HTTP API Gateway

Service Discovery and Governance Platform for Microservice and Distributed Architecture

Computational framework for reinforcement learning in traffic control

🐳 🚦 Docker Traffic Control - network rate limiting, emulating delays, losses, duplicates, corrupts and reorders of network packets using only container labels or a command-line interface.

traffic control in pure go - it allows to read and alter queues, filters and classes

AppActive: A middleware dedicate to building multi-site active/active application architectures（阿里巴巴开源的一款标准、通用且功能强大的，致力于构建应用多活架构的开源中间件）

Test your application on Kubernetes in a brand new simple way⚡ 轻量高效的微服务本地联调测试工具

NetLimiter-like bandwidth limiting and QoS for Linux

A lightweight Python-based Web-GUI for Linux traffic control (tc) to set, view and delete traffic shaping rules.

Lightweight Java SDK used as Proxyless Service Governance

Lightweight Go SDK used as Proxyless Service Governance

A new approach to fighting cross-session tracking: multi-layer online fingerprint obfuscation. Spoofs browser/OS (headers & JS), hardware, TLS cipher-suite, canvas, peripherals and much more.

Pseudo-driver for the intermediate queue device.

An EBPF based IPv4/IPv6 firewall with integrations for OpenZiti Zero-Trust Framework edge-routers and tunnellers

CortexBrain is an ambitious open-source project designed to build an intelligent, lightweight, and highly efficient monitoring platform for distributed cloud and hybrid (cloud–edge) workflows

Traffic Lights Control with Deep Learning

Adaptive real-time traffic light signal control system using Deep Multi-Agent Reinforcement Learning

Convert network filtering rules from various formats into BPF programs

We developed a system that leverages on YOLO Machine Learning Model for managing the traffic flow based on the vehicle density.

This is a web-based tool for simulating network quality. Ideal for use with software routers on Linux platform. It focuses on simulating weak network (poor network) conditions, with built-in scenario models(3G, 4G, Wi-Fi, Starlink, etc.) and combinations of parameters such as packet loss, delay, jitter, and bandwidth limitation, etc.