AIP-C01 Practice Test 7 — 10 Questions

Question 1

Which THREE metrics are best used for setting up auto-scaling policies on a SageMaker endpoint?

Accepted Answer

InvocationsPerInstance. InvocationsPerInstance, CPUUtilization, and GPUUtilization are the standard metrics to trigger scaling actions.

Answer

IAMUserLoginCount

Answer

S3RequestLatency

Question 2

Which THREE of the following are components of a robust AI governance framework in an AWS environment?

Accepted Answer

Implement Amazon Bedrock Guardrails. Option A is correct because Amazon Bedrock Guardrails provides configurable safeguards such as content filters, denied topics, and PII redaction that enforce responsible-AI policies at inference time, which is a core control of an AI governance framework. Option D is correct because Bedrock Model Invocation Logging captures invocation metadata (and optionally full request/response payloads) to CloudWatch Logs or Amazon S3, delivering the auditability and traceability that governance requires. Option E is correct because IAM roles with least-privilege access restrict who and what can invoke models or manage AI resources, satisfying the access-control and segregation-of-duties principles of governance. Option B does not belong because granting all users AdministratorAccess violates least privilege and destroys accountability. Option C does not belong because publicly hosting a model endpoint exposes it to unauthorized use and data exfiltration, directly undermining governance and security.

Answer

Provide all users with AdministratorAccess

Answer

Publicly host the model endpoint

Question 3

A developer wants to ensure that the RAG pipeline is resilient to outages. What architectural pattern should be used?

Accepted Answer

Multi-region deployment with cross-region replication for the vector database.. A multi-region deployment with cross-region replication of the vector database ensures that if one AWS region becomes unavailable, the RAG pipeline can fail over to a replica region that already holds the embedded document vectors, preserving retrieval and generation. This directly addresses resilience to outages by removing the single-region failure domain for both compute and the vector store. Cross-region replication keeps the vector index synchronized so failover does not require re-ingesting and re-embedding the corpus.

Answer

Single-node deployment.

Answer

Hardcoding API endpoints.

Answer

Using only one S3 bucket.

Question 4

Which THREE factors should you consider when tuning your inference endpoint for cost-efficiency?

Accepted Answer

Auto Scaling policies based on custom metrics. Instance type, auto-scaling configuration, and model optimization (like quantization) are critical levers for cost efficiency.

Answer

CloudTrail log retention period

Answer

Number of S3 buckets used

Question 5

When implementing a RAG-based application, which TWO of the following ensure document security?

Accepted Answer

Apply metadata filters to control document access. Option A is correct because applying metadata filters at query time restricts retrieval to only the documents a given user is authorized to see, enforcing document-level access control within the RAG pipeline. Option B is correct because IAM-based connectors authenticate to data sources using identity and access management policies, ensuring that only permitted documents are ingested and that access respects existing enterprise permissions. Option C is wrong because a single shared user removes per-user accountability and grants everyone the same access, defeating least privilege. Option D is wrong because making all documents globally readable exposes sensitive content to every user and query. Option E is wrong because disabling indexing of sensitive documents doesn't secure them within RAG; it merely removes them from retrieval, which is a data-availability decision rather than an access-control mechanism.

Answer

Use a single shared user for all data source connections

Answer

Make all documents globally readable

Answer

Disable indexing of sensitive documents

Question 6

Your organization needs to ensure that only authorized IAM users can access specific foundation models in Bedrock. Which configuration is required?

Accepted Answer

Attach an IAM policy with bedrock:InvokeModel allowing access to specific model ARNs. Amazon Bedrock integrates with AWS IAM to control access to foundation models. To restrict which IAM users can invoke specific models, you attach an IAM policy that includes the bedrock:InvokeModel action and specifies the ARNs of the allowed foundation models. This policy can be attached to users, groups, or roles, and it enforces least privilege at the model level. Without such a policy, users either have no access or overly broad access, so this is the required configuration.

Answer

Enable AWS Organizations SCPs only

Answer

Use Amazon Cognito user pools

Answer

Use Resource-Based Policies on the foundation model

Question 7

Which THREE items must be configured when setting up a new Knowledge Base in Amazon Bedrock?

Accepted Answer

Embedding model selection.. Embedding model, data source, and vector database are the three mandatory components for a Knowledge Base.

Answer

Model evaluation dataset.

Answer

External firewall rules.

Question 8

A company is building a RAG application on Amazon Bedrock. They need to store embeddings for a large-scale knowledge base with low-latency similarity search and full integration with LangChain. Which vector database should the developer recommend?

Accepted Answer

Amazon OpenSearch Serverless vector engine. Amazon OpenSearch Serverless vector engine is purpose-built for storing and querying high-dimensional embeddings with k-NN similarity search, offering low-latency retrieval at scale and native LangChain integration via the OpenSearch vector store class. It removes cluster management overhead while supporting the vector workloads RAG applications require.

Answer

Amazon DynamoDB with global secondary indexes

Answer

Amazon Aurora PostgreSQL without pgvector

Answer

Amazon S3 with Athena query engine

Question 9

Which TWO of the following strategies are best for reducing the cost of SageMaker training jobs?

Accepted Answer

Using Managed Spot Training. Using Managed Spot Training and instance-appropriate types are standard methods for reducing training costs.

Answer

Keeping training clusters running

Answer

Increasing the number of instances

Answer

Enabling detailed logging for every epoch

Question 10

A company is using RAG with Amazon Bedrock Knowledge Bases. They need to ensure that users can only retrieve documents they are authorized to see. How should this be implemented?

Accepted Answer

Use the filters attribute in the Retrieve API call based on document metadata. Amazon Bedrock Knowledge Bases support metadata filtering on the Retrieve and RetrieveAndGenerate APIs. By attaching authorization metadata (e.g., department, clearance level) to documents during ingestion and passing a filters attribute in the Retrieve call based on the user's identity, the application ensures users only retrieve documents they are authorized to see. This enforces document-level access control at query time.

Answer

Encrypt the documents with different KMS keys

Answer

Create separate Knowledge Bases for every user

Answer

Apply IAM policies to the S3 bucket