DevOps-Security-Agent-Skills/devops/ai/model-registry-governance/SKILL.md

name, description, license, metadata

name	description	license	metadata
model-registry-governance	Establish model registry standards, governance controls, metadata schemas, approvals, and lifecycle policies for enterprise AI deployments.	MIT	author version devops-skills 1.0

Model Registry Governance

Create a trustworthy system of record for model artifacts, prompts, adapters, and evaluation evidence.

Core Principles

• Traceability: every production model maps to source code, data snapshot, and evaluation results.
• Reproducibility: builds are deterministic with pinned dependencies.
• Policy-driven promotion: no manual bypass for critical safety checks.
• Lifecycle hygiene: stale, vulnerable, or unowned models are retired automatically.

Required Metadata Schema

Track at minimum:

• Model name, semantic version, checksum, and storage URI
• Base model lineage and fine-tune method
• Training/eval datasets and time windows
• License, allowed use cases, prohibited use cases
• Security risk rating and mitigation controls
• Owner, backup owner, and escalation contact

Approval Workflow

1. Registration request created from CI.
2. Security checks (artifact scan, dependency scan, provenance).
3. Evaluation package uploaded (quality, toxicity, jailbreak, bias, latency, cost).
4. Required approvals: platform + product + security (as policy dictates).
5. Promotion to stage/prod based on signed decision record.

Lifecycle States

• draft: internal experimentation.
• candidate: passed baseline tests.
• approved: authorized for production rollout.
• deprecated: replacement announced, new usage blocked.
• retired: no serving allowed, archived for audit.

Governance Policies

• Reject artifacts without SBOM/provenance.
• Block promotion if known critical CVEs remain unresolved.
• Require refreshed evals after prompt/template changes.
• Expire approvals after a configurable period (for example 90 days).

Audit Readiness

Maintain immutable records of:

• Who approved and when
• Which policy checks executed
• Which exceptions were granted
• What model/version served each customer request window

Related Skills

• sbom-supply-chain - Provenance and signing
• policy-as-code - Enforce governance with policy engines
• llm-fine-tuning - Version adapters and training outputs