tutorial

This guide is for setting up a local Kafka environment in a single machine quickly. A properly configured Kafka cluster is laborious to set up and has a lot of dependencies like Apache ZooKeeper etc. and that can be disconcerting if you just want to develop locally or put together a proof of concept prototype. This is obviously not the way to set up a production Kafka cluster as there is no security, redundancy, fault tolerance, scaling and a host of other requirements for a production grade environment.

Data Science Getting Started Platform To get started quickly with data science, I started looking at python and its powerful set of libraries (like pandas, NumPy, Scikit-Learn, etc) that makes data analysis easier. I wanted to have a platform that is accessible over the internet so I can get to it from any laptop/PC that has internet access. I decided to get a minimal Virtual Private Server (VPS) that supports containers so I can set up a Docker container with all the languages and frameworks/libraries/tools and mount a path on the VPS that contains all the projects I am working on, which will be checked in to git.