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UnitFail Notifier systemd failure alerts

#python#alerts#monitoring#logging#cli

Silent service failures and crashing background daemons on production Linux hosts often go unnoticed until customers experience downtime, while manually monitoring systemctl…

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requirements.txt — list of dependencies

What's in the ZIP

  • Python source, README and requirements

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More details

Silent service failures and crashing background daemons on production Linux hosts often go unnoticed until customers experience downtime, while manually monitoring systemctl states across multiple machines is inefficient. Without automated notification hooks, developers must constantly inspect journalctl logs to catch restart loops, crashed workers, and missed timer schedules. The tool installs a global systemd OnFailure drop-in configuration and a dedicated alert template featuring recursion protection to prevent notification loops. It queries systemctl to detect failed units, inspect exit codes, track restart counts, and catch stalled timers. For every incident, it extracts the latest journalctl log lines and dispatches structured diagnostic payloads through generic HTTP webhooks, ntfy push servers, or standard SMTP email. Example: Run python3 unitfail_notifier_systemd_fail.py --help to review the complete command-line interface. Trigger a manual alert test by running python3 unitfail_notifier_systemd_fail.py notify --unit nginx.service --config /etc/unitfail/config.json to assemble unit properties and transmit recent journal lines directly to configured notification channels. This tool does not automatically restart crashed services, repair corrupted unit definitions, or support alternative init systems like SysVinit or OpenRC.

UnitFail Notifier systemd failure alertsMonitoring

Quick Start

Runs on Python 3.9 or newer. Check requirements.txt in the ZIP and install what it lists with pip install -r requirements.txt.

1 — Install the dependencies

pip install -r requirements.txt

2 — Run it

How agents & programs use it: Install its requirements in a virtual environment; scripts and AI agents can then run it as a subprocess.

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