, and permissions 2. Use Amazon Cognito for identity management
Troubleshooting and Optimization	18%	- Debug and resolve errors 1. Identify and fix code defects 2. Resolve integration and configuration problems - Troubleshoot application issues 1. Use Amazon CloudWatch, AWS X-Ray for monitoring 2. Analyze logs, metrics, and traces - Optimize application performance 1. Improve latency and throughput 2. Optimize resource usage and costs
Development with AWS Services	32%	- Write code for applications hosted on AWS 1. Implement architectural patterns 2. Use AWS SDKs and APIs 3. Develop serverless applications - Integrate AWS services into applications 1. Implement messaging and event-driven workflows 2. Use AWS Lambda, API Gateway, Amazon EventBridge - Interact with AWS data services 1. Implement caching and data storage strategies 2. Work with Amazon DynamoDB, Amazon S3

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Amazon AWS Certified Developer - Associate Sample Questions (Q424-Q429):

NEW QUESTION # 424
A developer is writing a web application that must share secure documents with end users. The documents are stored in a private Amazon S3 bucket. The application must allow only authenticated users to download specific documents when requested, and only for a duration of 15 minutes.
How can the developer meet these requirements?

A. Use server-side encryption with AWS KMS managed keys (SSE-KMS) and download the documents using HTTPS.
B. Modify the S3 bucket policy to only allow specific users to download the documents. Revert the change after 15 minutes.
C. Copy the documents to a separate S3 bucket that has a lifecycle policy for deletion after 15 minutes.
D. Create a presigned S3 URL using the AWS SDK with an expiration time of 15 minutes.

Answer: D

NEW QUESTION # 425
A developer is creating an AWS Lambda function that searches for items from an Amazon DynamoDB table that contains customer contact information- The DynamoDB table items have the customer's email_address as the partition key and additional properties such as customer_type, name, and job_tltle.
The Lambda function runs whenever a user types a new character into the customer_type text input The developer wants the search to return partial matches of all the email_address property of a particular customer_type The developer does not want to recreate the DynamoDB table.
What should the developer do to meet these requirements?

A. Add a global secondary index (GSI) to the DynamoDB table With ernail_address as the partition key and customer_type as the sort key Perform a query operation on the GSI by using the begins_wtth key condition expression With the emal_address property.
B. Add a global secondary index (GSI) to the DynamoDB table with customer_type as the partition key and email_address as the sort key Perform a query operation on the GSI by using the begvns_wth key condition expression With the emad_address property
C. Add a local secondary Index (LSI) to the DynamoDB table With job_tltle as the partition key and emad_address as the sort key Perform a query operation on the LSI by using the begins_wrth key condition expression With the email_address property
D. Add a local secondary index (LSI) to the DynamoDB table With customer_type as the partition key and email_address as the sort key Perform a query operation on the LSI by using the begins_wlth key condition expression With the email_address property

Answer: B

Explanation:
* Understand the Problem: The existing DynamoDB table has email_address as the partition key.
Searching by customer_type requires a different data access pattern. We need an efficient way to query for partial matches on email_address based on customer_type.
* Why Global Secondary Index (GSI):
* GSIs allow you to define a different partition key and sort key from the main table, enabling new query patterns.
* In this case, having customer_type as the GSI's partition key lets you group all emails with the same customer type together.
* Using email_address as the sort key allows ordering within each customer type, facilitating the partial matching.
* Querying the GSI:
* You'll perform a query operation on the GSI, not the original table.
* Use the begins_with key condition expression on the GSI's sort key (email_address) to find partial matches as the user types in the customer_type field.
References:
* DynamoDB Global Secondary Indexes: https://docs.aws.amazon.com/amazondynamodb/latest
/developerguide/GSI.html
* DynamoDB Query Operation: [invalid URL removed]
* Key Condition Expressions: [invalid URL removed]

NEW QUESTION # 426
A developer has a financial application. The application uses AWS Secrets Manager to manage an Amazon RDS for PostgreSQL database's username and password. The developer needs to rotate thepassword while maintaining the application's high availability. Which solution will meet these requirements with LEAST development effort?

A. Rotate the secret by using the alternating-users rotation strategy. Update the application with an appropriate retry strategy to handle authentication failures.
B. Rotate the secret by using multivalue answer rotation. Update the application with an appropriate retry strategy to handle authentication failures.
C. Use the PostgreSQL client to create a new database username and password. Include the new secret values by performing an immediate rotation. Use the AWS CLI to update the RDS database password.
Perform an immediate rotation of the Secrets Manager secrets.
D. Rotate the secret by using the single-user rotation strategy. Update the application with an appropriate retry strategy to handle authentication failures.

Answer: D

Explanation:
Requirement Summary:
* Secrets managed inAWS Secrets Manager
* DB:Amazon RDS for PostgreSQL
* Needautomated password rotation
* Must maintainhigh availability
* Least development effort
Rotation Strategies:
#Single-user rotation strategy
* #Simplest to implement
* The secret containsone set of credentialsused by app and rotation logic
* #Supportsautomated rotation
* AWS providesbuilt-in Lambda rotation templatesfor RDS
A: Alternating-users strategy
* ##More complex
* Requires application toswitch usersduring rotation window
B: Manual secret + CLI rotation
* #Too much manual work
* Not scalable or reliable
C: Multivalue answer rotation
* #Not a valid strategy in this context
* Doesn't apply to Secrets Manager
* Secrets Manager rotation strategies:https://docs.aws.amazon.com/secretsmanager/latest/userguide
/rotating-secrets.html
* RDS PostgreSQL secret rotation:https://docs.aws.amazon.com/secretsmanager/latest/userguide/rotating- secrets_strategies.html#rotating-secrets-single-user

NEW QUESTION # 427
A company stores its data in data tables in a series of Amazon S3 buckets. The company received an alert that customer credit card information might have been exposed in a data table on one of the company's public applications. A developer needs to identify all potential exposures within the application environment.
Which solution will meet these requirements?

A. Use Amazon Made to run a job on the S3 buckets that contain the affected data. Filter the findings by using the SensitiveData:S30bject/Personal finding type.
B. Use Amazon Athena to run a job on the S3 buckets that contain the affected data. Filter the findings by using the SensitiveData:S30bject/Financial finding type.
C. Use Amazon Athena to run a job on the S3 buckets that contain the affected data. Filter the findings by using the SensitiveData:S30bject/Personal finding type.
D. Use Amazon Made to run a job on the S3 buckets that contain the affected data. Filter the findings by using the SensitiveData:S30bject/Financial finding type.

Answer: D

NEW QUESTION # 428
A developer is creating an AWS CloudFormation template to deploy Amazon EC2 instances across multiple AWS accounts. The developer must choose the EC2 instances from a list of approved instance types.
How can the developer incorporate the list of approved instance types in the CloudFormation template?

A. In the Resources section of the CloudFormation template, create resources for each EC2 instance type in the list.
B. In the CloudFormation template, create a separate parameter for each EC2 instance type in the list.
C. In the CloudFormation template, create a parameter with the list of EC2 instance types as AllowedValues.
D. Create a separate CloudFormation template for each EC2 instance type in the list.

Answer: C

Explanation:
In the CloudFormation template, the developer should create a parameter with the list of approved EC2 instance types as AllowedValues. This way, users can select the instance type they want to use when launching the CloudFormation stack, but only from the approved list.

NEW QUESTION # 429
......

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