Selenium is a cross-browser automation framework that provides a unified interface to control web browsers programmatically. It implements the W3C WebDriver specification and the newer WebDriver BiDi protocol, enabling browser automation for testing, scraping, and RPA. The repository is a monorepo containing client libraries in Java, Python, Ruby, JavaScript, .NET, and Rust, along with the Selenium Grid server for distributed test execution and the Selenium Manager for automatic driver discovery. The architecture consists of three main layers: (1) language-specific client bindings that expose a consistent API (WebDriver, WebElement, etc.) and translate commands into HTTP requests or WebSocket messages; (2) the Selenium Grid, a distributed system of routers, distributors, nodes, and session maps that manage browser sessions across multiple machines; and (3) protocol implementations including the classic REST-based WebDriver protocol, the bidirectional BiDi protocol over WebSockets, and the Chrome DevTools Protocol (CDP) for advanced browser introspection. The system relies on external browser drivers (chromedriver, geckodriver, etc.) and communicates with browsers via HTTP and WebSocket. Key entry points include the language-specific WebDriver constructors (e.g., webdriver.Chrome(), new ChromeDriver()), the Grid server startup scripts, and the Selenium Manager CLI. Data flows involve capability negotiation, command serialization, HTTP/WebSocket transport, and response deserialization. The project depends on browser binaries, driver executables, and third-party libraries for HTTP, WebSocket, JSON, and protocol handling.

This repository provides Docker images and Kubernetes Helm charts for deploying Selenium Grid, the industry-standard browser automation framework. It covers all major browser backends (Chrome, Firefox, Edge, Chromium) and supports multiple deployment modes: standalone single-container, hub-and-node, fully distributed grid, and dynamic grid with Docker-in-Docker or Kubernetes backends. The architecture follows a microservice pattern where each Grid component (Router, Distributor, Session Queue, Nodes, etc.) runs in its own container, orchestrated by supervisord. Beyond core Grid images, the repo includes a comprehensive monitoring stack with a Go-based Prometheus exporter that scrapes the Grid GraphQL endpoint, pre-built Grafana dashboards, and a KEDA external scaler for Kubernetes native autoscaling. Video recording and upload services are provided as sidecar containers, with both event-driven (ZeroMQ) and polling-based implementations. The CI/CD pipeline is extensive, with GitHub Actions workflows for building multi-architecture images (amd64/arm64), running integration tests, scanning for vulnerabilities, and publishing to Docker Hub and GHCR. The codebase is well-tested with unit tests for Go components, Python integration tests for autoscaling, and Java/Playwright browser tests. Despite its complexity, the repository demonstrates solid engineering practices with clear separation of concerns, reusable shell libraries, and automated dependency management via Renovate and Dependabot.