Model Registry & CI/CD for ML
A model registry with automated evals, canary rollout, shadow traffic, and one-click rollback for ML services.
PythonKubernetesCI/CDAWS

Highlights
- Signed model artifacts with reproducible training metadata.
- Canary and shadow deploys with automated eval gates.
- One-click rollback tied to the last known-good registry entry.
Outcomes
- Reduced bad-model incidents in production to zero over 9 months.
- Cut release cycle for ML services from monthly to daily.
Stack
- Python
- Kubernetes
- Docker
- AWS
- CI/CD