AIP-C01 Foundation Model Integration Data And Compliance — 10 Questions

Question 1

A healthcare startup needs to ensure that their Bedrock-based AI application is HIPAA compliant. What is the mandatory step for the data storage layer?

Accepted Answer

Enable server-side encryption with AWS managed keys on the S3 bucket containing the source data.. To meet HIPAA requirements, all data must be encrypted at rest using AWS KMS with customer-managed keys (CMK) and have logging enabled via CloudTrail.

Answer

Store all data in-memory only to avoid persistent storage risks.

Answer

Use public S3 buckets with ACLs enabled.

Answer

Disable logging to prevent sensitive data from appearing in logs.

Question 2

Which TWO factors are critical when choosing a model for a RAG architecture that requires high grounding accuracy?

Accepted Answer

The model's support for citation and source attribution.. Accuracy in RAG relies on model reasoning capability and the quality of the retrieved chunks.

Answer

The model's training date.

Answer

The model's ability to generate images.

Answer

The number of parameters in the model.

Question 3

A developer is designing a RAG system and wants to ensure high-quality retrieval. Which THREE techniques should be implemented to improve semantic search relevance?

Accepted Answer

Using a reranking model to score retrieved documents. Hybrid search, reranking, and semantic chunking are standard best practices for enhancing RAG retrieval accuracy.

Answer

Increasing the vector dimension size to maximum

Answer

Using only fixed-size overlap chunking

Question 4

A developer wants to choose a foundation model in Amazon Bedrock that offers the best balance of reasoning capability and latency for a customer support chatbot. Which tool should the developer use to evaluate models?

Accepted Answer

Bedrock Model Evaluation jobs.. The Bedrock Model Evaluation service allows developers to compare model performance using automated and human-in-the-loop metrics.

Answer

Amazon CloudWatch Metrics for Bedrock.

Answer

AWS Glue DataBrew.

Answer

Amazon SageMaker Model Monitor.

Question 5

An organization is deploying a RAG architecture using Amazon Bedrock and Amazon OpenSearch Serverless. The security team requires that all data remain within the VPC. How should the developer configure the integration?

Accepted Answer

Deploy the Bedrock Knowledge Base using a PrivateLink interface endpoint for Bedrock and a VPC endpoint for OpenSearch Serverless.. To keep traffic within the VPC, developers must configure VPC Endpoints (PrivateLink) for both Amazon Bedrock and Amazon OpenSearch Serverless.

Answer

Configure the Knowledge Base to use an S3 Gateway Endpoint only.

Answer

Use a NAT Gateway to route all traffic to the Bedrock service.

Answer

Use an API Gateway with a WAF to restrict access to the vector store.

Question 6

A company is building a RAG application using Amazon Bedrock and needs to ensure that the data ingested into the knowledge base is filtered based on user identity. Which approach should the developer use?

Accepted Answer

Use Amazon Bedrock Knowledge Base metadata filtering during the retrieval phase to apply access controls.. Knowledge Base filters allow you to restrict retrieval results based on metadata attributes associated with the document chunks.

Answer

Use Lambda authorizers to filter the retrieved results after they are returned by the model.

Answer

Create separate vector indexes for every user role within the Knowledge Base configuration.

Answer

Implement fine-grained access control using IAM policies on the S3 bucket containing the source data.

Question 7

A healthcare organization must ensure that PII is removed from documents before they are stored in an Amazon Bedrock Knowledge Base. Which THREE actions should the developer take?

Accepted Answer

Configure the Knowledge Base to use a private VPC endpoint to prevent data exfiltration.. Data preparation involves identifying, masking, and auditing data before it reaches the vector store.

Answer

Manually encrypt all files using AWS KMS before uploading to S3.

Answer

Enable Amazon Bedrock Data Protection policies to automatically strip PII during vectorization.

Question 8

A company is integrating Amazon Bedrock with a private knowledge base. They need to ensure that PII is masked before the retrieved documents are passed to the Foundation Model. Which approach is most effective?

Accepted Answer

Implement an AWS Lambda function with Amazon Comprehend to redact PII during the ingestion process into the Knowledge Base.. Amazon Comprehend can be integrated into the data ingestion pipeline to detect and redact PII before documents are indexed into the Amazon OpenSearch Serverless vector store.

Answer

Configure the Bedrock Knowledge Base to use a custom encryption key for PII filtering.

Answer

Enable Amazon Macie on the S3 bucket and configure Bedrock to ignore flagged objects.

Answer

Use Amazon Bedrock Guardrails to mask PII during the inference request.

Question 9

A company is building a RAG application using Amazon Bedrock and needs to ensure that sensitive PII is filtered out before it reaches the foundation model. Which feature should be used to achieve this?

Accepted Answer

Amazon Bedrock Guardrails. Amazon Bedrock Guardrails allows users to configure content filters, including PII redaction, to prevent sensitive information from being processed by or returned from foundation models.

Answer

AWS WAF on the Bedrock API endpoint

Answer

Amazon Macie on the S3 bucket housing the source data

Answer

AWS Glue DataBrew

Question 10

A developer is optimizing a RAG solution for a legal firm. The documents are highly dense and technical. Which chunking strategy in Amazon Bedrock Knowledge Bases provides the best balance of retrieval accuracy?

Accepted Answer

Hierarchical chunking.. Hierarchical chunking is designed for complex documents by creating parent and child chunks, which helps maintain context during retrieval.

Answer

Semantic chunking based on paragraph breaks.

Answer

Fixed-size chunking with 100 token overlap.

Answer

Default chunking strategy.