A Tale of Two Worlds: Canary-Testing for Both ML Models and Microservices
With the rapid and recent rise of data science, organizations are leveraging Cloud Native tools, especially Kubeflow for Data Science. One of the big challenges is how to deploy models in productions …
| Talk Title | A Tale of Two Worlds: Canary-Testing for Both ML Models and Microservices |
| Speakers | Vincent Lesierse (Technical Product Manager, Vamp.io), Jörg Schad (Head of Machine Learning, ArangoDB) |
| Conference | KubeCon + CloudNativeCon Europe |
| Conf Tag | |
| Location | Barcelona, Spain |
| Date | May 19-23, 2019 |
| URL | Talk Page |
| Slides | Talk Slides |
| Video | |
With the rapid and recent rise of data science, organizations are leveraging Cloud Native tools, especially Kubeflow for Data Science. One of the big challenges is how to deploy models in productions using similar practices like A/B testing and Canary-releasing which have proven successful for microservices. How to easily test and update your data models to production without impacting users? These are typical challenges a data-scientist will encounter when self-deploying and -managing the lifecycle of data models in production. In this talk Vincent Lesierse and Jörg Schad are going to show how experiences learned from releasing Microservices on Kubernetes can be applied to the world of ML Models, and where the deployment and lifecycle management of these ML Models differs from Microservices.
