Search Results for "performance testing" - Page 4
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Showing 512 open source projects for "performance testing"
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8 Monitoring Tools in One APM. Install in 5 Minutes.AppSignal works out of the box for Ruby, Elixir, Node.js, Python, and more. 30-day free trial, no credit card required.
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Full-stack observability with actually useful AI | Grafana CloudBuilt on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
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PgRx
Build Postgres Extensions with Rust
pgrx is a Rust framework for developing PostgreSQL extensions, making it easier to write safe, high-performance native extensions in Rust. It handles the boilerplate and unsafe FFI needed to interface with Postgres internals, allowing developers to focus on logic. With built-in support for SQL generation, testing, and deployment, pgrx streamlines the extension creation process while embracing Rust’s safety guarantees. -
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TextWorld
TextWorld is a sandbox learning environment for the training
TextWorld is a learning environment designed to train reinforcement learning agents to play text-based games, where actions and observations are entirely in natural language. Developed by Microsoft Research, TextWorld focuses on language understanding, planning, and interaction in complex, narrative-driven environments. It generates games procedurally, enabling scalable testing of agents’ natural language processing and decision-making abilities. -
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Simple Evals
Lightweight framework for evaluating large language model performance
simple-evals is a lightweight evaluation framework developed by OpenAI for quickly testing models against small, focused benchmarks. It is designed to help researchers and developers run targeted evaluations without the complexity of large-scale pipelines. By emphasizing simplicity, the framework makes it easy to define new tasks, run evaluations, and interpret results in a reproducible way. It is particularly useful for sanity checks, exploratory research, and comparing performance across different models or configurations. ... -
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LangWatch
The platform for LLM evaluations and AI agent testing
LangWatch is an open-source observability and monitoring platform designed to help developers evaluate and improve applications built with large language models. The platform provides tools for tracking model interactions, analyzing prompt behavior, and identifying issues such as hallucinations, latency problems, or unexpected responses. By collecting telemetry data from AI applications, LangWatch allows developers to understand how their systems perform in real-world usage scenarios. The... -
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Agent Behavior Monitoring
The open source post-building layer for agents
Agent Behavior Monitoring is an open-source framework designed to monitor, evaluate, and improve the behavior of AI agents operating in real or simulated environments. The system focuses on agent behavior monitoring by collecting interaction data and analyzing how agents perform across different scenarios and tasks. Developers can use the framework to observe agent actions in both online production environments and offline evaluation settings, making it useful for debugging and performance... -
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TapeAgents
A framework that facilitates all stages of LLM development
TapeAgents is a framework that facilitates all stages of the Large Language Model (LLM) agent development lifecycle, providing tools for building, testing, and deploying AI agents. -
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subfinder
Fast passive subdomain enumeration tool
Subfinder is a high-performance passive subdomain discovery tool built for fast and reliable asset enumeration. It focuses exclusively on collecting valid subdomains from a wide range of passive online sources, prioritizing accuracy and speed over intrusive scanning techniques. The project is widely used in bug bounty hunting, penetration testing, and attack surface mapping because it minimizes noise while producing actionable results. -
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langrocks
Tools like web browser, computer access and code runner for LLMs
Langrocks is a programming language experimentation toolkit that enables developers to create, test, and optimize custom programming languages. -
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NGINX Admin’s Handbook
How to improve NGINX performance, security, and other important things
nginx-admins-handbook is a practical, in-depth guide for configuring, securing, and operating NGINX across real-world deployments. It distills years of research, notes, and field experience into a single handbook that complements the official docs with concrete rules, explanations, and curated external references. The handbook spans fundamentals and advanced topics alike, from HTTP and SSL/TLS basics to reverse proxy patterns, performance tuning, debugging workflows, and hardening... -
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Prompt flow
Build high-quality LLM apps
Prompt flow is a suite of development tools designed to streamline the end-to-end development cycle of LLM-based AI applications, from ideation, prototyping, testing, and evaluation to production deployment and monitoring. It makes prompt engineering much easier and enables you to build LLM apps with production quality. -
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mlx
MLX: An array framework for Apple silicon
MlX offers a local web interface to browse, download, and run ML models via Hugging Face or local sources. It supports searching by tags or tasks, visualization of model metadata, quick inference demos, automatic setup of runtime environments, and works with PyTorch, TensorFlow, and ONNX. Ideal for researchers exploring and testing models via browser. -
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BenchmarkTools.jl
A benchmarking framework for the Julia language
BenchmarkTools makes performance tracking of Julia code easy by supplying a framework for writing and running groups of benchmarks as well as comparing benchmark results. This package is used to write and run the benchmarks found in BaseBenchmarks.jl. The CI infrastructure for automated performance testing of the Julia language is not in this package but can be found in Nanosoldier.jl. -
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JMH Gradle Plugin
Integrates the JMH benchmarking framework with Gradle
...Developers can run benchmarks via Gradle commands, produce reports, and compare performance over time. This reduces the manual effort of setting up JMH, making performance testing a natural part of the development cycle. The plugin is especially useful in projects where regression in execution speed or memory use must be carefully monitored. -
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Barter
