Mesos, with its semi-centralized infrastructure, sustains the skeleton of Silicon Valley’s Netflix (Fezo), Airbnb (Airflow), Heroku, and Apple to name a few, and has established itself as a staple in any automated machine learning pipeline and distributed heterogeneous data pruning.

In this course, we will learn the foundation of Mesos within the automated pipeline on fault-tolerant cluster semaphores. We will set up a virtual cluster running Marathon and Zookeeper and a concurrent Docker application. We will establish a master-slave infrastructure, experience real-time debugging, and learn how to automate cluster arbitration via Soliton automata. We will then see an iterative queue manager for indexed tasks dispatched concurrently inside a poset topology.

Key Features

• Launch a webserver with Go and Docker
• Gain exposure to an automated machine learning pipeline
• Validate your learning with assessments and quizzes

Who this course is for

This course is targeted at data science professionals looking to get started with Mesos to integrated it in their machine learning pipeline.