II.
SkillArea overview
Reference · liveskill-area:ci-cd-ml-pipelines
CI/CD for ML Pipelines overview
Applying delivery automation to ML workflows - train/validate/register stages, deployment gates, artifact promotion, and rollback control.
Attributes
displayName
CI/CD for ML Pipelines
description
Applying delivery automation to ML workflows - train/validate/register
stages, deployment gates, artifact promotion, and rollback control.
domains
expertiseLevels
- intermediate
- expert
Outgoing edges
applies_to2
- domain:ml-ops·DomainMLOps
- specialization:devops-sre-platform·Specialization
requires_skill_area2
- skill-area:deployment-infrastructure-management·SkillAreaDeployment and Infrastructure Management
- skill-area:ml-pipeline-testing·SkillAreaML Pipeline Testing
Incoming edges
lib_requires_skill_area3
- lib-agent:ai-agents-conversational--agent-deployment-engineer·LibraryAgentagent-deployment-engineer
- lib-agent:data-science-ml--ml-architect·LibraryAgentml-architect
- lib-skill:data-science-ml--kubeflow-pipeline-executor·LibrarySkillkubeflow-pipeline-executor
prerequisite_for_learning1
- skill-area:machine-learning·SkillAreaMachine Learning
requires_expertise1
- role:machine-learning-ops-engineer·RoleMachine Learning Ops Engineer
requires_skill_area3
- stack-profile:feature-store-mlops·StackProfileFeature Store & MLOps Stack (Feast, MLflow, BentoML, K8s, Prometheus)
- stack-profile:ml-pipeline-stack·StackProfileML Pipeline Stack (PyTorch/TensorFlow, MLflow, BentoML, K8s)
- workflow:model-training-pipeline·WorkflowModel Training Pipeline