dagron/ docs
Documentation

Operate dagron

dagron is an open-source DAG workflow engine: plain-YAML workflows, retries and backoff, a live web UI, SQLite or Postgres, and Kubernetes execution — from one static Rust binary, with a database as its only state. These pages cover running it: the CLI, day-to-day administration, upgrades, and scaling.

Install

Three ways in, smallest first. The workflow YAML is the same in all of them.

One binary — local development
# engine + management API + Swagger on localhost
$ dagron dev workflow.yaml

# one-shot: run a workflow, drain, exit
$ dagron examples/simple_dag.yaml
Docker Compose — full stack with the web UI
$ git clone https://github.com/lucheeseng827/dagron
$ cd dagron && docker compose up

# open the UI
http://localhost:3000
Helm — production on Kubernetes
# multi-arch images + OCI chart on Docker Hub
$ helm install dagron \
    oci://registry-1.docker.io/mancube/dagron

# point at your own Postgres
$ helm install dagron oci://registry-1.docker.io/mancube/dagron \
    --set postgres.enabled=false \
    --set externalDatabaseSecret.name=dagron-db

Prebuilt binaries for Linux, macOS and Windows are on GitHub Releases; the chart is also listed on Artifact Hub.

The pages

Reference

CLI & configuration

The dagron binaries and how they are invoked, the environment variables that configure them, compile-time features, and the MCP tools an agent can call.

 Operate

Admin & maintenance

What you are operating and what its state is. Monitoring and health, backups and restore, dead letters, API tokens, secrets, and a symptom-first troubleshooting table.

 Operate

Update & upgrade

How schema migrations actually work, the production upgrade procedure, rolling restarts across multiple schedulers, and rollback.

 Operate

Scaling & HA

How the data plane scales out, the deployment configurations from a single binary to a replicated cluster, the knobs that govern concurrency, and the limits.

Going deeper

These pages are the operator's cut. The full reference — workflow YAML fields, the HTTP APIs, GitOps, datasets, streaming, AI workloads, migration guides from Airflow, Argo and Temporal — lives with the source: