- A
MLflow
Why wrong: MLflow is for managing the ML lifecycle, not for containerization or orchestration of deployed models.
- B
Docker
Docker is the standard for containerizing applications, including ML models and their dependencies.
- C
Kubeflow
Why wrong: Kubeflow is an MLOps platform that runs on Kubernetes, but it is not a containerization tool itself; the question specifically asks for tools to containerize and orchestrate.
- D
Kubernetes
Kubernetes orchestrates containerized applications, providing scaling, load balancing, and management for deployed models.
- E
ONNX
ONNX is an open format for representing ML models, enabling interoperability between frameworks and efficient inference on different runtimes.
Question 86 of 1,000
AI0-001 AI Infrastructure and Technologies Practice Question
This AI0-001 practice question tests your understanding of ai infrastructure and technologies. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. 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 machine learning engineer needs to containerize a PyTorch model for deployment on Kubernetes. Which THREE tools or formats should they use?
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
✓
Docker
Docker is correct because it is the standard tool for creating container images that package the PyTorch model along with its dependencies, runtime, and environment into a portable artifact. Kubernetes requires container images (typically built with Docker) to deploy and orchestrate workloads, making Docker essential for containerization before deployment.
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.
- ✗
MLflow
Why it's wrong here
MLflow is for managing the ML lifecycle, not for containerization or orchestration of deployed models.
- ✓
Docker
Why this is correct
Docker is the standard for containerizing applications, including ML models and their dependencies.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Kubeflow
Why it's wrong here
Kubeflow is an MLOps platform that runs on Kubernetes, but it is not a containerization tool itself; the question specifically asks for tools to containerize and orchestrate.
- ✓
Kubernetes
Why this is correct
Kubernetes orchestrates containerized applications, providing scaling, load balancing, and management for deployed models.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
ONNX
Why this is correct
ONNX is an open format for representing ML models, enabling interoperability between frameworks and efficient inference on different runtimes.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Cisco often tests the distinction between containerization tools (Docker) and orchestration or ML lifecycle tools (Kubeflow, MLflow), leading candidates to select tools that manage containers rather than build them.
Detailed technical explanation
How to think about this question
Docker uses a layered filesystem (UnionFS) and a Dockerfile to define the base image (e.g., nvidia/cuda:12.1-runtime-ubuntu22.04), install PyTorch and dependencies, and copy the model artifacts. The resulting image is stored in a registry (e.g., Docker Hub) and pulled by Kubernetes nodes, where each container runs as an isolated process with cgroups for resource limits. A subtle behavior: Docker's default network bridge mode can cause issues with Kubernetes pod networking, so the container must be built with the correct entrypoint and health check commands for Kubernetes liveness probes.
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.
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 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: Docker — Docker is correct because it is the standard tool for creating container images that package the PyTorch model along with its dependencies, runtime, and environment into a portable artifact. Kubernetes requires container images (typically built with Docker) to deploy and orchestrate workloads, making Docker essential for containerization before deployment.
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
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
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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