ltsopensource/light-task-scheduler
Light Task Scheduler
Light Task Scheduler is a distributed job scheduling and workflow orchestration platform designed for managing background processing across scalable computing environments. It functions as a cluster management system that coordinates stateless nodes to execute recurring, cron-based, or one-time tasks with centralized control and high availability.
The platform distinguishes itself through a leader-based coordination model that automatically elects a primary controller to manage task distribution and system state. It supports complex workflow dependencies, ensuring that prerequisite tasks complete successfully before triggering subsequent processes. The system provides granular operational control, allowing users to pause, resume, terminate, or manually trigger jobs on demand through a centralized interface.
The framework includes comprehensive capabilities for fault-tolerant execution, featuring automatic retries, node heartbeat monitoring, and task redistribution to maintain stability during failures. It offers extensive observability tools, including real-time task execution tracking, cluster-wide performance metrics, and business event logging. Developers can extend the system’s core functionality through modular service interfaces and integrate it into existing applications using standard dependency injection and metadata-driven configuration.
Features
- Distributed Job Schedulers - Provides a distributed job scheduling platform that manages recurring and one-time tasks across a cluster of stateless nodes.
- Task Dependency Management - Coordinates complex workflow dependencies by ensuring prerequisite tasks complete successfully before triggering subsequent processes.
- Task Lifecycle Management - Offers centralized control to pause, resume, terminate, or manually trigger background tasks.
- Fault-Tolerant Coordinators - Ensures system stability through automatic leader election, heartbeat monitoring, and task redistribution during node failures.
- Distributed Cluster Management - Organizes computing nodes into scalable clusters with centralized monitoring for high availability.
- Distributed Task Queues - Coordinates background job execution with support for task dependencies and retry policies.
- Workflow Orchestration - Manages complex task dependencies to ensure prerequisite jobs complete before triggering subsequent workflow steps.
- Workflow Orchestration Engines - Acts as a workflow orchestration engine for defining and executing sequences of dependent tasks.
- Distributed Cluster Coordination - Coordinates cluster state and task distribution through an automatic leader election model.
- Distributed Task Queues - Provides a distributed task queue for managing and executing background jobs across multiple worker nodes.
- Event-Driven Workflow Orchestrators - Orchestrates complex sequences of dependent tasks triggered by completion signals and predefined logical flows.
- Cluster Node Management - Organizes computing nodes into scalable clusters with automatic master election to maintain high availability.
- High Availability Cluster Deployments - Provides a platform for managing distributed computing nodes with automatic master election and high availability.
- Heartbeat Monitors - Monitors worker node health and resource metrics via heartbeats to enable automatic failure detection and workload balancing.
- Job Lifecycle Management - Offers a centralized interface for monitoring task status, updating parameters, and managing the lifecycle of background jobs.
- Fault Tolerance - Ensures reliable job execution through automatic retries, node election, and task redistribution during failures.
- Modular Provider Interfaces - Implements a modular service provider interface to allow custom storage, logging, and communication protocol extensions.
- Task Retry Policies - Supports configurable retry policies for individual tasks to handle transient failures and ensure reliable execution.
- Task Execution Monitoring - Provides real-time visibility into job progress and system performance through a centralized dashboard.
- Cluster Monitoring Systems - Aggregates performance metrics and resource utilization across distributed nodes for cluster-wide health monitoring.
