easyMultiple SelectObjective-mapped
AIF-C01 Practice Question: A developer is building an application that uses…
A developer is building an application that uses Amazon Bedrock to answer questions based on a large internal knowledge base. The knowledge base contains PDFs, Word documents, and web pages. Which TWO AWS services are commonly used together to implement a Retrieval-Augmented Generation (RAG) architecture on AWS? (Select TWO.)
⚠ Common exam trap
Many exam-takers confuse data preparation or query services (like AWS Glue or Athena) with the vector search and retrieval components essential for RAG, overlooking that Amazon OpenSearch Serverless provides the vector database capability while Bedrock Knowledge Bases orchestrates the ingestion and retrieval pipeline.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Amazon Bedrock Knowledge Bases
Amazon Bedrock Knowledge Bases is correct because it provides a fully managed service that ingests, chunks, and indexes documents (PDFs, Word, web pages) into a vector store, enabling retrieval-augmented generation (RAG) without custom infrastructure. It integrates directly with foundation models in Bedrock to retrieve relevant context and generate answers grounded in the knowledge base.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Amazon Bedrock Knowledge Bases
Why this is correct
Knowledge Bases is the managed service for creating a RAG pipeline with document ingestion and retrieval.
- ✗
Amazon SageMaker Ground Truth
Why it's wrong here
Ground Truth is for data labeling, not for RAG.
- ✗
AWS Glue
Why it's wrong here
Glue is an ETL service, not directly part of a RAG architecture.
- ✗
Amazon Athena
Why it's wrong here
Athena is for querying data in S3 using SQL, not for RAG.
- ✓
Amazon OpenSearch Serverless
Why this is correct
OpenSearch Serverless can serve as a vector database for storing and retrieving embeddings in a RAG system.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AIF-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AIF-C01 exam.