Module to watch over different processes, that application consists of
Generates CRC hashes for strings - for use by node redis clients to determine key slots.
Find the position of grapheme cluster breaks in a string
Simple yet powerful wrapper over node.js cluster API. This module is inspired by impressive, but abandoned project Cluster created by TJ Holowaychuk.
GCP provider for Alchemy v2 (Effect-based IaC). Resources for Project, Cluster, NodePool, Compute, ManagedLustre, ServiceUsage, ServiceNetworking, Cloud Run (Service + Job + IAM), with ADC-backed credentials and target-side IAM bindings.
The official OpenSearch client for Node.js
React-leaflet-cluster is a plugin for react-leaflet. A wrapper component of Leaflet.markercluster.
Client for prometheus
Fast nd point clustering.
[](https://www.npmjs.com/package/@camunda8/sdk)
Cluster management for puppeteer
Group points into clusters based on their spatial proximity or properties.
Matter.js main entrypoint
Matter protocol in pure js
AWS SDK for JavaScript Ecs Client for Node.js, Browser and React Native
The official Couchbase Node.js Client Library.
Fast and small Node.js Worker_Threads and Cluster Worker Pool
Terminal and Web console for Kubernetes
Takes a set of points and partition them into clusters according to DBSCAN's data clustering algorithm.
Provides Beautiful Animated Marker Clustering functionality for Leaflet
cluster workers reload
Layout algorithms for visualizing hierarchical data.
extensible multi-core server manager
Sharing Connection among Multi-Process Nodejs
Tool with some similarities to puppet but specializing in fast development iteration and continuous deployment. Specifically initially for use with justin.tv / twitch.tv project clusters.
Forum and mailing list project aiming to be a complete Direct Democracy implementation where everybody can propose polls, vote on them, or delegate their voice to someone else. Trust through: - P2P cluster - PGP signatures - electoral lists
Define your project in terms of blocks, configurations, tests, and modes. Install or Create recipes and/or plugins to define actions, compute clusters, and tools for simulation, synthesis, or anything else. Run your actions, test_lists, or tests in parallel, with dependencies, on a cluster, or locally. Share your recipes and plugins with people down the hall and around the world.
Some tools for dynamically creating clusters on top of OpenNebula. This project is a playground and implementations will be most likely domain specific to my company in early versions, although I try to abstract from that as much as possible. This is WORK IN PROGRESS! All versions <1.0.0 should be treated as development and unstable versions.
TTK is designed to help you while you are writing dynamic tests for your projects. It keeps track of your test strategies by means of a solid dynamic hierarchy of test strategy classes. The only way to be 100% generic is to be extensible, after all. Network distribution strategies can also be written since TTK provides cluster features. TTK understands YAML and XML as input and output languages to describe both tests and results.
JRuby Mahout is a gem that unleashes the power of Apache Mahout in the world of JRuby. Mahout is a superior machine learning library written in Java. It deals with recommendations, clustering and classification machine learning problems at scale. Until now it was difficult to use it in Ruby projects. You'd have to implement Java interfaces in Jruby yourself, which is not quick especially if you just started exploring the world of machine learning.
Uttk is designed to help you while you are writing dynamic tests for your projects. It keeps track of your test strategies by means of a solid dynamic hierarchy of test strategy classes. The only way to be 100% generic is to be extensible, after all. Network distribution strategies can also be written since Uttk provides cluster features. Uttk understands YAML and Ruby as input languages and speaks YAML, XML and HTML as output languages.
Vagrant-ZFS is a plugin for Vagrant to automate cloning and sharing ZFS filesystems from the host machine to a guest VM. This is useful for things like bringing up multiple VMs to test database clustering without requiring you to manually copy large amounts of data into multiple locations on your host or syncing data from host to VMs. This project is still in the very early stages, so proceed with caution.
== coral This gem is simply a meta package that installs and requires the CORL gem. Note: CORL is still early in development! DO NOT USE IN PRODUCTION YET!! Now you get to hear the story of two names. Short story first; We switched to the CORL name (github.com/coralnexus/corl). If your interested in why: The original name of the CORL project was Coral, and we were exited when we found the Ruby gem name "coral" available. Our first versions of our CORL system were named coral_core, coral_cloud, coral_vagrant, coral_plan, and many more were planned. We created a meta gem (this one) to install a core combination of gems. During the course of development we found another project that came before ours that uses the name coral, so we decided to update our project name, so as to avoid conflicts. For us Coral is more than a word, it is a concept that embodies dynamic ecosystems supporting a rich variety of lifeforms. Coral are very interesting creatures and we endeavor to create software that helps build dynamic ecosystems of digital creatures. We decided to use an acronym that sounds like the word Coral because the acronym fit with our desire to create something good for administration but also good for flexible research, so we came to Cluster Orchestration and Research Library. We split the core components out into a small concurrent plugin framework called Nucleon, upon which CORL is built. All of our coral sub gems are integrated into these two. This gem exists only as a installer for people who accidentally spell coral the right way when trying to install the CORL system. Use the CORL gem instead. == Copyright Licensed under Apache license, version 2. See LICENSE.txt for further details. Copyright (c) 2013-2014 Adrian Webb <adrian.webb@coralnexus.com> Coral Technology Group LLC
Ruby Scientist and Graphics is a practical data science toolkit for Ruby. It includes a lightweight built-in DataFrame for loading, cleaning, and transforming data; quick descriptive statistics and correlations; charting via Gruff (bar and line); and simple ML utilities (linear regression and k-means)—all behind a small, unified, pandas-inspired API. Key features: - Load data from CSV and JSON. - Clean and transform (remove/add columns, handle missing values, limit rows). - Describe datasets and compute correlations quickly. - Create bar and line charts with customization options. - Train/predict with linear regression; cluster with k-means. - Save/load project state (data + trained model) and run simple pipelines. - Optional backend adapters (e.g., Rover) while keeping the same API. Ideal for analysts and developers who want to explore data in Ruby without relying on Python or R. Note: plotting via Gruff uses rmagick, which requires ImageMagick installed on the system.
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