Introducing the Shiny Production with AWS Book
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
It’s the new year. Moving into 2020, I’d like to introduce you to the BRAND NEW Shiny Production with AWS Book. This book details the enterprise-grade process for deploying, hosting, and maintaining Shiny
web applications using AWS
, Docker
, and Git
. It contains 24 Chapters covering the entire deployment process!
This is part of a series of articles on key Data Science skills for 2020 and beyond:
- 5 Data Science Technologies for 2020 (and Beyond)
- AWS Cloud – 14% Share, 400% Growth
- Docker – 4000% Growth
- Git Version Control – 8% Share, 150% Growth
- Shiny Web Applications (Coming Soon)
- H2O Automated Machine Learning (AutoML) (Coming Soon)
- [NEW] – Shiny Production with AWS Book
Businesses need applications to run
My prognostication for 2020 and beyond is simple – Businesses need apps to run.
As business demands for apps has accelerated, this shift has driven a massive increase in demand in technologies for deploying applications. According to Indeed’s Hiring Lab, the 5-year demand for app and cloud technologies has skyrocketed:
- AWS Cloud – 14% Share, 400% Growth
- Docker – 4000% Growth
- Git Version Control – 8% Share, 150% Growth
This growing technology demand is proof that businesses need apps in a bad way. Learn how to deploy applications, and your career will accelerate. Not to mention the massive benefit to your organization.
Problem: No one teaches Data Scientists how to deploy apps
Traditionally, production tasks were performed by Developer Operations (DevOps). The problem with this approach is that 99% of applications are low-to-moderate usage. Involving DevOps in deploying low-usage data science apps takes them away from deploying and maintaining critical applications (super-high usage, customer-facing, mission-critical). Further, it slows down your organizations productivity – getting new apps out becomes a bottleneck.
Production – Deployment Becomes the Bottleneck
The problem is that no one teaches Data Scientists how to deploy applications. Data Scientists become stuck at the Last Mile – The series of tasks related to getting your app from your computer to the cloud or your organizations server.
In 2020 and beyond, Data Scienctists need to meet the accelerating demands of the business This is a new challenge. To meet accelerating demands of the business, these “Last Mile” tasks are ones that Data Scientists can do and must learn how to do to fast-track the organization’s ability to produce, deliver, and use data-driven applications with low-to-moderate usage (99% of business apps).
Solution: Shiny Production with AWS Book and Course
The goal of the Shiny Production with AWS Book is to detail the “Last Mile” – A set of tasks required to deploy Full-Stack Shiny
Applications into Production.
Software Deployment Workflow
The Book Does Not Teach Development
See the Shiny Developer with AWS Course for Develoment and Deployment
I do not teach shiny
development in this book. Only application deployment. To fully replicate the materials in the book, you will need to take the Shiny Developer with AWS Course to develop:
- The Full Stack Stock Analyzer application with
Shiny
,Bootstrap
, andMongoDB
, and - The Application Library containing full-text search and app tagging capabilities.
My recommendation:
Take the Shiny Developer with AWS Course if you need to learn every detail of becoming a Shiny
Developer with AWS
. Or better yet, take the NEW 4-Course R-Track System to go from beginner to expert in 6-months or less.
Stock Analyzer Application
A full-stack web application that uses MongoDB
for storing and managing user data (roles, passwords, and settings). The application enables users to store information on their favorites stocks using the tidyquant
API. The application is built with Shiny
and hosted on EC2. Make this app.
Stock Analyzer – Full-Stack Data Science App
Make this App
Application Library
A meta-application that is stored at the base URL to help users navigate to applications. The Application Library includes functionality for Full Text Search and selecting applications by Tags, making it easy to find the apps your users need. Make this app.
Application Library – Full-Text Search for Finding Apps
Make this App
Where the book picks up
This book covers that last mile: Production. You will learn proven strategies for deploying enterprise shiny
applications. This guide follows the “Part 4 – Production with AWS” portion of my Shiny Developer with AWS Course.
Learn Shiny App Development and Deployment
If you are ready to learn how to develop and deploy Shiny
Applications in the cloud using AWS
, then I recommend my NEW 4-Course R-Track System. This system of premium courses is designed to take you from beginner to expert within 6-months.
I look forward to providing you the best data science for business education.
Matt Dancho
Founder, Business Science
Lead Data Science Instructor, Business Science University
R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.