- A
Amazon SageMaker
Why wrong: SageMaker is a platform for building, training, and deploying custom ML models — Bedrock provides access to pre-trained foundation models without the need to train or host your own.
- B
Amazon Rekognition
Why wrong: Rekognition is a pre-trained vision AI service for image/video analysis — it's a specific AI service, not a foundation model access platform.
- C
Amazon Bedrock
Amazon Bedrock provides serverless API access to foundation models from Amazon, Anthropic, Meta, Stability AI, and others — enabling generative AI applications without managing model training or inference infrastructure.
- D
AWS DeepComposer
Why wrong: AWS DeepComposer is an educational service for learning generative AI through music composition — it's not the platform for accessing production foundation models via API.
Quick Answer
The answer is Amazon Bedrock. This is the correct choice because Bedrock is a fully managed AWS service that provides access to pre-trained foundation models from leading AI providers—such as AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon—through a single API, enabling tasks like text generation and image creation without the need to train models from scratch or manage underlying infrastructure. On the AWS Certified Cloud Practitioner CLF-C02 exam, this question tests your understanding of managed AI services versus custom model training; a common trap is confusing Bedrock with Amazon SageMaker, which is used for building and training custom models, not for accessing pre-trained models via API. A helpful memory tip: think of Bedrock as the "foundation" layer—just as a building needs a solid base, Bedrock gives you a ready-made foundation of AI models to build upon.
CLF-C02 Cloud Technology and Services Practice Question
This CLF-C02 practice question tests your understanding of cloud technology and services. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A company wants to accelerate their machine learning workflows by using pre-trained foundation models for tasks like text generation and image creation without training models from scratch. Which AWS service provides access to pre-trained foundation models via API?
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
Amazon Bedrock is a fully managed service that provides access to pre-trained foundation models (FMs) from leading AI providers like AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon via a single API. It enables you to build generative AI applications for tasks such as text generation and image creation without managing underlying infrastructure or training models from scratch.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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 SageMaker
Why it's wrong here
SageMaker is a platform for building, training, and deploying custom ML models — Bedrock provides access to pre-trained foundation models without the need to train or host your own.
- ✗
Amazon Rekognition
Why it's wrong here
Rekognition is a pre-trained vision AI service for image/video analysis — it's a specific AI service, not a foundation model access platform.
- ✓
Amazon Bedrock
Why this is correct
Amazon Bedrock provides serverless API access to foundation models from Amazon, Anthropic, Meta, Stability AI, and others — enabling generative AI applications without managing model training or inference infrastructure.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
AWS DeepComposer
Why it's wrong here
AWS DeepComposer is an educational service for learning generative AI through music composition — it's not the platform for accessing production foundation models via API.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse Amazon SageMaker (a full ML lifecycle service) with Bedrock (a managed FM API service), or mistakenly think Amazon Rekognition or AWS DeepComposer provide general-purpose generative AI capabilities, when in fact they are specialized for narrow use cases.
Detailed technical explanation
How to think about this question
Amazon Bedrock exposes foundation models via a unified API that abstracts the underlying model provider, allowing you to invoke models like Anthropic's Claude or Stability AI's Stable Diffusion using the same interface. Under the hood, Bedrock manages model endpoint scaling, security, and integration with AWS services like IAM for access control and CloudWatch for monitoring. A real-world scenario is a company using Bedrock to generate product descriptions (text) and marketing images (image) by calling the InvokeModel API with a single SDK, avoiding the cost and complexity of hosting separate model endpoints.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A company's IT admin needs to give a contractor read-only access to production logs without sharing account credentials. Using role-based access control (RBAC) and temporary scoped permissions — not a permanent shared password — is the correct pattern. Questions like this test whether you can apply least-privilege access across cloud identity services.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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FAQ
Questions learners often ask
What does this CLF-C02 question test?
Cloud Technology and Services — This question tests Cloud Technology and Services — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Amazon Bedrock — Amazon Bedrock is a fully managed service that provides access to pre-trained foundation models (FMs) from leading AI providers like AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon via a single API. It enables you to build generative AI applications for tasks such as text generation and image creation without managing underlying infrastructure or training models from scratch.
What should I do if I get this CLF-C02 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 11, 2026
This CLF-C02 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 CLF-C02 exam.
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