Consultation
MLOps Handoff Advisory
Clarify who owns training jobs, monitoring alerts, and rollback when an ML feature leaves the research notebook.
Advisory sessions map your current training and serving path, then define lightweight ownership for retraining triggers, drift signals, and incident response — without prescribing a particular cloud vendor stack.
Typical outcomes
- Ownership matrix for train, serve, and monitor
- Alert triage outline tied to on-call practice
- Rollback checklist for feature flags