Amazon Bedrock Provisioned Throughput vs On-Demand for Low Latency Chatbots
A company wants to build a chatbot that responds to customer queries using a foundation model. They need low latency and want to avoid managing infrastructure. Which AWS service should they use?
⚠ Common exam trap
AWS often tests the misconception that AWS Lambda can handle any serverless workload, but candidates must recognize that Lambda is unsuitable for large model inference due to its execution time, memory, and GPU limitations, whereas Bedrock is purpose-built for foundation model access.
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 foundation models (FMs) from leading AI providers via a simple API, eliminating the need to manage underlying infrastructure. It is designed for building generative AI applications like chatbots with low latency, as it handles model hosting, scaling, and inference optimization automatically. This makes it the ideal choice for the company's requirement of low-latency responses without infrastructure management.
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 EC2
Why it's wrong here
EC2 requires full infrastructure management.
- ✗
AWS Lambda
Why it's wrong here
Lambda runs application logic but does not host foundation models; invoking a model still requires a separate service, and cold starts add latency. It is tempting as a serverless compute layer, which is correct for event-driven glue code, not for model inference itself.
- ✓
Amazon Bedrock
Why this is correct
Amazon Bedrock provides serverless access to foundation models through a single API, so the company avoids provisioning or scaling infrastructure while obtaining the low-latency inference the chatbot requires. No model hosting or GPU capacity management falls on the customer.
- ✗
Amazon SageMaker
Why it's wrong here
SageMaker requires provisioning and managing endpoints, instances and scaling policies, contradicting the no-infrastructure requirement. It is tempting because it hosts models, and it would be correct for custom training or full control over inference infrastructure, not for a managed foundation-model chatbot.
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Same concept, more angles
1 more way this is tested on AIF-C01
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. A startup needs to generate product descriptions from bullet points using a foundation model. They want a fully managed serverless experience. Which AWS service should they use?
easy- A.Amazon Comprehend
- ✓ B.Amazon Bedrock
- C.Amazon Polly
- D.Amazon Lex
Why B: Amazon Bedrock is a fully managed serverless service that provides access to foundation models (FMs) from leading AI providers via an API, making it ideal for generating product descriptions from bullet points. It eliminates infrastructure management while allowing you to invoke models like Anthropic Claude or Amazon Titan for text generation tasks.
JA
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.