Open-source Rust framework for building event-driven systems
Barter is an open-source, Rust-based ecosystem of libraries for building high-performance, event-driven algorithmic trading systems—covering live trading, paper trading, and backtesting. It is designed for safety, speed, and flexibility in quantitative finance workflows. Use mock MarketStream or Execution components to enable back-testing on a near-identical trading system as live-trading. Centralised cache-friendly state management system with O(1) constant lookups using indexed data structures. ... -
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Grafbase
The Grafbase GraphQL Federation Gateway
Grafbase is an open-source GraphQL federation gateway and API platform designed to unify multiple backend services and data sources into a single, high-performance GraphQL interface. The project provides a Rust-based gateway that acts as the central layer for composing and managing distributed APIs, particularly in microservice architectures where data may come from many independent systems. By supporting GraphQL federation standards, the platform enables teams to combine multiple subgraphs... -
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NOFX
Open source AI trading OS for autonomous multi-model trading systems
NOFX is an open source AI-powered trading operating system designed to automate financial trading workflows using autonomous AI agents. It acts as an infrastructure layer that transforms market data into AI-driven trade decisions and execution. Instead of requiring users to manually configure machine learning models, data sources, and API integrations, the system allows AI components to perceive market conditions, select models, and perform trading actions automatically. It supports running... -
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TensorFlow Serving
Serving system for machine learning models
TensorFlow Serving is a flexible, high-performance serving system for machine learning models, designed for production environments. It deals with the inference aspect of machine learning, taking models after training and managing their lifetimes, providing clients with versioned access via a high-performance, reference-counted lookup table. TensorFlow Serving provides out-of-the-box integration with TensorFlow models, but can be easily extended to serve other types of models and data. The... -
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rip2
A safe and ergonomic alternative to rm
rip is a rust-based rm with a focus on safety, ergonomics, and performance. It favors a simple interface and does not implement the xdg-trash spec or attempt to achieve the same goals. Deleted files get sent to the graveyard (typically /tmp/graveyard-$USER, see notes on changing this) under their absolute path, giving you a chance to recover them. No data is overwritten. If files that share the same path are deleted, they will be renamed as numbered backups. -
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AutoAgent AI
Autonomous harness engineering
...The system is particularly useful for building domain-specific agents that need continuous performance improvement. -
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JAX Toolbox
Public CI, Docker images for popular JAX libraries
JAX Toolbox is a development toolkit designed to streamline and optimize the use of JAX for machine learning and high-performance computing on NVIDIA GPUs. It provides prebuilt Docker images, continuous integration pipelines, and optimized example implementations that help developers quickly set up and run JAX workloads without complex configuration. The project supports popular JAX-based frameworks and models, including architectures used for large-scale pretraining such as GPT and LLaMA... -
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osu!framework
A game framework written with osu! in mind.
...If you are interested in creating a project using the framework, please start from the getting started wiki resources (or jump straight over to the project templates). You can either start off from an empty project, or take a peek at a working sample game. Either way, full project structure, cross-platform support, and a testing setup are included! This framework is intended to take steps beyond what you would normally expect from a game framework. This means things like basic UI elements, text rendering, advanced input handling (textboxes) and performance overlays are provided out-of-the-box. Any of the osu! code that is deemed useful to other game projects will live in this framework project. ... -
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Hurl
Hurl, run and test HTTP requests with plain text
Hurl is a command line tool that runs HTTP requests defined in a simple plain text format. It can chain requests, capture values and evaluate queries on headers and body responses. Hurl is very versatile: it can be used for both fetching data and testing HTTP sessions. Hurl makes it easy to work with HTML content, REST / SOAP / GraphQL APIs, or any other XML / JSON-based APIs. Hurl can run HTTP requests but can also be used to test HTTP responses. Different types of queries and predicates... -
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Paddler
Open-source LLM load balancer and serving platform for hosting LLMs
Paddler is an open-source LLM infrastructure platform designed to deploy, manage, and scale large language models on private infrastructure. The system acts as a specialized load balancer and serving layer for language models, enabling organizations to run inference workloads without relying on external API providers. It supports running models locally through engines such as llama.cpp while distributing requests across multiple compute nodes to improve performance and reliability. The... -
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Happy DOM
Happy DOM is a JavaScript implementation of a web browser
Happy DOM is a JavaScript implementation of a web browser without its graphical user interface. It includes many web standards from WHATWG DOM and HTML. The goal of Happy DOM is to emulate enough of a web browser to be useful for testing, scraping web sites, and server-side rendering. Happy DOM focuses heavily on performance and can be used as an alternative to JSDOM. Happy DOM now supports Declarative Shadow DOM which can be used for server-side rendering of web components. This package makes it possible to use Happy DOM with Jest. -
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Headless
Create a virtual X screen from Ruby, record videos and take screenshot
...It enables developers to programmatically control web pages, perform navigation, and extract content efficiently. The tool is particularly useful for tasks such as scraping, testing, and automation workflows where rendering a full browser UI is unnecessary. It supports executing scripts that interact with DOM elements, simulate user actions, and handle asynchronous content. headless is designed for performance, minimizing overhead while maintaining compatibility with modern web standards. Its architecture allows integration into pipelines and automation systems, making it suitable for backend processing tasks. ...
