Overview
What this challenge is about.
Build a Canary Rollout for a Production Recommender. Advanced challenge in code. Writing production code that solves real engineering problems, earn a blockc...
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.
This is not a coding exercise. It is the work a software engineer does between a Jira ticket and a merged PR. That distinction matters to every hiring manager who has seen candidates solve LeetCode problems and none who have shipped production code under real constraints.
When you finish, you will have something most graduates do not: a real-world deliverable, verified by Ewance, that you can show to a hiring manager and say "I did this. Here is the proof."
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.
ML Engineering and Production ML
Master · Ai Systems
Strong alignment
This challenge maps to ML Engineering and Production ML at the Master level. It sharpens the same practical skills your coursework expects — but in a real industry context with actual constraints and deliverables.
Skills
Skills you'll demonstrate.
Each one shows up on your verified credential.
- Canary Deployment
Apply canary deployment to solve real industry problems and demonstrate production-level capability.
- Kubernetes
Apply kubernetes to solve real industry problems and demonstrate production-level capability.
- Ab Testing
Apply ab testing to solve real industry problems and demonstrate production-level capability.
- Prometheus
Apply prometheus to solve real industry problems and demonstrate production-level capability.
- Model Rollout
Apply model rollout to solve real industry problems and demonstrate production-level capability.
- Sequential Testing
Apply sequential testing to solve real industry problems and demonstrate production-level capability.
Careers
Career paths this challenge builds toward
Completing this challenge demonstrates skills that transfer directly to these roles:
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