- A
Deploy stateless containers without session persistence
Why wrong: Stateless architecture would lose session state between preprocessing steps, causing errors or inconsistent behavior.
- B
Use a single larger GPU instance to handle all requests
Why wrong: Vertical scaling has limits and does not solve horizontal scaling requirements; it also lacks fault tolerance.
- C
Deploy multiple instances behind a round-robin load balancer with sticky sessions
Sticky sessions ensure that all requests from a user session are routed to the same instance, preserving session state during horizontal scaling.
- D
Implement a message queue (e.g., Kafka) to buffer requests
Why wrong: Message queues help with asynchronous processing but do not inherently maintain session state across multiple requests.
AI0-001 AI Infrastructure and Technologies Practice Question
This AI0-001 practice question tests your understanding of ai infrastructure and technologies. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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.
An MLOps team observes that their production inference API experiences increasing latency as more concurrent requests arrive. They need to scale horizontally while maintaining session state of preprocessing steps. Which deployment strategy should they implement?
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
Deploy multiple instances behind a round-robin load balancer with sticky sessions
Sticky sessions (session affinity) ensure that all requests from a given client are routed to the same backend instance, preserving the in-memory session state of preprocessing steps. Combined with a round-robin load balancer, this allows horizontal scaling while maintaining stateful behavior, which is essential for the described latency issue under concurrent load.
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.
- ✗
Deploy stateless containers without session persistence
Why it's wrong here
Stateless architecture would lose session state between preprocessing steps, causing errors or inconsistent behavior.
- ✗
Use a single larger GPU instance to handle all requests
Why it's wrong here
Vertical scaling has limits and does not solve horizontal scaling requirements; it also lacks fault tolerance.
- ✓
Deploy multiple instances behind a round-robin load balancer with sticky sessions
Why this is correct
Sticky sessions ensure that all requests from a user session are routed to the same instance, preserving session state during horizontal scaling.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Implement a message queue (e.g., Kafka) to buffer requests
Why it's wrong here
Message queues help with asynchronous processing but do not inherently maintain session state across multiple requests.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Cisco often tests the distinction between stateless and stateful scaling, where candidates mistakenly choose message queues (Option D) thinking they solve concurrency, but they fail to address the synchronous session state requirement.
Detailed technical explanation
How to think about this question
Sticky sessions are typically implemented via a load balancer inserting a cookie (e.g., `AWSALB` for ALB or `JSESSIONID` for Java apps) or by hashing the client IP to a backend. Under the hood, the load balancer maintains a mapping table that persists for the session duration, ensuring that subsequent requests from the same client hit the same instance. In real-world MLOps, preprocessing steps like tokenization or feature engineering often cache intermediate results in memory, making sticky sessions critical to avoid recomputation and maintain low latency.
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 practitioner preparing for the AI0-001 exam encounters this exact type of scenario on the job. The correct answer here is not the most general option — it is the best answer for the specific constraint described. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Real exam questions reward reading the full scenario before eliminating options, because the constraint defines which answer fits.
What to study next
Got this wrong? Here's your next step.
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FAQ
Questions learners often ask
What does this AI0-001 question test?
AI Infrastructure and Technologies — This question tests AI Infrastructure and Technologies — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Deploy multiple instances behind a round-robin load balancer with sticky sessions — Sticky sessions (session affinity) ensure that all requests from a given client are routed to the same backend instance, preserving the in-memory session state of preprocessing steps. Combined with a round-robin load balancer, this allows horizontal scaling while maintaining stateful behavior, which is essential for the described latency issue under concurrent load.
What should I do if I get this AI0-001 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.
About these practice questions
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Last reviewed: Jul 4, 2026
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.
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