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godzilla.dev
Self-hosted crypto funding rate arbitrage & market making
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.
Hi Product Hunt! I'm kx, builder of godzilla.dev.
I built this because I kept hitting the same wall: cloud-based trading bot platforms are great for getting started, but once real capital is involved, you don't want your API keys and strategy logic living on someone else's servers — and you can't fix latency you don't control.
godzilla.dev is fully self-hosted. The execution path is C++ for ultra low-latency market making; the strategy layer is Python so iteration stays fast. The main use cases are funding rate arbitrage on perpetuals and market making, and it's been running in production at a top-10 derivatives exchange for three years across liquidity provision and hedging.
It's open source — pip install godzilla.dev gets you started. Happy to answer anything about the architecture or the funding rate arb strategy design.
A backtesting harness that replays historical funding rate data against the C++ execution path would save so much time. Right now it feels like you have to be live to really validate anything, and a solid simulated venue for paper trading the latency-sensitive strategy logic side-by-side with real market snapshots would make the whole framework way more approachable for newer contributors.
Love that the execution path lives in C++ while strategy logic stays in Python, that's the right split for latency-sensitive work without making iteration a pain. Self-hosting the keys and strategies feels overdue for this space.
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.
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.
godzilla.dev was submitted on Product Hunt and earned 0 upvotes and 5 comments, placing #73 on the daily leaderboard. 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.
godzilla.dev was featured in Open Source (68.6k followers), Crypto (39.7k followers), GitHub (41.3k followers) and Web3 (7.8k followers) on Product Hunt. Together, these topics include over 55.2k products, making this a competitive space to launch in.
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