About the course
This course focuses on creation of UI dashboard for analytics with the help of Node, Flux, React, and webpack
Apache Mesos is an open source cluster manager that handles workloads in a distributed environment through dynamic resource sharing and isolation. Apache Mesos abstracts CPU, memory, storage, and other compute resources away from machines (physical or virtual), enabling fault-tolerant and elastic distributed systems to easily be built and run effectively.
This course begins with undertaking Airbnb case study and understanding DeltaSync at Airbnb. Then, you look at another case study wherein you will learn Fenzo with Mesos. Also, you will learn reactive streams with Redux dispatcher and the Gulp Task Runner concurrency issue. Next, you will learn about Soliton Automata model and will perform dynamic resource allocation in a noArch environment. Also, you will be familiar with Cassandra sink and network flows. Moving ahead, you will learn multitenancy with druid to power user-facing data applications. Also, you will undertake heron case study and learn job scheduling and dynamic tenancy allocation. Finally, you will learn Airflow and Webpack in Mesos.
The code files are placed at this link https://github.com/PacktPublishing/Mesos-Analytics
Style and Approach
In this course, we will learn how to set-up Zookeeper and Marathon, to get started with creating a webpack application with NodeJS, Google MaterialUI, and Facebook’s ReactJS.
What You Will Learn
- Understand Airbnb case study and learn DeltaSync at Airbnb
- Learn Fenzo with Mesos with the help of a case study
- Learn reactive streams with Redux dispatcher and the Gulp Task Runner concurrency issue
- Learn Soliton Automata model
- Perform dynamic resource allocation in a noArch environment
- Get familiar with Cassandra sink and network flows
- Undertake heron case study and learn job scheduling and dynamic tenancy allocation
- Understand what is dynamic tenancy allocation
- Learn Airflow and Webpack in Mesos
Karl Whitford has been involved in the tech industry for 10 years as a software engineer. He has a background in statistical machine learning, deep learning, and A.I. from Columbia University. He also has knowledge of computational physics/mathematics from DePaul University and UT Austin. He is a professional in the fields of game A.I, compression, machine learning, and distributed cluster computing. Karl is an open source contributor to SMACK, Pancake Stack (PipelineI/O), and Pregel-Mesos, among others. He has previous work experience with Microsoft, Coca Cola, and Unilever to name a few; he is also an indie game developer and founder of Esquirel (Black-Squirrel) Studios in San Francisco, California. He was also handpicked by UploadVR as "one to watch" and featured at Mountain View’s 2016 VR Showcase.