TL;DR — Leoflow v0.0.1 just shipped. It speaks the Airflow API, runs the Airflow 3.2.x UI unmodified, but replaces the Python control plane with Go. Pod-per-task is the only execution mode. Each DAG is its own container image. Fan-in (map-reduce) is a Python list comprehension. Install: curl -fsSL https://raw.githubusercontent.com/neochaotic/leoflow/main/install.sh | sh. GitHub: neochaotic/leoflow — stars and issues warmly accepted.
The 3 AM pager
You know the one. The scheduler stalled again. Or the triggerer suffocated under 500 sensors. Or a worker leaked file descriptors until Kubernetes OOMKilled it mid-run. Or someone bumped pandas for the new DAG and broke six legacy ones because they all share the same image.
Apache Airflow is the most widely deployed workflow orchestrator on earth. It is also the one that bleeds the most in production. None of those wounds are bugs — they are structural consequences of running orchestration through a Python control plane. You cannot patch the GIL. You cannot make DagBag reparse cheap. You cannot make Celery workers ephemeral without rewriting them.
So we did the only thing left: we kept everything Airflow got right and replaced everything that bleeds.
