Rust for Data Source Monitoring and Automation

Stand up production-grade monitoring for Rust services and automate the operational tasks that keep them running. This intermediate course pairs systems engineering practice with the modern Rust toolchain to instrument, observe, and operate data infrastructure. Module 1 walks through the full monitoring stack: logging versus metrics, the four golden signals, push and pull collection strategies, the ELK stack on Linux, Prometheus and Grafana for metric collection and visualization, and the `tracing` crate for structured Rust logs. A parallel AI-augmented track introduces Amazon Q Developer for code assistance. Module 2 builds Rust CLIs for system automation: filesystem traversal with walkdir and glob, log parsing with regex and flate2, wrapping external commands with `std::process::Command`, and a graded compliance utility that crawls JSON-defined rules and exits non-zero on violations — drop-in CI/CD ready. Throughout, learners pair the standard tooling with AWS Bedrock prompt management for AI-augmented operations.