R Markdown + RStudio Connect + R Shiny
summary
Automates scheduled pipelines by publishing Git repos to RStudio Connect via import from Git with a manifest JSON, producing daily JSON logs; injects loggit calls into named R Markdown chunks and uses loggit::read_logs to parse thousands of lines into R data tables; renders and sends structured error emails via blastula when tryCatch detects failures; composes a process-monitoring Shiny app that surfaces chunk timings, error frequency across dev vs prod, and a searchable error table so teams troubleshoot without hunting through raw logs.
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chapters (5)
- 0:00R Markdown, RStudio Connect, R Shiny
- 2:17Automating data processing
- 4:07Error alerts and logging
- 9:56Process monitoring app
- 14:15Summary
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