Devconf.US

Jupyter extension for executing kubeflow pipeline seamlessly
08-14, 11:20–11:55 (US/Eastern), Conference Auditorium (capacity 260)

As an enthusiastic contributor to the open-source project Elyra, I am excited to introduce you to the seamless integration of Elyra with Kubeflow 2.0. Elyra, a powerful toolkit designed to enhance the usability of Kubeflow Pipelines, brings a host of features to streamline the development and deployment process of machine learning workflows on Kubernetes. With Elyra, users gain access to a user-friendly visual editor, support for multiple programming languages, and advanced collaboration tools, all tailored to enhance the efficiency and effectiveness of building and deploying machine learning models within the Kubeflow ecosystem. Let's explore how Elyra can elevate your experience with Kubeflow 2.0 and empower you to unleash the full potential of your machine learning projects.

Senior Software Engineer working in the OpenShift AI space. Active contributor in OpenDatahub, Elyra, and Kubeflow open source community. My interests lies in Artificial Intelligence, DevOps, Backend and Cloud Computing.