Open-Source DevOps · dagucloud

dagu

Dagu is a lightweight, self-contained workflow orchestration engine built in Go that runs as a single binary without requiring a database. It lets teams define data pipelines and task automation in simple YAML, manage them through a web UI, and integrate with AI agents via MCP protocol.

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Source: GitHub — github.com/dagucloud/dagu

3.6k

GitHub stars

292

Forks

Primary language

GPL-3.0

License (OSI-approved)

Key facts

Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.

Field	Value
Repository	dagucloud/dagu
Owner	dagucloud
Primary language	Go
License	GPL-3.0 — OSI-approved
Stars	3.6k
Forks	292
Open issues	118
Latest release	v2.10.1 (2026-07-06)
Last updated	2026-07-08
Source	https://github.com/dagucloud/dagu

What dagu is

Dagu is a Go-based DAG orchestrator using file-backed state storage, supporting shell commands, Docker containers, Kubernetes Jobs, and SSH execution. It includes a web UI, built-in MCP server for AI agent integration, configurable queues, concurrency controls, and distributed worker capability; designed for local-first or self-hosted deployment.

Quickstart

Get the dagu source

Clone the repository and explore it locally.

terminalbash

1git clone https://github.com/dagucloud/dagu.git2cd dagu3# follow the project's README for install & configuration

Need it deployed, integrated, or customized instead? DEV.co ships production installs.

Best use cases

Cron and legacy script migration

Replace opaque cron jobs and bash scripts with observable DAGs featuring automatic logging, retries, notifications, and a UI for monitoring and manual interventions.

ETL and data pipelines

Turn extraction scripts, SQL queries, dbt commands, and data processing runbooks into durable, observable pipelines with built-in error handling and state tracking.

Infrastructure and server automation

Execute commands and scripts over SSH on remote servers with centralized logging, audit trails, and the ability to trigger from GitHub events without exposing infrastructure publicly.

Implementation considerations

File-backed state storage means scaling beyond one machine requires careful queue and worker configuration; no built-in distributed consensus, so operator responsibility for consistency.
YAML DAG definition is approachable but tool integration (IDE support, schema validation, CI/CD templates) is not clearly documented; review existing examples and docs before adoption.
Web UI and MCP support for AI agents suggest a low-code workflow model; test whether your team's workflows fit the supported action types (shell, Docker, K8s, SSH, harness.run).
GPL-3.0 copyleft license requires code review for commercial deployments; consider whether modifications must be open-sourced or if your use case fits the community license terms.
Single-binary installation simplifies setup but operational readiness (logging, monitoring, alerting, backup/restore) depends on your infrastructure maturity.

When to avoid it — and what to weigh

Require multi-tenant SaaS isolation by default — Dagu is designed for small teams on self-hosted or local instances. Managed Dagu instances exist but require evaluation for your isolation and compliance needs.
Need strict commercial support guarantees — GPL-3.0 license requires careful review for commercial use. Community support via Discord is available; formal SLA or vendor support is not clearly documented.
Have extremely high throughput requirements at scale — While Dagu claims to handle thousands of runs per day, this depends heavily on hardware, workflow shape, and queue configuration. Not positioned as a large-scale distributed orchestrator like Airflow with Celery.
Require proprietary license or closed-source operation — Dagu is GPL-3.0, making it unsuitable for teams unable to work with copyleft licensing or unwilling to disclose modifications in self-hosted scenarios.

License & commercial use

Dagu is released under GPL-3.0 (GNU General Public License v3.0), a copyleft license requiring that any modified source code be made available under the same license if distributed. Community self-hosted use requires no license key. Commercial features (SSO, RBAC, audit logging) are available via self-host license and managed Dagu instances.

GPL-3.0 is a copyleft license; commercial use is legally permitted, but any modifications to Dagu itself must be released under GPL-3.0 if you redistribute the software. Using Dagu to orchestrate proprietary workflows (which remain separate from Dagu's code) is generally permissible, but the distinction requires careful review. Commercial support, SLA guarantees, and indemnification are not clearly documented. Advise legal and compliance review before production deployment.

DEV.co evaluation signals

Editorial assessment — not user reviews. Directional, with an explicit confidence level.

Signal	Assessment
Maintenance	Active
Documentation	Adequate
License clarity	Needs review
Deployment complexity	Low
DEV.co fit	Good
Assessment confidence	High

Security considerations

Dagu stores state in local files; file permissions and access control depend on the operating environment. Web UI authentication requires review (credentials visible in live demo suggest basic auth; SSO available in paid tiers). MCP endpoint exposes workflow read/write/execute capabilities and should be protected behind network boundaries. SSH action execution, Docker, and Kubernetes integration increase the attack surface; isolation and RBAC are provided in paid licensing. No third-party security audit or CVE history is evident in the data.

Alternatives to consider

Apache Airflow

Full-featured, widely adopted orchestrator with mature ecosystem, but requires PostgreSQL, Redis, and Python runtime. Scales to large deployments; steeper operational complexity and learning curve than Dagu.

Temporal

Durable execution engine with strong guarantees and SDKs for multiple languages. More heavyweight than Dagu; designed for microservices and event-driven architectures rather than simple DAGs and cron replacement.

Prefect

Python-centric workflow engine with cloud and self-hosted options. Easier to use than Airflow but less lightweight than Dagu; requires Python and external service for full feature set.

Software development agency

Build on dagu with DEV.co software developers

Dagu offers a lightweight alternative to Airflow and Cron with minimal operational overhead. Evaluate the GPL-3.0 licensing and deployment model for your team, then start with the quick-start guide and live demo.

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dagu FAQ

Can I use Dagu in production?

Yes, if you can operate a self-hosted instance or adopt Dagu's managed offering. Community self-hosted requires no license key; commercial features (SSO, RBAC, audit logging) are available via self-host or managed licenses. Review GPL-3.0 terms for your use case.

Does Dagu require a database?

No. Dagu stores state in local files, eliminating the need for PostgreSQL, MySQL, or other external databases. This simplifies deployment but means state is local to the Dagu instance; distributed setups require careful worker and queue configuration.

How does Dagu integrate with AI agents?

Dagu exposes a built-in MCP (Model Context Protocol) server at http://localhost:8080/mcp. AI agents like Claude, Codex, and Gemini can connect to read workflow state, preview/apply changes, and trigger runs via dagu_read, dagu_change, and dagu_execute tools.

What happens if I modify Dagu's source code and deploy it?

GPL-3.0 requires that modifications be made available under the same license if distributed. Using Dagu to run proprietary workflows is permissible; modifying Dagu itself for internal use is also permissible, but redistribution requires source disclosure. Consult legal counsel for clarity on your deployment model.

Custom software development services

DEV.co helps companies turn open-source tools like dagu into production software. Our software development services cover the full lifecycle — architecture, web development, integration, and maintenance — delivered by software developers and web developers who ship. Engage our software development agency to implement or customize it for your open-source devops stack.

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