DVA-C02 Exam Dumps - AWS Certified Developer - Associate

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.

Why Option B is Correct:Amazon ECS does not natively process docker-compose.yml files. Instead, the configurations from docker-compose.yml must be converted into ECS-compatible configurations within a task definition. Task definitions are the primary way to specify container configurations in ECS, including service dependencies like databases, caches, and volumes.

Steps to Resolve the Error:

Extract the configurations from the docker-compose.yml file.

Map the dependencies and settings to the appropriate ECS task definition fields.

Deploy the task definition to the ECS cluster.

Why Other Options are Incorrect:

Option A: Docker labels do not directly impact ECS task execution or integrate with ECS service configurations.

Option C: ECS namespaces do not exist as a feature.

Option D: Changing the service type to REPLICA does not resolve the issue of missing service dependency configurations.

AWS Documentation References:

Amazon ECS Task Definitions

Migrating Docker Compose Workloads to ECS

These solutions will mitigate the error most cost-effectively because they do not require increasing the provisioned throughput of the DynamoDB table or creating additional resources. Exponential backoff is a retry strategy that increases the waiting time between retries to reduce the number of requests sent to DynamoDB. The AWS SDKs for DynamoDB implement exponential backoff by default and also provide other features such as automatic pagination and encryption. Increasing the read and write throughput of the DynamoDB table, creating a DynamoDB Accelerator (DAX) cluster, or creating a second DynamoDB table will incur additional costs and complexity.

This solution is the most efficient method to grant users access to AWS resources without requiring them to log in. Amazon Cognito is a service that provides user sign-up, sign-in, and access control for web and mobile applications. Amazon Cognito identity pools support both authenticated and unauthenticated users. Unauthenticated users receive access to your AWS resources even if they aren’t logged in with any of your identity providers (IdPs). You can use Amazon Cognito to associate unauthenticated users with an IAM role that has limited access to resources, such as Amazon S3 buckets or DynamoDB tables. This degree of access is useful to display content to users before they log in or to allow them to perform certain actions without signing up. Using an identity provider to securely authenticate with the application will require users to log in, which does not meet the requirement. Creating an AWS Lambda function to create an IAM user when a user accesses the application will incur unnecessary costs and complexity, and may pose security risks if not implemented properly. Creating credentials using AWS KMS and applying them to users when using the application will also incur unnecessary costs and complexity, and may not provide fine-grained access control for resources.

Comprehensive Detailed and Lengthy Step-by-Step Explanation with All AWS Developer References:

1. Understanding the Use Case:

The goal is to store objects in an S3 bucket while optimizing storage costs. The key conditions are:

Objects are accessed infrequently after 1 week.

Objects must remain immediately accessible at all times.

2. AWS S3 Storage Classes Overview:

Amazon S3 offers various storage classes, each optimized for specific use cases:

S3 Standard: Best for frequently accessed data with low latency and high throughput needs.

S3 Standard-Infrequent Access (S3 Standard-IA): Optimized for infrequently accessed data but requires the same availability and immediate access as Standard storage. It provides lower storage costs but incurs retrieval charges.

S3 Glacier Flexible Retrieval (formerly S3 Glacier): Designed for archival data with retrieval latency ranging from minutes to hours. This does not meet the requirement for "immediate access."

S3 Glacier Deep Archive: Lowest-cost storage, suitable for rarely accessed data with retrieval times of hours.

3. Explanation of the Options:

Option A:"Create an S3 Lifecycle rule to expire objects after 7 days."Expiring objects after 7 days deletes them permanently, which does not fulfill the requirement of retaining the objects for later infrequent access.

Option B:"Create an S3 Lifecycle rule to transition objects to S3 Standard-Infrequent Access (S3 Standard-IA) after 7 days."This is the correct solution. S3 Standard-IA is ideal for objects accessed infrequently but still need to be available immediately. Transitioning objects to this storage class reduces storage costs while maintaining availability and low latency.

