Case Study: AI-as-a-Service on Kubernetes at Scale and In Production
AI is popular and yet faces two big challenges in the industry: 1) self-service and automation 2) Use in real production.At the Israel Ministry of Defense we are taking on the challenges with containe …
| Talk Title | Case Study: AI-as-a-Service on Kubernetes at Scale and In Production |
| Speakers | Tushar Katarki (Product Manager, Red Hat), Itay Gabbay (Machine Learning Engineer, MOD Israel) |
| Conference | KubeCon + CloudNativeCon North America |
| Conf Tag | |
| Location | San Diego, CA, USA |
| Date | Nov 15-21, 2019 |
| URL | Talk Page |
| Slides | Talk Slides |
| Video | |
AI is popular and yet faces two big challenges in the industry: 1) self-service and automation 2) Use in real production.At the Israel Ministry of Defense we are taking on the challenges with containers and Kubernetes. We have built AI-as-a-service with open source tools and Kuberentes. Our Data Scientists use the service for data, experimentation and to deliver models into production iteratively with self-service and automation.Using Kubernetes, we are able to run massive machine learning pipelines automatically, and improve our machine learning models. We implemented several principles of AutoML - a wide research area nowadays. Using AutoML & Kubernetes, we can further improve our machine learning models and pipelines - automatically.Come find out how we built our AI service on Kubernetes, issues we ran into and best practices with a live demo and supporting slides.
