Kubernetes in Practice

Goal

1. Use Kubernetes
2. ML on Kubernetes
   1. port MapReduce Lite to Kubernetes
   2. develop Spark for Kubernetes
3. Kubernetes educations
4. Running Kubernetes events
   1. colleague courses
   2. online courses
   3. report successful stories
   4. conferences

Book

Part 1. Running Kubernetes

1. Run on a Single Linux Box

2. Run on Linux Boxes using Vagrant

3. Run on Debian Boxes on GCE

4. Run on Debian Boxes on AWS

5. Run on CoreOS using Vagrant

6. Run on CoreOS using GCE

7. Run on CoreOS using AWS

8. Run on CoreOS using Azus

Part 2. Computing on Kubernetes

1. Develop MapReduce
2. Run Hadoop
3. Port Spark

Part 3. Big Data on Kubernetes

1. Running Storm
2. Running Kafka
3. Running HBase

Part 4. Machine Learning on Kubernetes

1. Collaborative Filtering
2. Frequent Itemset Mining
3. Matrix Decomposition
4. Spectral Clustering
5. Graph Mining
6. Latent Topic Modeling