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49 repositorios

Awesome GitHub RepositoriesCentralization Patterns

Architectural strategies for unifying service interfaces and security filtering.

Distinct from System Internals: Distinct from System Internals: focuses on the architectural pattern of centralization rather than low-level operational principles.

Explore 49 awesome GitHub repositories matching software engineering & architecture · Centralization Patterns. Refine with filters or upvote what's useful.

Awesome Centralization Patterns GitHub Repositories

Encuentra los mejores repositorios con IA.Buscaremos los repositorios que mejor coincidan usando IA.
  • donnemartin/system-design-primerAvatar de donnemartin

    donnemartin/system-design-primer

    353,387Ver en GitHub↗

    Este proyecto es un recurso educativo integral y una guía de estudio centrada en la arquitectura de sistemas distribuidos y el diseño de infraestructura backend. Proporciona un plan de estudios estructurado para dominar los principios de escalabilidad, confiabilidad y rendimiento necesarios para diseñar sistemas de software complejos. El repositorio se distingue por ofrecer un enfoque metódico para la preparación de entrevistas técnicas, incorporando patrones de diseño, compensaciones arquitectónicas y herramientas de repetición espaciada para ayudar a los usuarios a retener conceptos complejos. Enfatiza el análisis basado en restricciones, enseñando a los usuarios cómo evaluar requisitos competitivos como latencia, consistencia y disponibilidad al redactar diseños arquitectónicos. El contenido cubre un amplio espectro de capacidades de diseño de sistemas, incluyendo estrategias para el escalado de bases de datos, gestión de tráfico y optimización de infraestructura. Detalla técnicas para el escalado horizontal, almacenamiento en caché multicapa, comunicación asíncrona y descubrimiento de servicios, al tiempo que proporciona marcos para realizar estimaciones de recursos y planificación de capacidad. La documentación está organizada como una guía de estudio, ofreciendo un camino sistemático a través de los fundamentos de la ingeniería backend y el diseño de sistemas a gran escala.

    Explains architectural strategies for unifying service interfaces and security filtering.

    Pythondesigndesign-patternsdesign-system
    Ver en GitHub↗353,387
  • firehol/netdataAvatar de firehol

    firehol/netdata

    79,416Ver en GitHub↗

    Netdata is a real-time infrastructure monitoring tool and multi-node observability platform. It functions as a high-resolution monitoring agent, log and metric aggregator, and time-series database designed to provide full-stack visibility into server health. The system is distinguished by its per-second metric sampling and zero-configuration auto-discovery, which allows for immediate infrastructure tracking upon installation. It utilizes edge-based machine learning and unsupervised models to detect system anomalies and abnormal metric patterns locally on each node. For distributed environment

    Organizes telemetry data using parent-child streaming architectures with configurable replication and retention.

    Go
    Ver en GitHub↗79,416
  • shieldfy/api-security-checklistAvatar de shieldfy

    shieldfy/API-Security-Checklist

    23,258Ver en GitHub↗

    This project is a comprehensive API security audit checklist and vulnerability audit framework. It provides a structured guide of security countermeasures for designing, testing, and deploying secure APIs across various protocols. The framework includes specialized guides for securing OAuth 2.0 authorization flows, implementing zero trust networking for service-to-service communication, and protecting GraphQL endpoints from resource exhaustion and information leakage. It also provides standards for integrating static analysis, dynamic scanning, and secret detection into CI/CD delivery pipelin

    Provides architectural patterns for aggregating and routing API telemetry data through centralized observability pipelines.

    apijwtoauth2
    Ver en GitHub↗23,258
  • vectordotdev/vectorAvatar de vectordotdev

    vectordotdev/vector

    22,071Ver en GitHub↗

    Vector is a high-performance observability data pipeline designed to collect, transform, and route logs, metrics, and traces across distributed infrastructure. It functions as a modular engine that decouples data ingestion from processing and transmission, utilizing a component-based architecture to connect diverse sources to multiple destinations. The project distinguishes itself through a focus on reliability and flow control. It implements backpressure-aware data movement to prevent data loss during traffic spikes and utilizes disk-backed event buffering to ensure durability during network

    Aggregates observability data into a central layer to separate concerns and improve control without requiring external message queuing systems.

