So Im a solo developer who has always had an itch for algorithmic trading. Initially I started off learning how to trade algorithmically with Yves Hilpisch book "Python for Algorithmic Trading" after reading that book I was hooked and started building algorithmic trading bots. Initially these were separate python scripts that I ran on my local machine. That was a bad idea cause local machines are not reliable and I wanted to run my bots 24/7 365. In my actual career im a software engineer with experience in building distributed systems and fault tolerant web applications.

I wasn't interested in deploying my code to managed services like MetaTrader, CTrader or QuantConnect etc because I wanted to have full control over my code and the environment it runs in. I also wanted to be able to run my bots in any programming language I wanted, not just Python. Sometimes I wanted to prototype a bot in Python and then rewrite it in C++ or Rust for performance reasons.

Many at this point would have said why not use a framework like Lean or Freqtrade or Hummingbot. However I found that these frameworks were too opinionated and if you decide to use them then your bot is now part and parcel of their framework. I backtested my bots locally in my own specific way, and now with AI my agents can generate code, backtest and analyze the results all locally, no need to run any of it in the execution platform. I wanted bots I could deploy, version, update and monitor like any other software application. I also wanted to explore building something that creates a standardized way of running bots.

This has been a 4 year journey and I made a lot of mistakes along the way. The application has seen 4 rearchitectures, 3 of which were basically complete rewrites. The first version was a python program and the bots were just modules that were loaded dynamically. The second was my serverless phase when I internally just wanted something that was online cron triggered and only works for me. The third was the first time I was dipping into kubernetes; more cloud native and the idiot in me decided to try make it a SaaS. The final form is a fully self-hosted runtime, api, cli and frontend that let you run bots as containers in a fault tolerant way both locally (through docker `the0 local`) and in a cluster (k8s) and monitor them with a minimalistic frontend.

To support multiple languages there's a thin contract that the bots have to implement: a main(bot_id, config) function and a bot-config.yaml file. The runtime (written in Go) takes care of the rest, it supports C++, Rust, Python, JS/TS, C#, Scala and Haskell for those who are brave enough to try it. More on the architecture here: https://docs.the0.app/runtime

If you want to play with the0 you can run it locally, guide here: https://docs.the0.app/deployment/local-getting-started. The0 is open source and licensed under Apache-2.0: https://github.com/alexanderwanyoike/the0

I currently use the0 to run my own personal algorithmic trading bots on a single node k3s cluster on a $10/month Hetzner VPS. I have 18 bots running on 2 brokers (Alpaca, Bybit) and they have been running for months without issues. Some bots trade crypto, others stocks, some do risk analysis and others invest. Coolest bit is the API provides an MCP server so AI agents can query the state of the bots, look at their logs, monitor them and even update them. Slap an OpenClaw agent and you can effectively setup an autonomous AI quantitative trading system (good luck chasing Alpha).

Now I must admit Lean has all the tools and far more quantitative prowess than the0, but I always felt it does too much. Each Lean engine runs one algorithm, and once you have lots of bots, running and managing all of them in production is left to you. That's the part the0 does, and its the only part it tries to do. If you find hiccups or have ideas for features Im all ears. More on the internals in my first comment.