What is shadow deployment in ML systems?

Shadow deployment runs a new model in parallel without affecting production output.

In shadow mode, the new model receives live traffic but its predictions are not served to users. Instead, outputs are logged and compared against the production model. This helps validate performance under real-world conditions without risk.