CAP CAP Model Deployment & Lifecycle Management

Question 1

Which deployment pattern runs the new model alongside the old model and gradually shifts traffic to the new one?

Accepted Answer

Canary / gradual rollout

Answer

Canary deployment incrementally shifts a small percentage of traffic to the new model, limiting risk before full cutover.

Question 2

Model monitoring in production should track which of the following to detect data drift?

Accepted Answer

Distribution of input features over time

Answer

Monitoring the statistical distribution of input features reveals data drift, which can degrade model performance over time.

Question 3

What does 'model staleness' mean in the CAP lifecycle management context?

Accepted Answer

Model performance has degraded because the real-world environment has changed

Answer

Model staleness occurs when concept drift causes a previously accurate model to become less effective as the underlying patterns change.

Question 4

Which artifact MUST be version-controlled alongside model code to ensure reproducibility?

Accepted Answer

Training data schema and model hyperparameters

Answer

Reproducibility requires version-controlling the training data schema, hyperparameters, and code so the exact model state can be recreated.

Question 5

A/B testing in model deployment is used to:

Accepted Answer

Compare two model versions using live traffic and business metrics

Answer

A/B testing exposes different user groups to each model version and measures real business outcomes to determine the superior model.

(CAP) Certified Analytics Professional Practice Test