Best Self Hosted Alternatives to AWS EventBridge Scheduler

Cronicle is a self-hosted, web-based job scheduler designed as a modern replacement for traditional cron. It provides a central UI and API to schedule, run, and monitor scripts across multiple servers, with distributed execution, logging, and operational controls.

Key Features

• Web UI for creating schedules (cron-style and intervals), launching jobs manually, and monitoring runs
• Distributed “worker” architecture to execute jobs across multiple servers/nodes
• Multiple schedule types and timezone-aware scheduling
• Per-job concurrency controls, timeouts, retries, and error handling
• Centralized logging with per-run output capture and searchable history
• Notifications and webhooks for job success/failure (integration-friendly)
• Role-based access controls (users, privileges) for multi-user operations
• REST-style API for automation and external integrations

Use Cases

• Centralize cron jobs for a multi-server environment (backups, ETL, maintenance)
• Run operational runbooks on demand with audit-friendly run history
• Coordinate scheduled scripts with notifications for failures and SLA monitoring

Limitations and Considerations

• Requires deploying and maintaining Cronicle server plus workers and its backing storage; sizing depends on job volume and log retention
• Focused on scheduling/executing scripts rather than full DAG workflows (may not fit complex pipeline orchestration needs)

Cronicle fits teams that want a lightweight, UI-driven scheduler to replace scattered crontabs and provide visibility, controls, and integrations. Its distributed worker model makes it well-suited for reliably running recurring automation across a server fleet.

Dagu is a lightweight workflow engine and scheduler for running tasks as Directed Acyclic Graphs (DAGs). Workflows are defined in simple YAML files and executed by an agent, with a built-in web UI for operations such as running, monitoring, and debugging.

Key Features

• Define workflows as DAGs in YAML (steps, dependencies, schedules)
• Built-in Web UI to view DAG status, runs, and execution history
• Manual runs, scheduled runs (cron-style), and dependency-based execution
• Retries, timeouts, and failure handling per step/workflow
• Centralized logging and execution artifacts/history for troubleshooting
• Notifications (e.g., via common channels like email/Slack) and callbacks/hooks for run events
• Parameterization and environment variables for reusable workflows

Use Cases

• Server and ops automation (backups, maintenance jobs, batch scripts)
• Data/ETL-style pipelines that can be expressed as shell commands or scripts
• Scheduled report generation or periodic integrations between systems

Dagu is a good fit when you want a simple, file-defined DAG scheduler with an operational UI, without adopting a heavier orchestration stack. It works well for teams that prefer Git-managed YAML workflows and straightforward deployment for internal automation.