(
Machine
Learning
OPerations) The machine learning life cycle. MLOps applies the practices of DevOps to machine learning. It includes the building, deploying, monitoring and maintenance of machine learning methods, from simple decision trees to advanced neural networks for deep learning. See
DevOps,
AI types and
machine learning.
AIOps
AIOps and MLOps both involve AI but they are not the same. Whereas MLOps covers the full life cycle of machine learning, AIOps is about applying AI to large datacenter operations.
AIOps monitors all servers and activities in the datacenter to identify issues before they become major problems. It also attempts to solve the problems automatically. For example, after detecting a surge of website traffic during holidays, AIOps may automatically scale servers to meet demand.