#distributed

H2O-3 presents a powerful in-memory platform for distributed, scalable machine learning with user-friendly interfaces in R, Python, Scala, Java, and JSON. It seamlessly integrates with big data technologies such as Hadoop and Spark, offering support for popular algorithms including GLM, XGBoost, Random Forests, and Deep Learning. Its extensible architecture allows developers to integrate custom algorithms and data transformations. Export models for rapid scoring in production environments. Built upon the foundation of H2O-2, it ensures easy installation via PyPI and CRAN for Python and R users, broadening accessibility and usability across various platforms. Comprehensive documentation fosters user engagement and community contribution, while simplifying complex terminology for better understanding.

Wgcloud offers a lightweight monitoring solution with a microservice Spring Boot architecture, designed for efficient system and network resource management. It supports diverse metrics such as CPU and memory usage, and provides features like network topology mapping, visualization, and real-time alerts. Its compatibility with multiple operating systems ensures streamlined data collection and enhanced operational efficiency.

Crawlab is a Golang-based web crawler management platform supporting multiple languages and frameworks such as Python and Scrapy. It features distributed architecture via Docker, simplifying deployment with tools like MongoDB and SeaweedFS. The flexible design supports task scheduling and integration without Scrapyd limitations, alongside an intuitive Vue-based UI.