    Rusteventsforwarderhacktoberfest
    Ver en GitHub↗22,071
  • prefecthq/prefectAvatar de PrefectHQ

    PrefectHQ/prefect

    21,640Ver en GitHub↗

    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

    Runs data pipeline tasks as managed custom jobs within cloud provider environments.

    Pythonautomationdatadata-engineering
    Ver en GitHub↗21,640
  • react-dnd/react-dndAvatar de react-dnd

    react-dnd/react-dnd

    21,641Ver en GitHub↗

    React DnD is a library for building complex drag-and-drop interfaces within React applications. It provides a declarative, component-based architecture that abstracts native browser drag-and-drop APIs, allowing developers to manage state and interactions between draggable sources and drop targets. The library utilizes a dependency injection backend to decouple interaction logic from specific input methods, supporting mouse, touch, and native browser events through a unified normalization layer. It employs a registry pattern to track active drop zones and a monitor pattern to observe the lifec

    Tracks the lifecycle of drag operations to update component state based on interaction status.

    TypeScriptdrag-and-dropnot-the-gamereact
    Ver en GitHub↗21,641
  • claude-code-best/claude-codeAvatar de claude-code-best

    claude-code-best/claude-code

    20,272Ver en GitHub↗

    Claude Code is a command-line interface and multi-agent orchestration framework designed for autonomous software engineering. It enables AI agents to perform codebase modifications, debugging, and Git workflow management while coordinating multiple specialized agents to decompose and execute complex engineering tasks in parallel. The system distinguishes itself through a high degree of isolation and safety, utilizing Git worktrees to create independent working directories for concurrent agents and implementing a tiered permission system that combines user rules, project policies, and OS-level

    Executes long-running agent tasks asynchronously in the background to keep the main interface operational.

    TypeScript
    Ver en GitHub↗20,272
  • alibaba/page-agentAvatar de alibaba

    alibaba/page-agent

    19,138Ver en GitHub↗

    Page-agent is an LLM browser automation agent and JavaScript in-page GUI controller. It translates natural language instructions into direct browser interface actions to automate web-based tasks and manipulate web page elements through a programmable interface. The system coordinates complex sequences of actions across multiple browser tabs and different websites. It functions as a remote browser control server, providing an interface that allows external clients to operate a browser and manage page interactions. Its capabilities include natural language intent decoding and action mapping, D

    Coordinates complex sequences of browser actions across multiple tabs and different websites.

    TypeScriptagentaiai-agents
    Ver en GitHub↗19,138
  • spotify/luigiAvatar de spotify

    spotify/luigi

    18,676Ver en GitHub↗

    Luigi is a Python framework designed for building and managing complex batch data pipelines. It functions as a workflow orchestration engine that organizes tasks into directed acyclic graphs, ensuring that jobs execute in the correct logical order based on their dependencies. By utilizing a centralized scheduler, the system coordinates task execution across distributed environments, tracks global workflow state, and prevents redundant processing by verifying the existence of output targets before triggering any work. The project distinguishes itself through a robust state-tracking mechanism t

    Coordinates task execution and tracks global workflow state through a centralized server.

    Pythonhadoopluigiorchestration-framework
    Ver en GitHub↗18,676
  • effect-ts/coreAvatar de Effect-TS

    Effect-TS/core

    14,618Ver en GitHub↗

    This project is a functional programming library and toolkit for building production TypeScript applications. It provides a system for managing concurrency, error handling, and resource lifecycles using functional effects. The project distinguishes itself through a comprehensive suite of specialized toolkits, including a dependency injection framework for decoupling service implementations, a workflow orchestrator for coordinating durable processes, and a SQL database toolkit for consistent data operations across multiple dialects. It also implements an OpenTelemetry instrumentation library f

    Manages asynchronous tasks and resource dependencies through a coordinated system to ensure reliable execution.

    TypeScript
    Ver en GitHub↗14,618
  • nodesource/distributionsAvatar de nodesource

    nodesource/distributions

    13,834Ver en GitHub↗

    This project is a Node.js binary distribution repository and Linux package repository. It provides a hosted set of pre-compiled JavaScript runtime binaries for various Linux distributions to simplify installation and version management through native package managers. The project includes a Node.js observability toolset and security policy manager. These components enable the gathering of runtime telemetry to monitor application health and performance via diagnostic dashboards, while providing a resource restriction layer that intercepts system calls to prevent unauthorized modules from acces

    Implements architectural patterns for aggregating and routing telemetry data through a consistent export interface.

