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Mechanisms for persisting function progress across steps and retries to ensure reliable completion.
Distinct from Execution State Persistence: Distinct from Execution State Persistence: focuses on workflow-specific step-by-step persistence rather than general script memory state.
Explore 7 awesome GitHub repositories matching development tools & productivity · Workflow Execution State Persisters. Refine with filters or upvote what's useful.
Inngest is a durable execution framework and event-driven automation engine designed to orchestrate background workflows. It enables developers to build resilient, stateful processes by memoizing function steps, ensuring that long-running tasks can automatically resume from the last successful operation after failures, timeouts, or infrastructure restarts. The platform distinguishes itself through its event-driven architecture, which uses a schema-validated bus to trigger functions and coordinate complex, multi-step logic. It employs an onion-model middleware approach for cross-cutting concer
Persists function progress across steps, retries, and deployments to ensure reliable completion of complex workflows.
ZenML is an extensible machine learning orchestration framework designed to manage the end-to-end lifecycle of data pipelines and AI agent workflows. It functions as a durable orchestrator that executes machine learning tasks as directed acyclic graphs, ensuring that every step is containerized for consistent performance across local, cloud, and hybrid infrastructure. By decoupling pipeline code from underlying compute and storage backends, the platform allows developers to define infrastructure-agnostic stacks that remain portable across diverse environments. The project distinguishes itself
Persists intermediate data, logs, and metadata across runs to enable auditability and retrieval of past results.
ZenML is an orchestration platform designed for building, deploying, and monitoring reproducible machine learning pipelines and agentic workflows. It provides a unified framework that manages the entire lifecycle of machine learning assets, from data processing and model training to the deployment of persistent inference services. By decoupling pipeline logic from underlying compute and storage, the platform enables teams to transition workflows seamlessly from local development environments to production-grade cloud infrastructure. The platform distinguishes itself through a service-oriented
Persists function progress and intermediate states across pipeline steps and retries to ensure reliable workflow completion.
Navigation2 是一个用于自主移动机器人的 ROS 2 导航框架。它提供了路径规划器、代价地图管理系统、运动学控制器和行为树编排器的核心功能,用于计算无碰撞路径并执行移动指令。 该框架的特色在于使用行为树来协调模块化任务服务器,从而实现复杂的导航流程和自主恢复动作。它支持插件式架构,允许在运行时切换规划器和控制器,以适应不同环境。 该系统涵盖了广泛的功能,包括全局和局部路径规划、2D SLAM 和基于地图的定位,以及通过网格代价地图进行的环境建模。它管理各种传动系统的运动控制,并集成了用于碰撞监控和紧急预防的安全系统。其他编排功能包括多目的地路径点排序、动态目标跟踪和自动对接程序。 该框架利用生命周期管理组件来协调操作服务器的启动、关闭和健康监控。
Persists progress and enables pausing and resuming of behaviors across system restarts.
Workflow is a platform for executing long-running, stateful processes that automatically persist progress and recover state after system interruptions. It functions as a durable orchestration engine designed to manage complex, multi-step asynchronous operations within distributed systems. The framework distinguishes itself through event-sourcing and checkpointing mechanisms that record execution steps as an immutable log, allowing for precise state reconstruction after failures. It provides sandboxed task isolation to run side-effect-heavy logic in restricted environments, ensuring that sensi
Persists function progress across steps and retries to ensure reliable completion of long-running processes.
This project is a business rules and complex event processing engine designed to manage logical decision-making and stateful workflows. It functions as a computational framework that evaluates incoming data streams and facts against conditional logic to derive new conclusions and trigger automated actions. The engine distinguishes itself through a combination of forward-chaining inference and deterministic state machine orchestration. It uses salience-based conflict resolution to prioritize rule execution and supports persistent contextual state tracking to manage long-running business proces
Maintains persistent data across rule executions to track entity progress and manage long-running business processes.
This project is a JavaScript-based workflow engine designed to execute business process models defined in standard XML. It functions as a stateful orchestrator that manages the lifecycle of complex processes by moving virtual tokens through tasks, gateways, and events. The engine provides a runtime environment for automating business logic, integrating external services, and coordinating human tasks within Node.js or browser-based applications. The engine distinguishes itself through its high degree of extensibility and state management capabilities. It allows developers to inject custom beha
Saves and recovers execution data to allow workflows to be paused, resumed, or rehydrated from serialized context sources.