---
title: MLOps
description: "MLOps: Scaling AI through automated pipelines for reliable, continuous model deployment and monitoring."
---

[Glossary ](https://www.o2oh.com/glossary)

# [MLOps](https://www.o2oh.com/glossary/mlops)

 Written by [one to ONE Holdings](https://www.o2oh.com/glossary/author/one-to-one-holdings) | Mar 27, 2026 10:28:10 AM

MLOps, or Machine Learning Operations, is a multidisciplinary engineering discipline that ensures reliable and efficient deployment of machine learning models in production.　It combines Data Engineering, [Machine Learning](https://www.o2oh.com/glossary/machine-learning-ml), and DevOps to build automated pipelines for continuous integration, delivery, and monitoring. By formalizing lifecycle management, MLOps addresses "technical debt" in AI systems and maintains model performance despite data drift. This approach is vital for converting experimental prototypes into scalable, industrial-grade software.

[View full post](https://www.o2oh.com/glossary/mlops)

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