A financial services company is preparing to deploy a new, high-stakes credit risk model. The executive team's primary requirement is to validate the new model's performance, latency, and stability using real-time production data without exposing any customers to its predictions or potential errors. The existing model must continue to handle all live credit decisions uninterrupted. Which model deployment strategy should the MLOps team implement to meet these specific requirements?
The correct answer is shadow deployment. This strategy involves deploying the new model alongside the production model, where it receives a copy of the live production traffic. However, its predictions are not used for any actual business decisions; they are logged for analysis. This allows the team to compare the new model's performance, stability, and latency against the current model under real-world conditions without any risk to customers, which perfectly matches the scenario's requirements.
Canary deployment is incorrect because it involves routing a small percentage of live traffic to the new model, and the predictions are used for that subset of users. This would violate the requirement of not exposing any customers to the new model's outcomes.
Blue-green deployment is incorrect because it involves switching all traffic from the old model environment ('blue') to a new model environment ('green') at once. It does not support running both models in parallel on the same traffic for validation without impacting users.
A/B testing is incorrect because its purpose is to compare two or more models by serving their predictions to different segments of users and measuring the impact on business metrics. This inherently requires exposing customers to the new model's predictions.
Ask Bash
Bash is our AI bot, trained to help you pass your exam. AI Generated Content may display inaccurate information, always double-check anything important.
What is shadow deployment in MLOps?
Open an interactive chat with Bash
Why can’t canary deployment be used in this scenario?
Open an interactive chat with Bash
How does shadow deployment differ from A/B testing?