Lesson 4/6: Deployment of Kubernetes

Back by popular request, this will be your LAST chance to participate in this 6 part series before we graduate to the next level of content. Thanks to our friends at Mozilla for hosting!

You will learn:

Overview

• What is Kubernetes and what is the main purpose behind it (ease of deployment, management and scaling)

• Networking (the basics of it, and why it’s hard to do networking of Docker containers without Kubernetes)

Deploying Kubernetes

• Quick overview of the infrastructure (API, nodes, network provider, ie. flannel)

• Using Kubeadm to initialize and join nodes to a cluster

• Explain why it’s a bad idea to have the Kubernetes master participate as a node in the cluster (for security reasons)

Using Kubernetes

• Basic overview of the different workload types (Daemonsets, Replication Controllers, etc.)

• Basic overview of how services work (and how they integrate with the rest of Kubernetes)

• The structure of the Kubernetes API YAML and how to create resources with it

• Deploy Zeppelin, Spark Master, Spark Slave workloads

• Verify that the work that we’ve done in previous meetups is working correctly on the cluster

• Scale up Spark Slaves to see performance improvements

• Show that we can deploy an arbitrary application and integrate it with our existing framework very easily (such as a distributed database)

Please be on time and bring your laptop. Food and drinks will be served.

Complete Syllabus

Lesson 1: Apache Spark, PySpark, and Zeppelin Intro

Lesson 2: Introduction to TensorFlow

Lesson 3: Machine Learning in TensorFlow

Lesson 4: Deployment of Kubernetes

Lesson 5: TensorFlow and Kubernetes in the Cloud

Lesson 6: Putting it all Together