    Shelljavascriptlinuxnode
    Ver en GitHub↗13,834
  • netflix/conductorAvatar de Netflix

    Netflix/conductor

    12,767Ver en GitHub↗

    Conductor is a distributed workflow manager and microservices orchestration engine. It coordinates long-running business processes across a network of services, using a stateful orchestration model to ensure consistent execution order and reliable state management. The system defines task sequences and conditional business logic using structured JSON configuration files. It manages the execution of complex operations across distributed systems with built-in persistence and failure recovery, tracking the progress of processes through a backend database. The platform provides capabilities for

    Provides a centralized system to coordinate task execution and prevent redundant job processing across a network.

    Java
    Ver en GitHub↗12,767
  • the-pocket/pocketflow-tutorial-codebase-knowledgeAvatar de The-Pocket

    The-Pocket/PocketFlow-Tutorial-Codebase-Knowledge

    12,396Ver en GitHub↗

    This project is a comprehensive suite of AI tools and frameworks, featuring an LLM multi-agent orchestrator, an autonomous agent runtime, and a stateful application framework. It provides the infrastructure to build and manage specialized AI agents capable of coordinating complex tasks through graph-based workflows and shared state. The system is distinguished by its implementation of the Model Context Protocol, allowing for standardized resource discovery and communication between AI clients and servers. It further includes an AI-powered documentation generator designed to analyze source cod

    Coordinates multiple tasks through signatures and primitives to create dependent execution chains.

    Pythoncodinglarge-language-modellarge-language-models
    Ver en GitHub↗12,396
  • boto/boto3Avatar de boto

    boto/boto3

    9,834Ver en GitHub↗

    Boto3 is the AWS SDK for Python, providing a programmatic interface for managing and automating AWS cloud infrastructure and services. It serves as a cloud management API client and resource manager for provisioning, configuring, and scaling virtual servers, databases, and storage. The library enables the implementation of infrastructure-as-code through declarative templates and scripts, allowing for the deployment of identical resource stacks across multiple accounts and geographic regions. It also provides a framework for coordinating distributed workflows, serverless functions, and contain

    AWS coordinates business logic across multiple processes using scheduling, routing, and state management.

    Pythonawsaws-sdkcloud
    Ver en GitHub↗9,834
  • threedotslabs/watermillAvatar de ThreeDotsLabs

    ThreeDotsLabs/watermill

    9,760Ver en GitHub↗

    Watermill is a Go library for building event-driven applications. It provides a framework for implementing event-driven architectures through a consistent interface for message publishing and subscribing, featuring a pub/sub message router and event stream processing pipelines. The library uses interface-based abstractions to decouple message producers and consumers from the underlying message broker. This allows different messaging technologies to be swapped via plugin-based broker integration. It employs a router-driven dispatch system and middleware-based pipelines to manage cross-cutting

    Provides an interface for managing complex patterns such as event sourcing and sagas to coordinate requests.

    Gocqrsevent-drivenevent-sourcing
    Ver en GitHub↗9,760
  • netflix/metaflowAvatar de Netflix

    Netflix/metaflow

    9,764Ver en GitHub↗

    Metaflow is a Python machine learning framework and MLOps workflow orchestrator designed to manage the lifecycle of data pipelines from local prototyping to production. It serves as a distributed compute manager and an experiment tracking system, enabling the creation of reproducible pipelines that transition between development and high-availability production environments. The framework distinguishes itself through an integrated checkpointing system that automatically persists intermediate data artifacts to remote storage, allowing failed runs to be resumed from the last successful step. It

    Coordinates dependent execution chains by linking multiple independent pipelines through an event-driven architecture.

    Pythonagentsaiaws
    Ver en GitHub↗9,764
  • joelgrus/data-science-from-scratchAvatar de joelgrus

    joelgrus/data-science-from-scratch

    9,636Ver en GitHub↗

    This project is a collection of foundational machine learning algorithms and data science tools implemented in Python. It focuses on building the logic of these tools using basic programming primitives rather than relying on specialized libraries. The implementation covers several core domains, including a linear algebra library for matrix and vector operations, a statistical analysis toolkit for probability and hypothesis testing, and a framework for map-reduce distributed processing. It also includes implementations for natural language processing, graph theory for network analysis, and var

    Implements closeness centrality to determine node importance based on path lengths.

