Kubernetes Seattle: Machine Learning and a Deep Dive into Network Policies

Quantum - 506 2nd Ave, Suite 900 Seattle - View Map Seattle
Wed, Jan 17, 2018, 6:30 PM (PST)

About this event


The meetup will be on Wednesday, January 17, 2018 and starts at 6:30 with food/beverages, speakers start at 7:00.

SPONSORED: Spin up and manage a Kubernetes cluster with Istio at AWS, GCE, GKE, DigitalOcean or Azure today w Stackpoint.io (https://stackpoint.io/clusters/new?solution=istio&utm_source=meetup&utm_medium=event_page&utm_campaign=sea_k8s)

If you would like to present or host feel free to reach out to me on meetup.com or Twitter @baldwinmathew.


6:30 - 7:00 - Arrive / Social

7:00 - 7:30 - Building Google's ML Engine from Scratch with GPUs, Kubernetes, Istio, and TensorFlow - Chris Fregly

Applying my Netflix experience to a real-world problem in the ML and AI world, I will demonstrate a full-featured, open-source, end-to-end TensorFlow Model Training and Deployment System using the latest advancements from Kubernetes, Istio, and TensorFlow.

In addition to training and hyper-parameter tuning, our model deployment pipeline will include continuous canary deployments of our TensorFlow Models into a live, hybrid-cloud production environment.

This is the holy grail of data science - rapid and safe experiments of ML / AI models directly in production. Following the Successful Netflix Culture that I lived and breathed (https://www.slideshare.net/reed2001/culture-1798664/2-Netflix_CultureFreedom_Responsibility2), I give Data Scientists the Freedom and Responsibility to extend their ML / AI pipelines and experiments safely into production.

Offline, batch training and validation is for the slow and weak. Online, real-time training and validation on live production data is for the fast and strong. Learn to be fast and strong by attending this meetup.

7:30 - 8:00 - Securing clusters with Kubernetes Network Policies - Ahmet Alp Balkan

Learn about Network Policies, a Kubernetes feature became stable in v1.7. Network Policies let you write rules to restrict incoming and outgoing traffic for Pods in a cluster.

8:00 - 8:30 - Wrap-up / Depart


Chris Fregly is Founder and Research Engineer at PipelineAI, a Streaming Machine Learning and Artificial Intelligence Startup based in San Francisco. He is also an Apache Spark Contributor, a Netflix Open Source Committer, founder of the Global Advanced Spark and TensorFlow Meetup, author of the O’Reilly Training and Video Series titled, "High Performance TensorFlow in Production."

Previously, Chris was a Distributed Systems Engineer at Netflix, a Data Solutions Engineer at Databricks, and a Founding Member and Principal Engineer at the IBM Spark Technology Center in San Francisco.

Twitter: @cfregly

Ahmet is a software engineer at Google Kubernetes Engine, working on optimizing the developer experiences. He creates developer tools and tells stories about complicated features.

Twitter: @ahmetb


506 2nd Ave
Suite 900
Seattle, WA


Wednesday, Jan 17
6:30 PM - 8:30 PM (PST)


506 2nd Ave, Suite 900 Seattle