Features

Deep dive into all Dagu capabilities.

Overview

Dagu provides a comprehensive set of features for building and managing workflows. This section covers everything you need to know about each feature in detail.

Feature Categories

🖥️ Interfaces

How to interact with Dagu:

• Command Line Interface - Run and manage workflows from the terminal
• Web UI - Monitor and control workflows visually
• REST API - Integrate Dagu programmatically

🔧 Executors

Different ways to run your commands:

• Shell - Run any command or script (default)
• Docker - Execute in containers for isolation
• SSH - Run commands on remote servers
• HTTP - Make REST API calls and webhook requests
• Mail - Send email notifications and reports
• JQ - Process and transform JSON data

⏰ Scheduling

Control when workflows run:

• Cron expressions with timezone support
• Multiple schedules per workflow
• Start/stop/restart patterns
• Skip redundant executions

🚀 Execution Control

Advanced execution patterns:

• Parallel execution with concurrency limits
• Conditional execution (preconditions)
• Continue on failure patterns
• Retry and repeat policies
• Output size management
• Signal handling

📊 Data Flow

Managing data in workflows:

• Parameters and runtime values
• Output variables between steps
• Environment variable management
• JSON path references
• Template rendering
• Special system variables

📋 Queue System

Workflow orchestration at scale:

• Built-in queue management
• Per-DAG queue assignment
• Priority-based execution
• Manual queue operations
• Concurrency control

📧 Notifications

Stay informed about workflow status:

• Email alerts on success/failure
• Custom notification handlers
• Log attachments
• Flexible SMTP configuration

Feature Highlights

Zero Dependencies

Unlike other workflow engines, Dagu requires:

• ❌ No database
• ❌ No message broker
• ❌ No runtime dependencies
• ✅ Just a single binary

Language Agnostic

Run anything that works on your system:

steps:
  - name: python
    command: python script.py
  - name: node
    command: npm run task
  - name: go
    command: go run main.go
  - name: bash
    command: ./script.sh

Hierarchical Workflows

Build complex systems from simple parts:

steps:
  - name: data-pipeline
    run: etl.yaml
    params: "DATE=today"
    
  - name: ml-training
    run: train.yaml
    depends: data-pipeline
    
  - name: deployment
    run: deploy.yaml
    depends: ml-training

Production Ready

Built for reliability:

• Process Management: Proper signal handling and graceful shutdown
• Error Recovery: Configurable retry policies and failure handlers
• Logging: Comprehensive logs with stdout/stderr separation
• Monitoring: Built-in metrics and health checks

Common Use Cases

Data Engineering

• ETL pipelines with dependency management
• Parallel data processing
• Scheduled batch jobs
• Data quality checks

DevOps Automation

• CI/CD pipelines
• Infrastructure provisioning
• Backup and restore workflows
• System maintenance tasks

Business Process Automation

• Report generation
• Data synchronization
• Customer onboarding
• Invoice processing

Performance Characteristics

Scalability

• Handle thousands of concurrent workflows
• Efficient file-based storage
• Minimal memory footprint
• Fast startup times

Limitations

• Single-machine execution (no distributed mode)
• 1MB default output limit per step
• 1000 item limit for parallel execution
• File system dependent

Getting Started with Features

1. Start with the basics: Learn about Interfaces to interact with Dagu
2. Choose your executor: Pick the right Executor for your tasks
3. Add scheduling: Set up automatic execution
4. Handle errors: Implement proper retry and error handling
5. Scale up: Use queues for complex orchestration

Feature Comparison

Feature	Dagu	Airflow	GitHub Actions	Cron
Local Development	✅	❌	❌	✅
Web UI	✅	✅	✅	❌
Dependencies	✅	✅	✅	❌
Retries	✅	✅	✅	❌
Parallel Execution	✅	✅	✅	❌
No External Services	✅	❌	❌	✅
Language Agnostic	✅	❌	✅	✅

See Also

Explore specific features:

• Command Line Interface - Master the CLI
• Shell Executor - Run commands effectively
• Scheduling - Automate workflow execution
• Execution Control - Advanced patterns