Amazon Web Services SAA-C03 Actual Questions

AmazonTextractcan extract text from the PDFs, andAmazon Comprehendis the most suitable service to analyze the extracted text for sentiment and insights. Comprehend offers a fully managed, low-operational overhead solution for analyzing text data. The results can then be stored in anAmazon S3bucket, ensuring scalability and easy access.

Option A: Athena is for querying structured data and is not suitable for sentiment analysis.

Option B: SageMaker adds complexity and is not necessary when Comprehend can handle sentiment analysis natively.

Option D: QuickSight is used for visualization and analytics, but it does not provide sentiment analysis.

AWS References:

Amazon Comprehend

Amazon Textract

The most secure solution for allowing EC2 instances to access an S3 bucket is by usingIAM roles. An IAM role can be created with an access policy that grants the required permissions (e.g., to read and write to the S3 bucket). The IAM role is then associated with the EC2 instances through anIAM instance profile.

By associating the role with the instances, the EC2 instances can securely assume the role and receive temporary credentials via the instance metadata service. This avoids the need to store credentials (such as access keys) on the instances or within the application, enhancing security and reducing the risk of credentials being exposed.

AWS CloudFormation can be used to automate the creation of the entire infrastructure, including EC2 instances, IAM roles, and associated policies.

AWS References:

IAM Roles for EC2 Instancesoutlines the use of IAM roles for secure access to AWS services.

AWS CloudFormation User Guidedetails how to create and manage resources using CloudFormation templates.

Why the other options are incorrect:

A. Save IAM access key in UserData: This is insecure because it involves storing long-term credentials in the instance user data, which can be exposed.

B. Store access keys in S3: This is also insecure, as it involves managing and distributing long-term credentials, which should be avoided.

D. Retrieve access keys via a script: This approach is unnecessarily complex and less secure than using IAM roles, which provide temporary credentials automatically.

Why Option B is Correct:

HTTP Proxy Integration: Passes XML requests directly to the application, which already supports XML.

JSON Conversion: An AWS Lambda function converts JSON requests to XML and calls the application.

API Gateway: Acts as a front end to handle JSON requests and integrates seamlessly with Lambda for the transformation process.

Why Other Options Are Not Ideal:

Option A: Suggests using API Gateway mappings to convert JSON to XML. API Gateway mapping templates are limited in functionality and are not ideal for complex transformations.

Option C and D: Use HTTP custom integration unnecessarily, which adds complexity without additional benefits.

AWS References:

Amazon API Gateway Integration:AWS Documentation - API Gateway Integration

AWS Lambda:AWS Documentation - Lambda

Amazon DynamoDB provides single-digit millisecond performance at any scale and is fully managed to handle millions of catalog records. It is ideal for structured catalog data such as product metadata and scales seamlessly during high-traffic events like sales. Amazon S3 is optimized for storing unstructured large objects such as videos and manuals, with virtually unlimited scalability and high durability. Option A (RDS) would not handle massive scale or traffic spikes as efficiently. Option C overloads DynamoDB by forcing it to store large binary data, which is not its purpose. Option D (DocumentDB) is suitable for JSON-like documents but not optimal for storing large media files and would add operational complexity. Therefore, option B represents the best separation of structured and unstructured data storage.