57 रिपॉजिटरी
Resources explaining the low-level design and operational principles of complex software systems.
Distinguishing note: General system internals rather than specific database or OS internals.
Explore 57 awesome GitHub repositories matching software engineering & architecture · System Internals. Refine with filters or upvote what's useful.
यह प्रोजेक्ट वितरित सिस्टम आर्किटेक्चर और बैकएंड इंफ्रास्ट्रक्चर डिज़ाइन पर केंद्रित एक व्यापक शैक्षिक संसाधन और अध्ययन मार्गदर्शिका है। यह जटिल सॉफ्टवेयर सिस्टम को डिज़ाइन करने के लिए आवश्यक स्केलेबिलिटी, विश्वसनीयता और प्रदर्शन में महारत हासिल करने के लिए एक संरचित पाठ्यक्रम प्रदान करता है। रिपॉजिटरी तकनीकी साक्षात्कार की तैयारी के लिए एक व्यवस्थित दृष्टिकोण प्रदान करके खुद को अलग करती है, जिसमें डिज़ाइन पैटर्न, आर्किटेक्चरल ट्रेड-ऑफ और स्पेस रिपिटिशन टूल शामिल हैं ताकि उपयोगकर्ताओं को जटिल अवधारणाओं को याद रखने में मदद मिल सके। यह बाधा-संचालित विश्लेषण पर जोर देती है, उपयोगकर्ताओं को सिखाती है कि आर्किटेक्चरल डिज़ाइन तैयार करते समय विलंबता (latency), स्थिरता (consistency) और उपलब्धता (availability) जैसी प्रतिस्पर्धी आवश्यकताओं का मूल्यांकन कैसे करें। सामग्री सिस्टम डिज़ाइन क्षमताओं के एक व्यापक स्पेक्ट्रम को कवर करती है, जिसमें डेटाबेस स्केलिंग, ट्रैफ़िक प्रबंधन और इंफ्रास्ट्रक्चर ऑप्टिमाइज़ेशन की रणनीतियाँ शामिल हैं। यह हॉरिजॉन्टल स्केलिंग, मल्टी-लेयर्ड कैशिंग, एसिंक्रोनस संचार और सर्विस डिस्कवरी के लिए तकनीकों का विवरण देती है, साथ ही संसाधन अनुमान और क्षमता नियोजन करने के लिए फ्रेमवर्क भी प्रदान करती है। दस्तावेज़ीकरण को एक अध्ययन मार्गदर्शिका के रूप में व्यवस्थित किया गया है, जो बैकएंड इंजीनियरिंग और बड़े पैमाने पर सिस्टम डिज़ाइन के मूलभूत सिद्धांतों के माध्यम से एक व्यवस्थित पथ प्रदान करती है।
Explains architectural strategies for unifying service interfaces and security filtering.
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.
This project is a curated knowledge repository designed to support the professional development of software engineers. It functions as a comprehensive index of industry best practices, methodologies, and design principles, providing a structured roadmap for those seeking to improve their technical skills, architectural decision-making, and career trajectory. The repository distinguishes itself through a community-driven approach, relying on peer-reviewed contributions to maintain an up-to-date collection of resources. It organizes vast amounts of technical information into a hierarchical taxo
Provides insights into the internal design and operational principles of complex software systems.
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.
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.
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.
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.
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.
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.
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.
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.
Playwright for Python is a browser automation framework designed for end-to-end testing, web scraping, and user interaction simulation. It functions as a headless browser controller that enables programmatic navigation, data extraction, and the execution of complex workflows across multiple rendering engines. The framework distinguishes itself through an actionability-aware interaction engine that automatically verifies element readiness before performing actions, significantly reducing test flakiness. It utilizes isolated browser contexts to maintain separate storage and cookies for parallel
Outputs detailed diagnostic information about internal operations to assist in identifying failures.
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.
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.
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.
Detect-It-Easy is a binary file identifier and analysis toolkit designed to determine file formats, compilers, and packers. It functions as a binary file identifier that utilizes signature matching and heuristic analysis to identify executable and archive formats. The project includes a custom file signature engine and a scriptable rule system for defining and applying detection logic to identify specific binary patterns. It features specialized detectors for Android packages, such as APK and DEX files, and a malware packer detector to identify protections, obfuscators, and virus families. T
Allows for the examination of internal system layouts to understand operating system data and memory organization.
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.
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.
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.
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 betweenness centrality to measure node influence via shortest path counts.