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Agentic AI Atlas · Feature Store Management
workflow:feature-store-managementa5c.ai
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workflow:feature-store-management

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Feature Store Management overview

Maintains the shared feature store — registering new features, monitoring freshness SLAs, decommissioning stale features, and ensuring consistent feature computation between training and serving. Excludes feature engineering research.

WorkflowOutgoing · 11Incoming · 1

Attributes

displayName
Feature Store Management
workflowKind
data
triggerType
continuous
typicalCadence
continuous
complexity
single-team
description
Maintains the shared feature store — registering new features, monitoring freshness SLAs, decommissioning stale features, and ensuring consistent feature computation between training and serving. Excludes feature engineering research.

Outgoing edges

applies_to_domain2
  • domain:data-science·DomainData Science
  • domain:ml-ops·DomainMLOps
involves_role3
  • role:ml-engineer·RoleMachine Learning Engineer
  • role:data-scientist·RoleData Scientist
  • role:platform-engineer·RolePlatform Engineer
performed_by_org_unit2
  • org-unit:ml-platform-team·OrgUnitML Platform Team
  • org-unit:data-platform-team·OrgUnitData Platform Team
requires_skill_area2
  • skill-area:python-data-pipelines·SkillAreaPython Data Pipelines
  • skill-area:kafka-stream-processing·SkillAreaKafka Stream Processing
triggers_responsibility2
  • responsibility:data-quality-monitoring·ResponsibilityData quality monitoring
  • responsibility:slo-definition·ResponsibilitySLO definition

Incoming edges

follows_workflow1
  • stack-profile:feature-store-mlops·StackProfileFeature Store & MLOps Stack (Feast, MLflow, BentoML, K8s, Prometheus)

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