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Build a Canary Rollout for a Production Recommender

FreeVerified credential3 weeksAdvanced

Overview

What this challenge is about.

Pick a serving stack (Triton, Seldon Core, KServe, or BentoML). Implement two-model traffic splitting with a configurable percentage (start at 5%). Wire up online metric collection (latency, click-through rate, error rate) into Prometheus + Grafana. Define the decision rule with a sequential test (e.g., always-valid p-values via Always-Valid Inference) so you can decide early without inflating false positives. Demonstrate on a public dataset with a synthetic 'good' and 'bad' deploy; the system should auto-rollback the bad one within 30 minutes.

CredentialBlockchain-anchored
ShareableLinkedIn-ready
LanguageEnglish
PaceSelf-paced

The Brief

What you'll do, and what you'll demonstrate.

Ship a working canary-rollout system that auto-promotes good deploys and auto-rolls-back bad ones within 30 minutes.

Earning criteria — what you'll demonstrate

  • Implement traffic-splitting in a production-grade serving stack
  • Design statistically honest auto-promote/rollback rules
  • Wire up the online metrics that matter (not just latency)
  • Defend a rollout decision rule in writing to a skeptical reviewer

Program Fit

Where this fits in your program.

Sharpens the same skills your degree expects you to demonstrate.

Skills

Skills you'll demonstrate.

Each one shows up on your verified credential.

Careers

Roles this prepares you for.

Real titles. Real skill bridges. Pick the one closest to your trajectory.

MLOps Engineer

Owning canary rollouts and auto-rollback logic is the work that defines a senior MLOps engineer on any team shipping models weekly.

This challenge sharpens

  • canary-deployment
  • model-rollout
  • kubernetes

Machine Learning Engineer

MLEs who can ship safely (with traffic-split + sequential tests) move faster than ones who can only train; this challenge gives a portfolio piece for that skill.

This challenge sharpens

  • model-rollout
  • ab-testing
  • sequential-testing

AI Solutions Architect

Designing rollout topologies and the decision rules that govern them is the architectural work AI solutions architects do for product teams.

This challenge sharpens

  • canary-deployment
  • kubernetes
  • model-rollout

One more thing

You can put a credential on your CV by Friday.