Minimize the Production Impact of ML Model Updates with Amazon SageMaker Shadow Testing¶
Ramesha, R., Zhao, Li, & Sairam, T. (2022). Minimize the Production Impact of ML Model Updates with Amazon SageMaker Shadow Testing. AWS Machine Learning Blog.
Cited by¶
1 citation across 1 artifact.
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Mechanisms¶
- Shadow-Map Evaluation
- Its strength is that it de-risks a map update by testing it on real context distributions with zero effect before it can act, catching regressions an offline test misses precisely because it uses live, current traffic;
This sourceShows that a shadow deployment tests a candidate on copied live traffic without affecting production responses and uses observed stability and performance to inform promotion.
- Its strength is that it de-risks a map update by testing it on real context distributions with zero effect before it can act, catching regressions an offline test misses precisely because it uses live, current traffic;
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