Anteon (formerly Ddosify) is an open-source platform for Kubernetes monitoring and performance testing. It provides a CLI-based load testing tool (Ddosify) that supports scenario-based testing with dynamic variable injection, extraction from responses, and assertions. Additionally, it includes an eBPF-based agent (Alaz, in a separate repository) for Kubernetes service map creation and real-time metrics collection without sidecars. The self-hosted deployment (in the selfhosted directory) orchestrates the platform using Docker Compose. The core engine is written in Go with a modular architecture, featuring pluggable components for requesters, reporting, and scripting.
This repository contains a Unity Editor tool for monitoring and visualizing PlayableGraphs in real-time. The tool displays the topology of PlayableGraphs showing nodes and connections, allows inspection of node details (playable properties, clip information, etc.), and provides UI controls for layout, refresh rate, and visibility options. It implements a modular architecture with separate concerns for the main window, graph view, node representations, object pooling, and utility functions. The tool supports various Playable node types with specific visualizations and handles edge cases like circular references in PlayableGraphs.
This repository contains the Apache SkyWalking Nginx Agent, a Lua-based library that provides distributed tracing capabilities for Nginx and OpenResty deployments. The agent integrates with Nginx's Lua API to automatically trace incoming and outgoing HTTP requests, propagate trace context between services using custom headers (sw8 and sw8-correlation), and report trace data to a SkyWalking OAP server. The architecture uses Nginx's phased execution model (init_worker, rewrite, body_filter, log) to manage the tracing lifecycle, with a shared dictionary for buffering trace segments and a timer for periodic reporting and heartbeats. The codebase demonstrates strong engineering practices with clear separation of concerns, comprehensive error handling, and performance optimizations like table pooling to reduce garbage collection pressure in LuaJIT. Several components show particular craftsmanship and reusability: the utility module provides high-performance table pooling and ID generation; the correlation context module implements lightweight context propagation via base64-encoded headers; and the segment reference module handles trace context serialization for cross-process tracing.