Agentic AI Atlasby a5c.ai
OverviewWikiGraphFor AgentsEdgesSearchWorkspace
/
GitHubDocsDiscord
iiRecord
Agentic AI Atlas · ML Model Versioning Governance
workflow:ml-model-versioning-governancea5c.ai
Search record views/
Record · tabs

Available views

II.Record viewspp. 1 - 1
overviewjsongraph
II.
Workflow overview

workflow:ml-model-versioning-governance

Reference · live

ML Model Versioning Governance overview

Governs ML model versioning, lineage tracking, and promotion workflows -- auditing model-registry completeness for metadata including training-data snapshots, hyperparameters, and evaluation metrics, validating model-card documentation against organizational standards, reviewing model-promotion gates from experimental through staging to production, enforcing reproducibility requirements by verifying training-pipeline determinism, assessing model-drift monitoring alerts and retraining trigger thresholds, auditing access controls on model artifacts and serving endpoints, and reconciling deployed model versions against the approved model inventory. Produces model governance compliance report and registry hygiene scorecard. Excludes model architecture research.

WorkflowOutgoing · 12Incoming · 0

Attributes

displayName
ML Model Versioning Governance
workflowKind
governance
triggerType
scheduled
typicalCadence
monthly
complexity
cross-team
description
Governs ML model versioning, lineage tracking, and promotion workflows -- auditing model-registry completeness for metadata including training-data snapshots, hyperparameters, and evaluation metrics, validating model-card documentation against organizational standards, reviewing model-promotion gates from experimental through staging to production, enforcing reproducibility requirements by verifying training-pipeline determinism, assessing model-drift monitoring alerts and retraining trigger thresholds, auditing access controls on model artifacts and serving endpoints, and reconciling deployed model versions against the approved model inventory. Produces model governance compliance report and registry hygiene scorecard. Excludes model architecture research.

Outgoing edges

applies_to_domain2
  • domain:ml-ops·DomainMLOps
  • domain:data-science·DomainData Science
involves_role3
  • role:ml-engineer·RoleMachine Learning Engineer
  • role:staff-engineer·RoleStaff Engineer
  • role:engineering-manager·RoleEngineering Manager
performed_by_org_unit3
  • org-unit:ml-platform-team·OrgUnitML Platform Team
  • org-unit:ml-team·OrgUnitML Team
  • org-unit:data-platform-team·OrgUnitData Platform Team
requires_skill_area2
  • skill-area:ml-fine-tuning·SkillAreaML Fine-Tuning
  • skill-area:eval-driven-development·SkillAreaEval-Driven LLM Development
triggers_responsibility2
  • responsibility:review-architecture-changes·ResponsibilityReview architecture changes
  • responsibility:data-quality-monitoring·ResponsibilityData quality monitoring

Incoming edges

None.

Related pages

No related wiki pages for this record.

Shortcuts

Open in graph
Browse node kind