Search Results for "process metrics" - Page 2
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Showing 90 open source projects for "process metrics"
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Why & When
Exposing the JDK Flight Recorder as a Spring Boot Actuator Endpoint
This is a Spring Boot 2 Starter exposing the JDK Flight Recorder as a Spring Boot Actuator Endpoint. Normally the JDK Flight Recorder is available locally or by JMX remote. Depending on your deployment scenario shell or JMX access might not be available for the application server. Here comes this handy starter into play! This starter adds a new Spring Boot Actuator endpoint for JDK Flight Recorder remote control. This RESTful endpoint allows starting and stopping Flight Recording and... -
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watercrawl
AI-ready web crawler that extracts and structures website content
WaterCrawl is an open source web crawling and data extraction platform designed to transform website content into structured data suitable for machine learning and AI workflows. It enables developers and researchers to crawl web pages, extract meaningful information, and convert it into formats that are easier to process and analyze. It provides a modern crawling system that can automatically navigate links, control crawl depth, and collect content from targeted sections of a website. WaterCrawl supports customizable extraction rules so users can focus only on relevant elements while ignoring unnecessary page components. WaterCrawl also offers real-time monitoring capabilities, allowing users to track crawling progress, performance metrics, and errors during large data collection jobs. ... -
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gopro-dashboard-overlay
Programs to process GoPro MP4 & Generic GPX/FIT files
gopro-dashboard-overlay is a multimedia processing toolkit that generates data-rich overlays on videos using telemetry data from GoPro cameras or external GPS sources. It processes video files alongside GPX or FIT data to render dashboards displaying metrics such as speed, distance, and location directly onto footage. The system supports a wide range of layouts, including maps, gauges, and charts, which can be customized through configuration files. It integrates FFmpeg for rendering and... -
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PyBroker
Algorithmic Trading in Python with Machine Learning
Are you looking to enhance your trading strategies with the power of Python and machine learning? Then you need to check out PyBroker! This Python framework is designed for developing algorithmic trading strategies, with a focus on strategies that use machine learning. With PyBroker, you can easily create and fine-tune trading rules, build powerful models, and gain valuable insights into your strategy’s performance. -
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Opik
Debug, evaluate, and monitor your LLMapps, RAG systems, and agentic AI
Confidently evaluate, test, and monitor LLM applications. Opik is an open-source platform for evaluating, testing, and monitoring LLM applications. Built by Comet. Record, sort, search, and understand each step your LLM app takes to generate a response. Manually annotate, view, and compare LLM responses in a user-friendly table. Log traces during development and in production. Run experiments with different prompts and evaluate against a test set. Choose and run pre-configured evaluation... -
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SDGym
Benchmarking synthetic data generation methods
...Measure performance and memory usage across different synthetic data modeling techniques – classical statistics, deep learning and more! The SDGym library integrates with the Synthetic Data Vault ecosystem. You can use any of its synthesizers, datasets or metrics for benchmarking. You also customize the process to include your own work. Select any of the publicly available datasets from the SDV project, or input your own data. Choose from any of the SDV synthesizers and baselines. Or write your own custom machine learning model. In addition to performance and memory usage, you can also measure synthetic data quality and privacy through a variety of metrics. ... -
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PRAXIST
Autonomous research system for measurable computer-executable research
...Runs can be monitored, stopped, resumed, and replayed, with the task project remaining the source of truth for objectives, metrics, baselines, and domain constraints. -
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Weibo Crawler
Python crawler for collecting and downloading Sina Weibo user data
weibo-crawler is a Python-based data collection tool designed to retrieve information from Sina Weibo user accounts. It automates the process of gathering posts, user profile details, and engagement metrics from one or more target accounts. weibo-crawler can extract comprehensive information about users, including profile attributes such as nickname, follower count, following count, and account metadata. It also captures detailed data about each post, including the content, publishing time, topics, mentions, likes, reposts, and comments. ... -
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Broadway
Concurrent and multi-stage data ingestion and data processing
Broadway is a data processing library for Elixir designed to handle high-throughput, concurrent workloads with ease. It provides an abstraction for defining pipelines that consume data from sources like RabbitMQ, Kafka, Amazon SQS, or custom producers. Each pipeline is fault-tolerant and backpressure-aware, ensuring stable throughput even under load. The library integrates seamlessly with GenStage and OTP supervision trees, making it highly resilient in production. Developers can enrich... -
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trench
Open-Source Analytics Infrastructure
Trench is an open-source analytics infrastructure designed for tracking events and performing real-time analysis of application data at scale. The system is built on top of high-performance data technologies including Apache Kafka and ClickHouse, which allows it to ingest and process very large volumes of events while maintaining fast query performance. It was originally developed to solve scaling challenges in product analytics systems where traditional relational databases become inefficient as event tables grow. The platform enables developers to collect events such as page views, user actions, and behavioral metrics while storing them in a column-oriented analytics database optimized for time-series workloads. ... -
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WGCLOUD
Visibility into servers, applications, and infrastructure
WGCLOUD is a distributed operations and maintenance monitoring platform designed to provide comprehensive visibility into servers, applications, and infrastructure through a lightweight yet highly integrated architecture. Built on a Spring Boot microservices foundation with an agent-server model, the system emphasizes rapid deployment, minimal configuration overhead, and automated operation for large-scale environments. It collects extensive host metrics such as CPU usage, temperature,... -
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Anthropic's Original Performance
Anthropic's original performance take-home, now open for you to try
Anthropic's Original Performance repository contains the publicly released version of a performance challenge originally used by Anthropic as part of their technical interview process, offering developers the opportunity to optimize and benchmark low-level code against simulated models. The project sets up a baseline performance problem where participants work to reduce simulated “clock cycles” required to run a given workload, effectively challenging them to engineer faster code under... -
