CAIC Cloud Infrastructure 3

Question 1

What does 'infrastructure as code' (IaC) provide for AI platform teams?

Accepted Answer

Reproducible, version-controlled environment provisioning

Answer

IaC tools like Terraform and Pulumi let teams define cloud resources in code, enabling repeatable, auditable, and diff-able infrastructure changes.

Question 2

A CAIC consultant recommends separating AI training and inference workloads into different node pools. What is the PRIMARY reason?

Accepted Answer

Training and inference require different hardware profiles and scaling behaviors

Answer

Training is batch-oriented and GPU-heavy, while inference is latency-sensitive and may need different GPU types or even CPU-only nodes, requiring distinct pools.

Question 3

Which networking concept reduces AI data transfer costs when moving large datasets between cloud storage and compute within the same region?

Accepted Answer

Private endpoints / VPC peering

Answer

Private endpoints and VPC peering keep traffic on the provider's backbone, avoiding public internet egress fees and reducing latency.

Question 4

What is the purpose of a feature store in cloud AI infrastructure?

Accepted Answer

To centralize, share, and serve ML features consistently across training and serving

Answer

A feature store (e.g., Feast, Tecton) ensures the same feature logic is used in training and inference, preventing training-serving skew.

Question 5

An organization needs to run AI workloads that require physical hardware control and data residency, but also want elastic capacity. Which pattern fits best?

Accepted Answer

Hybrid cloud with cloud bursting

Answer

Hybrid cloud with cloud bursting keeps sensitive workloads on-premises while automatically routing overflow to the public cloud during peak demand.

(CAIC) Certified AI Consultant Practice Test

(CAIC) Certified AI Consultant Practice Test

CAIC Cloud Infrastructure 3