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Machine Learning & Data Science / 28
mediumGoogleDatabricksMicrosoft

You're replacing a customer's live scoring model with a better one. Design the rollout so nothing blows up.

Offline wins don't justify big-bang swaps, models fail in ways staging never shows. The shadow → canary → ramp playbook, what to compare at each stage, and the rollback discipline that keeps customer trust.

Updated Aug 2026 · Grounded in real Forward Deployed Engineer interview loops and written to a senior-engineer editorial bar.

Offline wins don't justify big-bang swaps, models fail in ways staging never shows. The shadow → canary → ramp playbook, what to compare at each stage, and the rollback discipline that keeps customer trust.

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