Lightweight, single-binary workflow engine with built-in Web UI

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Last commit: 2d ago
Repo age: 4y old
Dagu screenshot

Dagu is a lightweight workflow orchestration engine that runs as a single self-contained binary and provides a modern Web UI. Workflows are defined in a declarative YAML format and can execute local commands, SSH commands, and containerized steps with scheduling and retries.

Key Features

  • Single-binary installation with zero required external dependencies; uses file-based storage for definitions, logs, and history
  • Declarative YAML DSL for DAGs with scheduling (cron), timezones, conditional steps, retries, and repeat policies
  • Built-in Web UI: visual DAG view, real-time monitoring, execution history, log search, and an integrated YAML editor
  • Executors for shell commands, Docker containers, SSH remote execution, and HTTP steps
  • Distributed execution: coordinator/worker model and built-in queueing to scale across machines
  • Nested/sub-DAG support for reusable composition and inspectable sub-runs in the UI
  • Integrations and platform features: GitHub Actions executor, API key management and RBAC, webhooks, email notifications
  • Newer features include human-in-the-loop approvals and a Chat Executor for integrating LLMs into workflows

Use Cases

  • Replace scattered cron jobs with a visual, auditable DAG system for server maintenance and operational scripts
  • Orchestrate multi-step CI/maintenance workflows that mix local scripts, SSH calls, and containerized tasks
  • Run distributed data-processing pipelines across multiple worker nodes with centralized monitoring and retries

Limitations and Considerations

  • Secrets management is not provided as a full built-in secret store; references and integrations (KMS/Vault/OIDC) are discussed/tracked as planned features
  • While Dagu supports distributed runs and queueing, very large cloud-native deployments may require external orchestration or custom scaling strategies

Dagu is designed for teams that want powerful orchestration with minimal operational overhead and straightforward local-first deployment. It emphasizes portability, simple YAML-based definitions, and an integrated UI for everyday workflow operations.

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