AI0-001 Implementing AI Solutions Practice Question
A team is deploying a multi-modal AI model that processes both text and images. They need to ensure that inference requests are handled quickly even during traffic spikes. Which integration pattern is BEST suited for this use case?
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
✓
Use an event-driven architecture with a queue and worker instances
Asynchronous processing with a message queue allows requests to be buffered and processed without blocking the user, scaling out workers as needed.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Deploy a synchronous REST API with auto-scaling
Why it's wrong here
Synchronous APIs can still cause timeouts if processing takes long; they block the caller.
- ✗
Stream responses directly from the model to the client
Why it's wrong here
Streaming may help latency but does not handle buffering during spikes.
- ✗
Pre-compute all possible outputs and cache them
Why it's wrong here
Pre-computation is impractical for dynamic multi-modal inputs.
- ✓
Use an event-driven architecture with a queue and worker instances
Why this is correct
Queues decouple request submission from processing, enabling resilient scaling and handling spikes.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI0-001 practice question is part of Courseiva's free CompTIA 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 AI0-001 exam.