Implement shadow deployment
Safely deploy new ML models
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Implement a shadow deployment strategy for a new ML model to compare it against the production model without affecting users. Design the traffic mirroring setup, comparison metrics collection, statistical significance test for declaring the challenger better, and the rollout plan from 0% to 100% traffic.
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Un point crucial : synchronisez l'horodatage des prédictions entre production et fantôme pour éviter les biais temporels. Ajoutez un monitoring de latence dès la duplication du trafic, car un proxy mal configuré peut dégrader les performances du modèle en production. Pensez aussi à logger les prédictions des deux modèles avec un même identifiant de requête pour faciliter les tests statistiques.
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