MLOps for OT: Monitoring & Rollback Playbook
Operational playbook for deploying, monitoring and safely rolling back machine learning models in industrial environments.
Sections: deployment checklist (canary tests, operator training), model health metrics (drift, latency, coverage), alert thresholds and owner, automated rollback triggers, data-labeling loops, and compliance logging. Include sample dashboards and brief escalation flows.
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