Lesson 4/6: Deployment of Kubernetes

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)

If you weren’t in attendance for the first session, please follow the instructions in this document to set up your environment before arriving: https://docs.google.com/document/d/1ayIjeM0SUA3BuF2CTOhcsyVgL9MP13NVHkPlrw7_MSQ/edit

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 Kubernets in the Cloud
Lesson 6: Putting it all Together

Thanks to our friends at Mozilla for hosting!