MLOps stands for machine learning operations. It comprises a set of practices and tools that combine DevOps principles to the development cycle of artificial intelligence applications.

Kubeflow is a powerful open-source platform that uses Kubernetes to make MLOps workflows simple, portable, and scalable. It allows MLOps professionals to break down your entire ML process (from data preparation to model training and deployment) into individual steps and then orchestrate them using Kubernetes containers.

This talk will comprise some options and strategies to create and run MLOps pipelines easily and securely with Kubeflow Pipelines, as it emerges as the de facto alternative to implement the deployment, monitoring, and management of machine learning workflows. The session includes code samples comprising a Java application and an Oracle Database.