RPC between cluster master and children
Client for prometheus
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
AWS SDK for JavaScript Ecs Client for Node.js, Browser and React Native
OCI NodeJS client for Cluster Placement Groups Service
extensible multi-core server manager
React-leaflet-cluster is a plugin for react-leaflet. A wrapper component of Leaflet.markercluster.
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.
[](https://www.npmjs.com/package/@camunda8/orchestration-cluster-api) [](https://www.npmjs.com/packa
A JavaScript library that breaks strings into their individual user-perceived characters (including emojis!)
Terminal and Web console for Kubernetes
Client for prometheus
rollup-plugin-node-polyfills ===
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.
Sharing Connection among Multi-Process Nodejs
Matter.js main entrypoint
The Socket.IO Redis adapter, allowing to broadcast events between several Socket.IO servers
This gem offers a shim to connect Rails apps with a Bonsai Elasticsearch cluster. The official Elasticsearch gem package requires some minor configuration tweaks in order to work correctly with Bonsai (namely the client needs to be instantiated with the cluster location and HTTP authentication details), and the process can be somewhat complicated for users who are unfamiliar with the system. The bonsai-elasticsearch-rails gem automatically sets up the Elasticsearch client correctly so users don't need to worry about configuring it in their code or writing an initializer. In order for the gem to work correctly, the application needs an environment variable called `BONSAI_URL`, which is populated with the complete Bonsai Elaticsearch cluster URL, including the HTTP authentication. The cluster URL will follow this pattern: https://user1234:pass5678@cluster-slug-123.aws-region-X.bonsai.io/ On Heroku, this variable is created and populated automatically when Bonsai is added to the application. Heroku users therefore do not need to perform any additional configuration to connect to their cluster after adding the bonsai-elasticsearch-rails gem. Users who are self-hosting their Rails app will need to make sure this environment variable is present: export BONSAI_URL="https://user1234:pass5678@aws-region-X.bonsai.io/" The cluster URL is available via the Bonsai dashboard.
Simplify enterprise-grade Kubernetes cluster operations and management with Rancher on Bare Metal Cloud. Deploy Kubernetes clusters using a few API calls.<br> <br> <span class='pnap-api-knowledge-base-link'> Knowledge base articles to help you can be found <a href='https://phoenixnap.com/kb/rancher-bmc-integration-kubernetes' target='_blank'>here</a> </span><br> <br> <b>All URLs are relative to (https://api.phoenixnap.com/solutions/rancher/v1beta)</b>
Pampa is a Ruby library for async & distributing computing providing the following features: - cluster-management with dynamic reconfiguration (joining and leaving nodes); - distribution of the computation jobs to the (active) nodes; - error handling, job-retry and fault tolerance; - fast (non-direct) communication to ensure realtime capabilities. The Pampa framework may be widely used for: - large scale web scraping with what we call a "bot-farm"; - payments processing for large-scale ecommerce websites; - reports generation for high demanded SaaS platforms; - heavy mathematical model computing; and any other tasks that requires a virtually infinite amount of CPU computing and memory resources. Find documentation here: https://github.com/leandrosardi/pampa
# Sparrow is a really fast lightweight queue written in Ruby that speaks memcached. # That means you can use Sparrow with any memcached client library (Ruby or otherwise). # # Basic tests shows that Sparrow processes messages at a rate of 850-900 per second. # The load Sparrow can cope with increases exponentially as you add to the cluster. # Sparrow also takes advantage of eventmachine, which uses a non-blocking io, offering great performance. # # Sparrow is a in-memory queue but will persist the data to disk when receiving a term signal. # # Sparrow comes with built in support for daemonization and clustering. # Also included are example libraries and clients. For example: # # require 'memcache' # m = MemCache.new('127.0.0.1:11212') # m['queue_name'] = '1' # Publish to queue # m['queue_name'] #=> 1 Pull next msg from queue # m['queue_name'] #=> nil # m.delete('queue_name) # Delete queue # # # or using the included client: # # class MyQueue < MQ3::Queue # def on_message # logger.info "Received msg with args: #{args.inspect}" # end # end # # MyQueue.servers = [ # MQ3::Protocols::Memcache.new({:host => '127.0.0.1', :port => 11212, :weight => 1}) # ] # MyQueue.publish('test msg') # MyQueue.run # # Messages are deleted as soon as they're read and the order you add messages to the queue probably won't # be the same order when they're removed. # # Additional memcached commands that are supported are: # flush_all # Deletes all queues # version # quit # The memcached commands 'add', and 'replace' just call 'set'. # # Call sparrow with --help for usage options # # The daemonization won't work on Windows. # # Check out the code: # svn checkout http://sparrow.googlecode.com/svn/trunk/ sparrow # # Sparrow was inspired by Twitter's Starling
== 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
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