18 Repos
Mechanisms for pausing, delaying, or conditionally waiting during the execution of automated sequences.
Explore 18 awesome GitHub repositories matching devops & infrastructure · Execution Flow Controls. Refine with filters or upvote what's useful.
Home Assistant is a centralized home automation platform designed to orchestrate diverse internet-connected devices and services. It functions as a local-first control system that normalizes heterogeneous hardware protocols into a unified set of entities, attributes, and services. The core architecture relies on an event-driven state bus and a modular integration model, allowing the system to manage state changes and communicate across decoupled components through standardized interfaces. The platform distinguishes itself through a highly flexible, declarative configuration framework that all
Manages concurrency through configurable strategies like single-instance locking, queuing, or parallel execution for simultaneous triggers.
Crawlee is a web scraping framework designed for building scalable, reliable, and distributed data extraction pipelines. It provides a unified interface for managing headless browser automation and lightweight HTTP requests, allowing developers to handle complex web navigation, dynamic content rendering, and large-scale data collection within a single, modular architecture. The project distinguishes itself through its resource-aware concurrency controller, which dynamically scales task execution based on real-time CPU and memory usage to prevent host machine exhaustion. It also features a rob
Provides controls to start, pause, resume, or abort task processing during long-running scraping operations.
Prefect is a workflow orchestration platform designed to define, schedule, and monitor complex data pipelines as Python code. It functions as a container-native engine that wraps individual tasks in isolated environments, ensuring consistent dependencies and resource allocation across diverse infrastructure. By utilizing a state-machine-based orchestration model, the system tracks execution progress through discrete transitions and persistent event logs to maintain reliable and observable task processing. The platform distinguishes itself through a decoupled worker-API architecture, which sep
Binds workflow execution to cloud container service work pools to manage remote infrastructure.
Argo is a cloud native CI/CD platform and Kubernetes workflow engine. It functions as a container pipeline orchestrator and job scheduler, managing multi-step sequences of containers as jobs using directed acyclic graphs within a cluster. The system acts as a progressive delivery controller, reducing release risk through automated Canary and Blue-Green deployment strategies. It provides declarative GitOps synchronization to mirror the state of a git repository directly into the cluster environment for continuous delivery automation. The platform covers a broad range of capabilities including
Regulates resource consumption and pipeline logic using loops, conditionals, and timeouts.
Duplicati is a self-hosted backup server designed to perform encrypted, incremental, and compressed backups to a wide range of local, network, and cloud-based storage providers. It functions as a background service that automates recurring data protection tasks, ensuring that only changed data blocks are stored to maximize efficiency and minimize bandwidth usage. The project distinguishes itself through a centralized management console that allows for the orchestration of multiple distributed backup agents from a single web-based dashboard. It supports multi-tenant management, enabling the or
Aborts backup tasks if required scripts fail or time out, enforcing execution time limits to prevent scripts from blocking system processes.
Floci is a local emulator for AWS services and cloud infrastructure designed for developing and testing applications without a live internet connection. It serves as a containerized cloud emulator and a serverless runtime emulator, allowing users to run high-fidelity replicas of cloud databases, queues, and compute services on a local machine. The project distinguishes itself by using real container images instead of simple mocks to ensure behavioral accuracy. It functions as a local API gateway simulator with proxy-based routing for REST and WebSocket APIs, and provides a serverless environm
Uses real container images for compute and database services to ensure behavioral accuracy.
Maestro is a declarative mobile and web UI automation framework designed for end-to-end testing. It operates by querying the native accessibility tree of an application, allowing for black-box testing without requiring source code instrumentation or platform-specific dependencies. The framework distinguishes itself through a unified command syntax that abstracts interactions across Android, iOS, and web environments. It features a dynamic synchronization engine that automatically pauses test execution to account for non-deterministic animations and network-dependent content loading, ensuring
Toggles hardware-level device states such as network connectivity and notifications during automated test runs.
Home Assistant is a local home automation platform and server that acts as an IoT device orchestrator. It integrates diverse smart home hardware by wrapping third-party APIs into a standardized logic layer and stores all system state and historical statistics on local hardware to eliminate cloud dependencies. The system functions as a Matter IoT controller and an MQTT home automation bridge, allowing for local interoperability between different manufacturers. It features a state-based entity model and an internal event bus that decouple physical device logic from system automation. The platf
Evaluates conditional requirements after a trigger occurs to block actions if specific criteria are not met.
This project is an open-source software development kit and framework for implementing the Matter smart home standard. It provides a universal IPv6-based application layer and a cluster-based data model to ensure interoperability between diverse smart home devices and controllers. The system is distinguished by its multi-transport network abstraction, which maps Bluetooth LE, Thread, and Wi-Fi implementations to a common layer. It includes specialized tooling for secure device commissioning via QR codes and NFC, as well as a comprehensive over-the-air firmware update system for distributing s
Provides controls for toggling binary on/off states for simple hardware device functions.
