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MLOps

Reviewed 19 July 2026Canonical definitionPart of: Agent Observability Terms →

MLOps (Machine Learning Operations) is the discipline of deploying, monitoring, and managing machine learning models in production. For agentic AI, MLOps extends to managing prompts, tools, policies, and multi-model orchestration alongside traditional model lifecycle.

§01 / QUESTIONSterm: MLOps
Questions

Common questions.

What are MLOps?

MLOps (Machine Learning Operations) is the discipline of deploying, monitoring, and managing machine learning models in production.

How do MLOps work?

For agentic AI, MLOps extends to managing prompts, tools, policies, and multi-model orchestration alongside traditional model lifecycle.

Which terms are related to MLOps?

Closely related concepts include Model Lifecycle Management, Distributed Tracing (Agent), Model Endpoint, AI Provenance. Each is defined in the Prefactor glossary.

§02 / RELATEDnext: where this fits
Keep reading

Where this fits.

See how every agent performs, and make it better

Prefactor helps teams observe, evaluate, and improve their AI agents in production, across every framework and provider.