Appendix C — Lab Map
This chapter aims to clarify the relationship between the assets you’ll make in each portfolio exercise and labs in this book.
Chapter | Lab Activity |
---|---|
Chapter 1: Environments as Code | Create a Quarto site that uses {renv} and {venv} to create standalone R and Python virtual environments. Add an R EDA page and Python modeling. |
Chapter 2: Project Architecture | Create an API that serves a Python machine-learning model using {vetiver} and {fastAPI} . Call that API from a Shiny App in both R and Python. |
Chapter 3: Databases and Data APIs | Move data into a DuckDB database and serve model predictions from an API. |
Chapter 4: Logging and Monitoring | Add logging to the app from Chapter 2. |
Chapter 5: Deployments and Code Promotion | Put a static Quarto site up on GitHub Pages using GitHub Actions that renders the project. |
Chapter 6: Demystifying Docker | Put API from Chapter 2 into Docker Container. |
Chapter 7: The Cloud | Stand up an EC2 instance. Put the model into S3. |
Chapter 8: The Command Line | Log into the server with .pem key and create SSH key. |
Chapter 9: Linux Administration | Create a user on the server and add SSH key. |
Chapter 10: Application Administration | Add R, Python, RStudio Server, JupyterHub, API, and App to EC2 instance from Chapter 7. |
Chapter 11: Scaling Server resources | Resize the server. |
Chapter 12: Computer Networks | Add proxy (NGINX) to reach all services from the web. |
Chapter 13: Domains and DNS | Add a URL to the EC2 instance. Put the Shiny app into an iFrame on the Quarto site. |
Chapter 14: SSL/TLS and HTTPS | Add SSL/HTTPS to the EC2 instance. |