A single-command torrent-based file distribution system for deploying files to multiple servers simultaneously.
Herd is a torrent-based file distribution system that enables simultaneous file transfers to multiple servers using a single command. It solves the problem of efficiently deploying files across distributed systems by leveraging BitTorrent's peer-to-peer architecture for faster distribution.
System administrators and DevOps engineers who need to deploy files or applications to multiple servers simultaneously, particularly those managing distributed infrastructure.
Developers choose Herd because it simplifies torrent-based distribution with a self-contained tracker, requires minimal dependencies, and offers easy Python integration compared to more complex alternatives like Twitter's original Murder system.
A single-command bittorrent distribution system, based on Twitter's Murder
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Spawns its own tracker in the background, eliminating the need for separate tracker processes as highlighted in the README under 'Differences from Murder', simplifying deployment workflows.
Can be imported as a Python module for easy integration into existing projects, with examples like herd.run_with_opts() provided in the 'Python Integration' section.
Handles both small and large file transfers without limitations, as it was updated from Horde to remove restrictions around large files, per the README.
Requires only Python and argparse (included in Python 2.7+), making setup straightforward with no extra modules, as stated in the 'Requirements' section.
The project is explicitly marked as DEPRECATED with no maintenance or pull requests accepted, as warned at the top of the README, posing risks for production use.
Designed for Python >2.5 and relies on argparse, which may need manual installation for older versions, and lacks native Python 3 support, limiting modern adoption.
Requires key-based passwordless authentication on all target destinations, adding configuration complexity that might not be feasible in secured or heterogeneous environments.