concept#Machine Learning#Platform#Observability#Reliability

Model Serving

Concepts and practices for exposing trained machine learning models to production traffic, focusing on scalability, versioning and observability.

Model serving describes the systems and infrastructure that expose trained machine learning models to production traffic, handling scaling, versioning, routing and observability.

Maturity

Established

Cognitive loadMedium

360° overview

Model Serving

Six perspectives place the building block in context. The numbers show where each perspective continues in the reading path.

The building block at a glance

Model Serving

360°

Classification

2

Complexity: Medium
Impact area: Technical

Technical context

2

Integrations

CI/CD pipeline (e.g., Jenkins, GitHub Actions)

+2

Principles & goals

1

Separation of training and serving runtime

Value stream stage: Run

Use cases & scenarios

4

Use cases: 3
Scenarios: 3

Compromises

3

Risks: 3
Best practices: 3

I/O & resources

4

Inputs: 3
Outputs: 3