AIP-C01 Practice Test 14 — 15 Questions

Question 1

When invoking models in Bedrock, what does the 'streaming' feature provide?

Accepted Answer

Reduced latency until the first token appears. Streaming allows the application to receive and display tokens as they are generated, improving user experience.

Answer

Support for larger context windows

Answer

Higher model accuracy

Answer

Lower cost per invocation

Question 2

Which API call in Amazon Bedrock is used to trigger a text generation request without a Knowledge Base?

Accepted Answer

InvokeModel. InvokeModel is the primary API for sending a prompt directly to a foundation model.

Answer

RetrieveAndGenerate

Answer

GetModelInvocation

Answer

CreateKnowledgeBase

Question 3

Which TWO approaches help optimize the costs of using Amazon Bedrock?

Accepted Answer

Purchasing Provisioned Throughput for predictable workloads. Choosing the right model for the task and using Provisioned Throughput for consistent volume are effective cost strategies.

Answer

Using the most expensive model for all tasks

Answer

Disabling all logging

Answer

Running every request as a separate job

Question 4

A company requires that every AI-generated document must include a watermark for traceability. How can this be handled in Bedrock?

Accepted Answer

Use a custom post-processing Lambda function to inject metadata. Bedrock does not natively watermark text; however, it supports output formats and integration with third-party tools or custom post-processing to append metadata or tracking tokens.

Answer

Use fine-tuning to force the model to watermark

Answer

Enable watermarking in the Bedrock console settings

Answer

Use AWS KMS to sign the generated text

Question 5

An organization is concerned about data residency requirements for their AI models. Where should they look to identify which AWS regions support specific models?

Accepted Answer

The Amazon Bedrock documentation region table.. The AWS Region Table for Amazon Bedrock lists the models available in each region.

Answer

The IAM console.

Answer

The AWS CLI.

Answer

The Amazon S3 bucket settings.

Question 6

You are optimizing a SageMaker inference endpoint for an LLM that requires high memory bandwidth. Which instance family should you choose to balance performance and cost?

Accepted Answer

inf2 instances. The inf2 instances are specifically optimized for cost-effective, high-performance generative AI inference.

Answer

g5 instances

Answer

m5 instances

Answer

p4d instances

Question 7

You are troubleshooting a SageMaker inference endpoint and need to see the container logs. Which service stores these logs?

Accepted Answer

Amazon CloudWatch Logs. SageMaker writes container logs (stdout/stderr) to CloudWatch Logs under the /aws/sagemaker/Endpoints/ path.

Answer

Amazon S3

Answer

Amazon DynamoDB

Answer

AWS CloudTrail

Question 8

To ensure compliance with data residency requirements, you must restrict which AWS regions your Generative AI application can process data. What is the most effective way to enforce this?

Accepted Answer

Service Control Policies (SCPs). AWS Organizations Service Control Policies (SCPs) can be used to deny Bedrock service access in restricted regions.

Answer

VPC Endpoint policies

Answer

IAM policies for all users

Answer

CloudFront geographic restrictions

Question 9

You are tuning a Large Language Model on SageMaker and notice that GPU memory utilization is consistently low despite high latency. Which action is most appropriate to optimize performance?

Accepted Answer

Implementing dynamic batching in your inference handler. Increasing the batch size or throughput via model parallelism or optimizing the inference script allows better utilization of the GPU hardware.

Answer

Increasing the number of instances

Answer

Switching to a larger instance type

Answer

Moving the model to CPU instances

Question 10

A developer needs to share a Bedrock prompt template with another team securely. What is the recommended method?

Accepted Answer

Use Amazon Bedrock Prompt Management. Amazon Bedrock Prompt Management allows for creating and sharing versioned prompt templates across accounts or teams securely.

Answer

Save the prompt as a text file in S3 with public access

Answer

Send the prompt in an email

Answer

Store the prompt in a Git repository without encryption

Question 11

Which data format is best suited for ingestion into an Amazon Bedrock Knowledge Base?

Accepted Answer

PDF, Markdown, or HTML files stored in Amazon S3.. Bedrock Knowledge Bases support various formats, but PDF, HTML, and Markdown are standard and natively handled.

Answer

Raw binary executable files.

Answer

Encrypted raw stream data.

Answer

Proprietary database dump files.

Question 12

A team wants to track who accessed a model and when. Which service provides this audit log?

Accepted Answer

AWS CloudTrail. AWS CloudTrail records all API calls made to AWS services, including Bedrock, creating an audit trail of identity and time.

Answer

AWS Config

Answer

Amazon GuardDuty

Answer

Amazon CloudWatch

Question 13

A developer needs to monitor their Bedrock application for potential abuse. Which TWO features should they utilize?

Accepted Answer

Amazon CloudWatch metrics (e.g., 5xx error rates). CloudWatch metrics for error rates and CloudTrail for audit logs are the primary methods for detecting abuse.

Answer

AWS Cost Explorer to track daily spending

Answer

Amazon Simple Notification Service

Answer

AWS Trusted Advisor performance checks

Question 14

A business requirement is to ensure that the RAG model output is grounded solely in the provided documents. How can this be enforced?

Accepted Answer

Set the model temperature to a very low value (e.g., 0.0) and use clear system instructions.. By configuring the prompt template with strict instructions and utilizing the 'RetrieveAndGenerate' API with the 'source-only' constraint (where supported), you force grounding.

Answer

Increase the temperature of the model to 1.0.

Answer

Use a secondary model to re-check the output.

Answer

Disable the model's training data.

Question 15

When dealing with PII in Generative AI, which THREE practices are recommended?

Accepted Answer

Implement access policies to restrict PII visibility. Redaction, encryption, and limiting access are standard PII practices.

Answer

Store PII in plain text logs for debugging

Answer

Share PII freely across all AWS accounts