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April 17, 2026 · 1 min read

What is model drift and how do you detect and handle it in production ML systems?

Model drift is the degradation of model performance over time as the real-world data distribution changes after deployment. Detect with monitoring (input distribution prediction distribution and ground truth metrics). Handle…

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📅 Apr 17, 2026 ⏱ 1 min read

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What is model drift and how do you detect and handle it in production ML systems?

COVER // WHAT IS MODEL DRIFT AND HOW DO YOU DETECT AND HANDLE IT IN PRODUCTION ML SYSTEMS?

Model drift is the degradation of model performance over time as the real-world data distribution changes after deployment. Detect with monitoring (input distribution prediction distribution and ground truth metrics). Handle with automated retraining triggers shadow deployments and champion-challenger frameworks.

advanced ml mlops model-drift monitoring production

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