mlops
Installation
SKILL.md
Plan and run MLOps
Overview
Router skill for operationalizing ML and LLM/GenAI workloads on Snowflake. It covers the process and governance layer — when to promote, what gates to enforce, what to monitor, how to roll back. It does not cover SDK-level code (model registration, feature store APIs, training loops) — that belongs to the machine-learning skill.
This skill applies to traditional ML and GenAI (prompt management, RAG, fine-tuning, agentic apps). There is no separate "LLMOps" — LLM operationalization is part of MLOps with workload-specific adaptations.
Scope split
| Question | Owner |
|---|---|
| When should I promote a model? What gates must it pass? | mlops |
| How do I register a model or deploy an endpoint? (code) | machine-learning |
| What should I monitor after deployment? When to roll back? | mlops |
| How do I set up Feature Store / Cortex Search? (code) | machine-learning |
| How should I govern Feature Store / Registry across environments? | mlops |
| How do I train / fine-tune / build RAG? (code) | machine-learning |
| How should I operationalize training across environments? | mlops |