Paths/MLOps Engineer/Model Serving / Scaling & Rollouts
Roll Out a New Model Gradually
A new model goes live to a slice of the traffic first, with a rule that sends it back if the metrics move the wrong way.
Validator
⏱ 0:00
IDLE — checks run live as you type commands; submit when done
01Requirements
live checks- File ~/serving/canary.yaml exists○
- The file names the stable and the canary version○
- The file splits the traffic between them○
- The file states the rollback condition○
02Walkthrough
1 of 4 revealed- 01
Create the serving directory
Rollout configuration lives next to the autoscaler.
mkdir -p ~/serving - 3 locked · each failed submit reveals one
03Stuck?
0 of 3 revealedTake a hint without losing the lab — each one points at the thing to look at, not at the answer.
04AI Tutor
guides, never solvesTell me what you're stuck on — I'll nudge, not solve. Which requirement are you looking at?
04Notebook
saved locally in this browserlearner@lab — ubuntu:24.04
Session is disposable
↑/↓ recalls commands · Ctrl+Enter submits · type help for the command list