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godzilla.dev
Self-hosted crypto funding rate arbitrage & market making
7 followers
Self-hosted crypto funding rate arbitrage & market making
7 followers
godzilla.dev is an open-source C++/Python framework for self-hosted crypto funding rate arbitrage and ultra low-latency market making, with enterprise private deployment. Unlike cloud bot platforms, strategies, API keys, and execution all run on your own infrastructure. Python for strategy logic, C++ for the execution path. Install via pip (godzilla.dev on PyPI), extend with your own signals, deploy anywhere. In production use at institutional trading desks.
Have you considered adding built-in support for funding rate forecasting models out of the box, maybe something like a simple LSTM or linear regression wrapper that plugs into the Python strategy layer? Would save a lot of boilerplate for anyone coming in fresh and wanting to test signal ideas quickly.
@ensar33961 Interesting idea. My instinct is to keep forecasting models out of core — signal research styles vary too much and I don't want to bless one approach — but a clean interface where any predictor plugs into the Python strategy layer, plus a linear-regression reference implementation as a template, feels right. Boilerplate reduction without opinion lock-in. Would that cover what you had in mind?
Congrats on the launch, running strategies on your own infra is a big deal for anyone worried about custody. One thing that would help adoption is a built-in backtest harness that replays historical funding rates and order book snapshots against the same C++ execution path, so you can validate signal changes without touching live capital. Would also make new strategy onboarding way less stressful.
@turgay76925 Thanks! You and Serhat independently landed on the same request, which tells me the priority. Same execution path for backtest and live is exactly the right constraint — otherwise the backtest lies to you.