Towards Kubeflow 1.0, Bringing a Cloud Native Platform For ML to Kubernetes
In December of 2017, a small number of folks from a handful of companies introduced Kubeflow; an open, cloud native platform for machine learning. The project has gained a lot of momentum with hundred …
| Talk Title | Towards Kubeflow 1.0, Bringing a Cloud Native Platform For ML to Kubernetes |
| Speakers | David Aronchick (Head of OSS Machine Learning, Microsoft), Jeremy Lewi (Senior Software Developer, Google) |
| Conference | KubeCon + CloudNativeCon Europe |
| Conf Tag | |
| Location | Barcelona, Spain |
| Date | May 19-23, 2019 |
| URL | Talk Page |
| Slides | Talk Slides |
| Video | |
In December of 2017, a small number of folks from a handful of companies introduced Kubeflow; an open, cloud native platform for machine learning. The project has gained a lot of momentum with hundreds of committers, thousands of commits and stars. With the traction, many companies are asking if can Kubeflow help them bring their ML practices to the next level, and where Kubeflow is going next. This talk will discuss the growth of the Kubeflow ecosystem and its place in the lifecycle of ML development. We will provide concrete examples of how Kubeflow is developing new applications such as Katib for hyperparameter tuning and Kubeflow pipelines to address gaps in the landscape. We will also show how we are using Kubernetes and Cloud Native technologies to glue these applications into a cohesive platform, and where Kubeflow will be going next.
