What is a shadow deployment and how does it differ from A/B testing?
mediumAnswer
- In shadow deployment, the new model runs alongside the current one on real production traffic, but its predictions are logged and not served to users.
- You compare its outputs to the production model without user impact.
- A/B testing splits real users between models and compares business metrics.
- Use shadow first to verify safety and correlations, then A/B to measure real impact.
Check yourself — multiple choice
- Shadow deployment shows the new model to half of users
- Shadow deployment logs new-model outputs without serving them
- A/B testing does not need randomization
- Shadow deployment measures business KPI impact
Shadow = observe without serving. A/B = split traffic and measure.
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