• rstudio::conf 2019
  • 1 Shiny in Production Workshop
  • 2 Introduction to Shiny in Production
    • 2.1 Workshop Objectives
    • 2.2 Workshop Infrastructure
  • 3 Introduction to the Application
    • 3.1 Activity: Explore the Application
  • 4 Application Testing: shinytest
    • 4.1 Testing Options
    • 4.2 Activity: shinytest
  • 5 Profiling: “The most important thing”
    • 5.1 Activity: Profiling
  • 6 Deployment
    • 6.1 RStudio Connect
    • 6.2 Activity: Inital Deployment
    • 6.3 Application Settings
      • 6.3.1 Access
      • 6.3.2 Metadata
      • 6.3.3 Logs
  • 7 Connecting to Data in Production
    • 7.1 The config package
    • 7.2 Environment Variables
    • 7.3 Activity: Databases
  • 8 Load Testing
    • 8.1 Optimization Loop Methodology
    • 8.2 Activity: Load Testing
  • 9 Plot Caching
    • 9.1 When to use plot caching
      • 9.1.1 Using renderCachedPlot
    • 9.2 Activity: Plot cache benchmarking
    • 9.3 Extended Topics
  • 10 Scaling
    • 10.1 RStudio Connect Performance Settings
      • 10.1.1 Content Scheduler
      • 10.1.2 Scheduling Parameters
    • 10.2 Activity: Runtime Settings
    • 10.3 Activity: Admin Dashboard
    • 10.4 Extended Topics
      • 10.4.1 High Availability and Horizontal Scaling
      • 10.4.2 R Markdown Documents with runtime::shiny
  • 11 Alternatives to Shiny
    • 11.1 Plumber
      • 11.1.1 Intro to Plumber
    • 11.2 Activity: Plumber
    • 11.3 R Markdown
    • 11.4 Activity: R Markdown
  • 12 DevOps Philosophy & Tooling
    • 12.1 Integrating Data Science and DevOps
      • 12.1.1 How does data science fit in with the DevOps philosophy?
      • 12.1.2 What do your dev, test and production environments look like?
      • 12.1.3 Does code deployment feel like a high-risk operation?
      • 12.1.4 Can deployments be decoupled from releases?
  • 13 Production Case Studies
    • 13.1 Case Study A: Dev/Test/Prod
    • 13.2 Case Study B: CI, Git, Chef
    • 13.3 Case Study C: Docker
  • 14 Shiny Async
  • Published with bookdown

Supplement to Shiny in Production

Chapter 14 Shiny Async

References and Resouces:

  • Webinar - Scaling Shiny apps with asynchronous programming
  • Webinar Slides
  • Shiny Dev Center Article: Improving scalability with async programming