    Python
    Ver en GitHub↗9,636
  • je-suis-tm/quant-tradingAvatar de je-suis-tm

    je-suis-tm/quant-trading

    9,190Ver en GitHub↗

    This project is a Python financial analytics framework and quantitative trading library. It provides a suite of mathematical tools for asset pricing, statistical market analysis, and the development of algorithmic trading strategies. The library is distinguished by its focus on currency and commodity correlation modeling, using regression and normalization to identify exchange rate drivers. It features a specialized portfolio optimization engine that applies graph theory, such as clique centrality and degeneracy ordering, alongside quadratic programming to balance risk-adjusted returns. The

    Uses clique centrality to identify influential and strongly correlated assets for concentrated investment sets.

    Pythonalgorithmic-tradingbollinger-bandscommodity-trading
    Ver en GitHub↗9,190
  • microsoft/ufoAvatar de microsoft

    microsoft/UFO

    9,017Ver en GitHub↗

    UFO is a multi-device task orchestrator and LLM agent orchestration framework designed to decompose natural language requests into executable task graphs. It functions as a cross-platform UI automation tool capable of performing interactions on Windows and mobile devices while routing tasks to distributed agents based on their hardware and software capabilities. The system is distinguished by its RAG-enhanced agent architecture, which integrates external documentation and previous execution traces to improve decision-making. It employs a hybrid UI detection approach that combines computer vis

    Coordinates dependent execution chains and groups of subtasks assigned to specific devices for complex goal achievement.

    Pythonagentautomationcopilot
    Ver en GitHub↗9,017
  • clips/patternAvatar de clips

    clips/pattern

    8,852Ver en GitHub↗

    Pattern is a Python web mining library that functions as an HTML web scraper, a natural language processing toolkit, and a network analysis tool. It provides a mathematical framework for categorizing datasets through a vector space model library. The project enables the extraction of structured data from web services and the creation of searchable web content indexes. It processes unstructured text using sentiment analysis, part-of-speech tagging, and n-gram searching. The library covers machine learning classification through the training of models using perceptron algorithms and support ve

    Implements graph theory metrics like node centrality to identify influential entities within network maps.

    Python
    Ver en GitHub↗8,852
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Explorar subetiquetas

  • Drag Lifecycle MonitorsPatterns for tracking and reporting the state of drag-and-drop operations. **Distinct from Centralization Patterns:** Focuses on monitoring drag lifecycle state, distinct from general-purpose centralization patterns.
  • Event MediatorsSpecialized hubs that coordinate communication between decoupled components to eliminate direct dependencies. **Distinct from Centralization Patterns:** Focuses on the mediator pattern for inter-component communication rather than general system centralization or data aggregation.
  • Network Centrality Analyses4 sub-etiquetasApplying graph theory metrics like clique centrality to identify influential nodes within a network. **Distinct from Centralization Patterns:** Applies graph centrality to financial asset correlations rather than software architectural patterns
  • Observability PipelinesArchitectural patterns for aggregating and routing telemetry data through centralized processing layers. **Distinct from Centralization Patterns:** Distinct from general centralization patterns: focuses specifically on the observability data pipeline architecture rather than generic service interface unification.
  • Signaling RegistriesCentralized services used for peer discovery and the initial coordination of network handshakes. **Distinct from Centralization Patterns:** Focuses on the specific signaling function for P2P discovery rather than general architectural centralization patterns.
  • Simulation SynchronizersArchitectural patterns for synchronizing multiple independent simulation clients to a shared timeline. **Distinct from Centralization Patterns:** Distinct from general centralization by focusing on the temporal synchronization of agent instances in a simulation.
  • Workflow Execution Managers2 sub-etiquetasCentralized systems that coordinate task execution and prevent redundant job processing. **Distinct from Centralization Patterns:** Distinct from general centralization patterns: focuses on workflow execution and worker coordination.
  • Workflow SchedulersCentralized services that manage task queues and track global workflow state across distributed environments. **Distinct from Centralization Patterns:** Distinct from general centralization patterns: focuses specifically on workflow and task orchestration.