Lightweight DAG Orchestrator
The ultimate lightweight orchestrator with no limitations for executing any kind of tasks on Unix systems. Deploy inside microservices, work with resource-constrained systems, cluster with other Dagychu instances, and execute scheduled tasks precisely when you need them.
Execute complex workflows with precision timing and dependency management
Powerful orchestration capabilities designed for modern infrastructure
Minimal resource footprint allows deployment inside microservices and resource-constrained environments without impacting system performance.
Seamlessly cluster multiple Dagychu instances across your infrastructure for distributed task execution and high availability.
Execute tasks at specific times or by deadline with intelligent scheduling that considers task duration and dependencies.
Run any type of task on Unix systems - Python scripts, bash commands, custom executables, or inline commands with full flexibility.
Track execution times, success rates, and performance trends with comprehensive logging and runtime analysis capabilities.
Simple, readable YAML configuration files for defining DAGs, dependencies, and scheduling with version control integration.
From free open-source to enterprise solutions
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Built for performance and reliability
Built with Python 3.8+ using modern async/await patterns. Supports virtual environments and custom executors for maximum flexibility.
Zero-configuration SQLite database for runtime statistics, execution logs, and scheduling. No external database dependencies required.
Built-in FastAPI server with JWT authentication, comprehensive endpoints for DAG management, and real-time execution monitoring.
Integrated Telegram and Slack notifications for execution status, failures, and performance alerts with customizable messaging.
Designed for Linux, macOS, and Unix-like systems. Supports systemd integration, daemon mode, and containerized deployments.
Built-in runtime analysis with EMA smoothing, trend detection, anomaly identification, and predictive execution time estimates.
Ideal use cases for Dagychu orchestration
ETL processes, data validation, and transformation workflows with dependency management and failure recovery mechanisms.
Automated testing, deployment pipelines, and release management with precise timing and rollback capabilities.
Scheduled report creation, data aggregation, and distribution workflows with deadline-based execution.
System cleanup, log rotation, backup operations, and health checks with intelligent scheduling and monitoring.
Coordinate complex microservice workflows, manage service dependencies, and ensure proper execution order.
System health checks, performance monitoring, and automated alerting workflows with custom notification rules.