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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... -
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Laravel Horizon
Dashboard and code-driven configuration for Laravel queues
Horizon provides a beautiful dashboard and code-driven configuration for your Laravel-powered Redis queues. Horizon allows you to easily monitor key metrics of your queue system such as job throughput, runtime, and job failures. All of your worker configuration is stored in a single, simple configuration file, allowing your configuration to stay in source control where your entire team can collaborate. When using Horizon, all of your queue worker configuration is stored in a single, simple... -
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faas-netes
Serverless Functions For Kubernetes
...You will find specific instructions and additional links in the documentation. OpenFaaS (Functions as a Service) is a framework for building serverless functions with Docker and Kubernetes which has first-class support for metrics. Any process can be packaged as a function enabling you to consume a range of web events without repetitive boilerplate coding. -
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flagger
Progressive delivery Kubernetes operator (Canary, A/B Testing)
Flagger is a progressive delivery tool that automates the release process for applications running on Kubernetes. It reduces the risk of introducing a new software version in production by gradually shifting traffic to the new version while measuring metrics and running conformance tests. Flagger implements several deployment strategies (Canary releases, A/B testing, Blue/Green mirroring) using a service mesh (App Mesh, Istio, Linkerd, Kuma, Open Service Mesh) or an ingress controller (Contour, Gloo, NGINX, Skipper, Traefik, APISIX) for traffic routing. ... -
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Bull
Queue package for handling distributed jobs and messages in NodeJS
The fastest, most reliable, Redis-based queue for Node. Carefully written for rock solid stability and atomicity. If you want to start using the next major version of Bull written entirely in Typescript you are welcome to the new repo here. Otherwise you are very welcome to still use Bull, which is a safe, battle tested codebase. If you need high quality production Redis instances for your Bull projects, please consider subscribing to RedisGreen, leaders in Redis hosting that works perfectly... -
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Benthos
Fancy stream processing made operationally mundane
Benthos is a high performance and resilient stream processor, able to connect various sources and sinks in a range of brokering patterns and perform hydration, enrichments, transformations and filters on payloads. It comes with a powerful mapping language, is easy to deploy and monitor, and ready to drop into your pipeline either as a static binary, docker image, or serverless function, making it cloud native as heck. Delivery guarantees can be a dodgy subject. Benthos processes and... -
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Apache APISIX
The cloud-native API gateway
...Compared with traditional API gateways, APISIX has dynamic routing and plug-in hot loading, which is especially suitable for API management under micro-service system. You can use Apache APISIX as a traffic entrance to process all business data, including dynamic routing, dynamic upstream, dynamic certificates, A/B testing, canary release, blue-green deployment, limit rate, defense against malicious attacks, metrics, monitoring alarms, service observability, service governance, etc. -
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PaSa
An advanced paper search agent powered by large language models
PaSa is an open-source “paper search agent” built around large language models (LLMs), designed to automate the process of academic literature retrieval with human-like decision making. Instead of simply translating a query into keywords and returning a flat list of matching papers, PaSa uses a dual-agent architecture (Crawler + Selector) that can iteratively search, read, analyze, and filter academic publications — simulating how a researcher might dig through citation networks, expand... -
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htop
htop - an interactive process viewer
htop is an interactive process monitoring and system management tool designed for Linux, macOS, BSD, and other Unix-like operating systems. It provides a real-time, color-coded interface for viewing system performance, running processes, CPU usage, memory consumption, and other critical system metrics. Unlike traditional command-line monitoring tools, htop offers an intuitive and user-friendly interface with mouse support, customizable views, and interactive controls. ... -
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TOPCEE
Python GUI tool for estimating plant CAPEX, OPEX, and profitability
TOPCEE (Toyese Oyegoke Process Cost & Economic Evaluator) is a GUI-based Python application designed to assist chemical engineers, researchers, and students in evaluating the profitability of chemical/process plants. The app calculates capital and operational expenditures (CAPEX & OPEX) and provides key profitability metrics such as: **ROI (Return on Investment) **IRR (Internal Rate of Return) **NPV (Net Present Value) **Payback Period (Discounted and Non-Discounted) **Benefit-Cost Ratios Users input plant-specific values like feedstock costs, operating time, product price, and equipment cost — and the tool generates real-time visualizations and results. ... -
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Geziyor
Blazing fast Go framework for web crawling and data scraping tasks
...Geziyor supports use cases such as data mining, monitoring web content, and automated testing workflows. It provides a flexible architecture where developers define parsing functions that process responses and extract the desired data. Geziyor includes features for managing requests, handling cookies, respecting robots rules, and exporting collected data in multiple formats. With built-in tools for caching, metrics collection, and proxy management, it enables developers to build robust and customizable scraping systems using Go. -
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HardwareMon
A modern crossplatform Linux and Windows tool for hardware metrics.
HardwareMon is a modern hardware monitoring and performance analytics application for Windows and Linux. Designed for both beginners and advanced users, HardwareMon makes it easy to understand how your system is performing through a clean, intuitive interface and real-time telemetry. Monitor CPU, memory, GPU, temperatures, power usage, clock speeds, and running processes while exploring historical performance data through interactive analytics and graphs. Whether you're gaming,... -
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Automated Tool for Optimized Modelling
Automated Tool for Optimized Modelling
During the exploration phase of a machine learning project, a data scientist tries to find the optimal pipeline for his specific use case. This usually involves applying standard data cleaning steps, creating or selecting useful features, trying out different models, etc. Testing multiple pipelines requires many lines of code, and writing it all in the same notebook often makes it long and cluttered. On the other hand, using multiple notebooks makes it harder to compare the results and to...