Newman is a headless API client and command line tool for executing Postman collections. It serves as an API test automation tool and execution engine that allows users to run predefined sets of API requests without a graphical interface. The project differentiates itself as a data-driven testing engine, capable of iterating through request sequences using external JSON or CSV files to validate multiple sets of input values. It also functions as an API execution reporter, utilizing a plugin-based interface to output results in formats such as JSON and JUnit. The tool covers broad capability
Manages the run process by selecting folders, setting timeouts, or stopping execution upon the first failure.
Free RPA tool by AI Singapore
Provides a free cloud service and Docker container support for executing automation flows on remote browsers and mobile devices.
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
Controls active pipeline runs by canceling, retrying, or resuming execution after manual intervention.
Azkaban ist ein verteilter Workflow-Manager und ein DAG-basierter Job-Orchestrator, der als Enterprise-Batch-Prozessor konzipiert ist. Er dient als Java-basierte Workflow-Engine, die komplexe Job-Sequenzen über einen Cluster von Executor-Servern plant und ausführt, mit spezifischer Funktionalität zur Verwaltung von Big-Data-Workloads auf Hadoop-Clustern. Das System zeichnet sich durch ein verteiltes Executor-Modell aus, das den Status über eine gemeinsame Datenbank koordiniert, um eine hohe Verfügbarkeit sicherzustellen. Es verwendet eine plugin-basierte Architektur, die benutzerdefinierte Job-Typen und Systemfunktionserweiterungen ermöglicht, einschließlich der Fähigkeit, Plugins ohne Neustart der Executor-Server neu zu laden. Die Plattform deckt ein breites Spektrum an Funktionen ab, einschließlich Daten-Pipeline-Orchestrierung mit bedingter Logik, periodischer und ereignisgesteuerter Planung sowie Enterprise-Monitoring mit SLA-Tracking. Sie bietet granulare Zugriffskontrolle und Benutzer-Impersonation für sichere Ausführung, neben Traffic-Management-Tools für Executor-Load-Balancing und Ressourcenquoten. Benutzer können Workflows über eine webbasierte Schnittstelle oder programmatisch über eine Workflow-Execution-API verwalten.
Provides mechanisms to start, pause, resume, and cancel active workflow executions.
Navigation2 is a ROS 2 navigation framework for autonomous mobile robots. It provides the core identity of a path planner, costmap management system, kinematic motion controller, and behavior tree orchestrator to compute collision-free routes and execute movement commands. The framework is distinguished by its use of behavior trees to coordinate modular task servers, enabling complex navigation routines and autonomous recovery actions. It supports a plugin-based architecture that allows planners and controllers to be swapped at runtime to adapt to different environments. The system covers a
Manages the flow of robot behaviors using sequences, recovery loops, and non-blocking execution patterns.
afrog is an HTTP vulnerability scanner and web vulnerability management system that identifies security flaws and known CVEs using a YAML-based rule engine. It functions as a payload generator and scanner, comparing server responses against detection rules to find unauthorized access points. The project provides a framework for out-of-band security testing, detecting blind vulnerabilities by triggering and verifying external DNS or HTTP callbacks. Beyond web traffic, it includes a protocol fuzzer capable of executing multi-step read and write sequences over raw TCP and SSL sockets to identify
Provides mechanisms to stop or delay the scanning process based on whether a specific rule matches.
Liteflow is a component-based rule engine and workflow orchestrator used to define business logic through a chain of reusable components. It utilizes a structured data language to map logic paths, functioning as a dynamic workflow engine for managing sequences of synchronous and asynchronous tasks. The project is distinguished by its support for hot deployment, allowing rule definitions and execution logic to be updated in real time without restarting the application. It also features a multi-language scripting engine that embeds external scripts into business rules to enable flexible logic c
Controls the logic flow through a mix of synchronous and asynchronous execution paths.
DDEV is a container-based local development environment and project manager designed to bootstrap consistent web development stacks. It orchestrates Docker containers to provide isolated Linux environments, integrating web servers, databases, and language runtimes. The project distinguishes itself by automating the complexities of local networking and security, featuring a local HTTPS proxy for SSL certificate automation and wildcard DNS for hostname management. It further enables collaboration by exposing local environments to the internet through tunneling for external project sharing. The
Deploys development environments into remote cloud containers to remove local system dependencies.
This project provides a comprehensive guide and framework for implementing autonomous AI coding assistants within local development environments. It focuses on orchestrating multi-agent teams that can plan, execute, and verify complex software engineering tasks, such as refactoring, bug resolution, and test generation, while maintaining deep awareness of project-specific context and memory. The system distinguishes itself through a robust security-first architecture that enforces granular access controls, execution isolation, and mandatory human-in-the-loop approvals for all file modification
Executes coding tasks in isolated, ephemeral cloud virtual machines that synchronize changes back to the repository.