scalo vs hyperi-rustlib vs rastreo

Self-regulating runtime for hyperscale-grade data-plane services. Config, logging and metrics come pre-wired as singletons you just use -- then CLI, health probes, transport, backpressure, adaptive scaling and deployment contracts all build on that integration. Batteries included, idiomatic Rust. Sibling to the scalo package on PyPI (scalo-py).

There's plenty of sage advice out there about how to run Rust services in production at scale — config cascades, structured logging, masking secrets, multi-backend secrets management, Prometheus, OpenTelemetry, Kafka transports, tiered disk-spillover sinks, adaptive worker pools, graceful shutdown — but almost none of it as code you can just install and use. This is that code. Opinionated, drop-in, working out of the box. The patterns from blog posts, watercooler chats and beers with your Google mates as actual library — not a framework you assemble from twenty crates and 8 weeks of munging.

CLI for rastreo — enrichment-aware network discovery