Shinken: A Nagios-Like Monitor That Grew Up Nagios is still everywhere — in legacy racks, old sysadmin playbooks, and default configs from 10 years ago. But anyone who’s had to scale it knows how quickly it starts to choke. Shinken showed up to fix that. Same checks, same config structure — but with an actual distributed architecture and a Python core that doesn’t feel like it was frozen in time.

It’s modular. It runs daemons for scheduling, polling, notifications, and brokering. You can split

Octopussy: When You Just Need Log Alerts That Make Sense There’s a flood of tools out there for logs. Some collect. Some store. Some analyze. And then there’s Octopussy — which does just one thing well: parses logs and alerts when something looks off. No big data, no dashboards with dancing graphs. Just fast, actionable event detection on top of syslog streams.

Originally developed in France (and still proudly carrying that design philosophy), Octopussy isn’t about reinventing log management. I

Meerkat: Lightweight Log Parsing for People Who Still Prefer grep In a world flooded with log analysis stacks, Meerkat feels like a breath of fresh air — small, specific, and fast. It’s not built to be a dashboard. It’s not trying to stream logs into a data lake. What it does is parse structured or semi-structured logs, match rules, and generate alerts or summaries — all without requiring a server backend or a web UI.

It’s a command-line tool, meant to be chained, scripted, embedded into cron j

LogAnomaly: Statistical Log Analysis Without the Rules LogAnomaly isn’t a log collector, a SIEM, or an alternative to Splunk. It’s a focused tool for detecting outliers in log files using statistical models — not pattern matching. No predefined rules, no signature sets. Instead, it builds a baseline of “normal” behavior from your logs and flags anything that deviates too much from that baseline.

The typical use case: logs are flowing, everything looks fine on the surface, but something unusual