Databricks Machine Learning Professional Question 86
Select 4You are working on a machine learning project where you are managing models using the Databricks MLflow Model Registry. Your team needs to differentiate between the available model stages to decide how to manage a new model version. Which of the following statements correctly describe the differences between the available model stages in the MLflow Model Registry?
- A
The 'Staging' stage is typically used for testing a model in a pre-production environment.
- B
The 'Archived' stage indicates a model is no longer actively used or needed and is stored for historical purposes.
- C
The 'Production' stage allows multiple versions of the same model to be marked as 'Production' simultaneously.
- D
The 'None' stage is the default stage for new model versions and indicates the model has not yet been assigned a specific stage.
- E
The 'Production' stage is used for models that are ready for deployment in production environments.
Show answer and explanation
Correct answers: A, B, D, E
Explanation
Databricks MLflow Model Registry offers different stages ('None', 'Staging', 'Production', and 'Archived') to manage and track the lifecycle of machine learning models. Understanding the purpose and constraints of these stages is crucial for effectively managing models and ensuring their proper deployment. This question evaluates your ability to identify and differentiate between these model stages.
- A. Correct.
Correct: The 'Staging' stage is used for testing models in a pre-production environment before they are promoted to 'Production'. This is typically where validation occurs.
- B. Correct.
Correct: The 'Archived' stage is meant for models that are no longer active but are kept for reference or audit purposes. They are not used in production or testing.
- C. Incorrect.
Incorrect: The 'Production' stage only allows one version of a model to be marked as 'Production' at a time to ensure clarity and prevent conflicts in production systems.
- D. Correct.
Correct: The 'None' stage is the default stage for new models, indicating they have not been assigned to 'Staging', 'Production', or 'Archived'.
- E. Correct.
Correct: The 'Production' stage is used for models that are ready and approved for deployment in production environments, ensuring they are used for real-world tasks.