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AI & Machine Learning · Foundational

Machine Learning Operations (MLOps)

Practices and tooling that apply DevOps principles to build, deploy, monitor and maintain ML models reliably in production.

Definition

MLOps covers data and model versioning, reproducible pipelines, experiment tracking, model registries, CI/CD for models, automated retraining, monitoring and governance. Its goal is to move models from experimentation to production quickly and keep them performing. LLMOps extends these practices to prompts, RAG pipelines and LLM evaluation.

Exam tip

Automated retraining triggered by drift detection is the hallmark of mature MLOps.

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