An insurance company developed a new experimental machine learning (ML) model to replace an existing model that is in production. The company must validate the quality of predictions from the new experimental model in a production environment before the company uses the new experimental model to serve general user requests.
Which one model can serve user requests at a time. The company must measure the performance of the new experimental model without affecting the current live traffic
Which solution will meet these requirements?
The other solutions are not suitable, because they have the following drawbacks:
References:
1:Shadow Deployment: A Safe Way to Test in Production | LaunchDarkly Blog
2:Shadow Deployment: A Safe Way to Test in Production | LaunchDarkly Blog
3:A/B Testing for Machine Learning Models | AWS Machine Learning Blog
4:Canary Releases for Machine Learning Models | AWS Machine Learning Blog
5:Blue-Green Deployments for Machine Learning Models | AWS Machine Learning Blog
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