Abstract: The past few years has seen growth and adoption of container technology for cloud native applications and devops and agility. Kubernetes has emerged as the defacto hybrid cloud container platform.
There is considerable interest in bringing data science workloads and workflows to OpenShift - Red Hat's Kubernetes distro. Data Scientists benefit by having a choice of public and private clouds and capabilities and technologies they bring for their experiments. Data and ML engineers benefit by able to scale and bring data science workloads and workflows to production.
We propose a hands on workshop where we show the attendees on how to deploy open source technologies for data science on Kubernetes - technologies such as Jupyter, Kafka, Spark, TensorFlow, Ceph etc. This workshop will be based on our experiences with this for Open Data Hub.
Bio: Coming Soon
Director of Engineering | Red Hat