Option C:"Create an S3 Lifecycle rule to transition objects to S3 Glacier Flexible Retrieval after 7 days."S3 Glacier Flexible Retrieval is a low-cost archival solution. However, it does not provide immediate access as retrieval requires minutes to hours. This option does not meet the requirement.

Option D:"Create an S3 Lifecycle rule to delete objects that have delete markers."This option is irrelevant to the given use case, as it addresses versioning cleanup, which is not enabled in the described S3 bucket.

4. Implementation Steps for Option B:

To transition objects to S3 Standard-IA after 7 days:

Navigate to the S3 Console:

Sign in to the AWS Management Console and open the S3 service.

Select the Target Bucket:

Choose the bucket where the objects are stored.

Set Up a Lifecycle Rule:

Go to the Management tab.

Under Lifecycle Rules, click Create lifecycle rule.

Define the Rule Name and Scope:

Provide a descriptive name for the rule.

Specify whether the rule applies to the entire bucket or a subset of objects (using a prefix or tag filter).

Configure Transitions:

Choose Add transition.

Specify that objects should transition to S3 Standard-IA after 7 days.

Review and Save the Rule:

Review the rule configuration and click Save.

5. Cost Optimization Benefits:

Transitioning to S3 Standard-IA results in cost savings as it offers:

Lower storage costs compared to S3 Standard.

Immediate access to objects when required.However, remember that there is a retrieval cost associated with S3 Standard-IA, so it is best suited for data with low retrieval frequency.

References:

Amazon S3 Lifecycle Configuration Guide

Amazon S3 Storage Classes

AWS S3 Pricing

AWS Documentation on S3 Standard-IA

IAM Roles for EC2 (A): The most secure way to provide AWS permissions from EC2.

Create a role with a policy allowing s3:GetObject on the specific bucket.

Attach the role to an instance profile and associate that profile with your instances.

Pre-signed URLs (C): Temporary, authenticated URLs for specific S3 actions.

Modify the app to use the AWS SDK to call GeneratePresignedUrl.

Embed these URLs when a user is properly logged in, allowing download access.

References:

IAM Roles for EC2: https://docs. aws.amazon.com/IAM/latest/UserGuide/id_roles_use_switch-role-ec2.html

Generating Presigned URLs: https://docs.aws.amazon.com/AmazonS3/latest/userguide/ShareObjectPreSignedURL.htm

This solution will meet the requirements by using AWS X-Ray to analyze and debug the performance issues with the distributed Lambda applications. AWS X-Ray is a service that collects data about requests that the applications serve, and provides tools to view, filter, and gain insights into that data. The developer can use AWS X-Ray to identify the root cause of the performance issues by examining the segments and errors that show the details of each request and the components that make up the applications. Option A is not optimal because it will use logging statements and Amazon CloudWatch, which may not provide enough information or visibility into the distributed applications. Option B is not optimal because it will use AWS CloudTrail, which is a service that records API calls and events for AWS services, not application performance data. Option D is not optimal because it will use Amazon Inspector, which is a service that helps improve the security and compliance of applications on Amazon EC2 instances, not Lambda functions.

References: AWS X-Ray, Using AWS X-Ray with AWS Lambda

Why Option B is Correct:A customer-managed AWS Key Management Service (KMS) key allows for encryption at rest and provides the ability to rotate the key on demand. This ensures compliance with security requirements for key management and database encryption.

RDS integrates natively with AWS KMS, allowing the use of a customer-managed key for encrypting data at rest.

Key rotation can be managed directly in AWS KMS without needing custom solutions.

Why Other Options are Incorrect:

Option A: AWS KMS managed encryption keys (AWS-owned keys) do not support key rotation on demand.

Option C & D: Storing keys in AWS Secrets Manager with custom rotation is not a recommended approach for database encryption. AWS KMS is designed specifically for secure key management and encryption.

AWS Documentation References:

Encrypting Amazon RDS Resources

AWS Key Management Service (KMS)