Model stages (staging, production, archived) in MLOps - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the purpose of the staging stage in model deployment?

The staging stage is where a model is tested in an environment similar to production to catch issues before full deployment. It acts like a dress rehearsal for the model.

beginner

Define the production stage for a machine learning model.

Production is the live environment where the model serves real users or systems. It must be stable, reliable, and performant.

beginner

What does it mean when a model is archived?

Archived means the model is no longer actively used but kept for record, audit, or possible future reference.

intermediate

Why is it important to have separate stages like staging and production?

Separate stages help catch errors early, protect users from unstable models, and allow safe testing before full release.

intermediate

How does archiving a model help in managing machine learning projects?

Archiving keeps old models safe for audits, comparisons, or rollback without cluttering active environments.

What is the main goal of the staging stage?

A Test the model in a safe environment before production

B Serve real users with the model

C Delete old models

D Train the model

Staging is used to test the model in an environment similar to production before full deployment.

Which stage is the model actively used by end users?

A Production

B Archived

C Staging

D Training

Production is the live environment where the model serves real users.

What happens to a model in the archived stage?

A It is deleted permanently

B It is kept for record but not used

C It is actively updated

D It is tested

Archived models are stored for record or audit but are not actively used.

Why should you not deploy a model directly to production without staging?

A Because staging is cheaper

B Because archived models are better

C To avoid exposing users to untested models

D Because production is slower

Staging helps catch issues before users see the model, protecting user experience.

Which stage helps in rolling back to a previous model version if needed?

A Production

B Staging

C Training

D Archived

Archived models can be retrieved to roll back or compare with current models.

Explain the differences between staging, production, and archived model stages.

Think about where the model is used and why.

Why is it important to archive models instead of deleting them?

Consider future needs and safety.