From Jupyter Notebook to Production: ML Deployment Guide
January 1, 1970
15 min read
MLOpsDeploymentDevOps
The real gap
The hard part isn’t training a model. It’s making inference reliable, observable, and cheap.
Minimal production checklist
- Deterministic preprocessing (versioned)
- Model + feature versioning
- Canary + rollback
- Monitoring: latency, error rate, drift proxies
- Automated evaluation on fresh data