Open Source Windows Clustering Software
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Clustering Software for Windows
View 2770 business solutionsBrowse free open source Clustering software and projects for Windows below. Use the toggles on the left to filter open source Clustering software by OS, license, language, programming language, and project status.
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S.M.A.R.T. Monitoring Tools
Disk Inspection and Monitoring
smartmontools contains utility programs (smartctl, smartd) to control/monitor storage systems using the Self-Monitoring, Analysis and Reporting Technology System (S.M.A.R.T.) built into most modern ATA and SCSI disks. It is derived from smartsuite. -
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K9s
Kubernetes CLI To Manage Your Clusters In Style!
K9s is a terminal based UI to interact with your Kubernetes clusters. The aim of this project is to make it easier to navigate, observe and manage your deployed applications in the wild. K9s continually watches Kubernetes for changes and offers subsequent commands to interact with your observed resources. Provides standard cluster management commands such as logs, scaling, port-forwards, restarts. Define your own command shortcuts for quick navigation via command aliases and hotkeys. Plugin support to extend K9s to create your very own cluster commands. Powerful filtering mode to allow user to drill down and view workload related resources. Supports for viewing RBAC rules such as cluster/roles and their associated bindings. Reverse lookup to asserts what a user/group or ServiceAccount can do on your clusters. You can benchmark your HTTP services/pods directly from K9s to see how your application fare and adjust your resources request/limit accordingly. -
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minikube
Sets up a local Kubernetes cluster to run it
minikube quickly sets up a local Kubernetes cluster on macOS, Linux, and Windows. We proudly focus on helping application developers and new Kubernetes users. It supports the latest Kubernetes release (+6 previous minor versions). It iscross-platform (Linux, macOS, Windows), and allows the deployment of its functions as a VM, a container, or on bare-metal. Provides multiple container runtimes (CRI-O, containerd, docker), Docker API endpoint for blazing fast image pushes, and advanced features such as LoadBalancer, filesystem mounts, and FeatureGates. Contains addons for easily installed Kubernetes applications. -
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PelicanHPC is an iso-hybrid (CD or USB) image that let's you set up a high performance computing cluster in a few minutes. A Pelican cluster allows you to do parallel computing using MPI. You can run Pelican on a single multiple core machine to use all cores to solve a problem, or you can network multiple computers together to make a cluster. The frontend node (either a real computer or a virtual machine) boots from the image. The compute nodes boot by PXE, using the frontend node as the server. All of the nodes of the cluster get their filesystems from the same image, so it is guaranteed that all nodes run the the same software. Packages can be added to all nodes using apt-get, thanks to aufs. The bootable image is created by running a single script, which takes advantage of the Debian Live infrastructure.
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MyCAT
Active, high-performance open source database middleware
MyCAT is an Open-Source software, “a large database cluster” oriented to enterprises. MyCAT is an enforced database which is a replacement for MySQL and supports transaction and ACID. Regarded as MySQL cluster of enterprise database, MyCAT can take the place of expensive Oracle cluster. MyCAT is also a new type of database, which seems like a SQL Server integrated with the memory cache technology, NoSQL technology and HDFS big data. And as a new modern enterprise database product, MyCAT is combined with the traditional database and new distributed data warehouse. In a word, MyCAT is a fresh new middleware of database. MyCAT ’s objective is to smoothly migrate the current stand-alone database and applications to cloud side with low cost and to solve the bottleneck problem caused by the rapid growth of data storage and business scale. -
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chaoskube
chaoskube periodically kills random pods in your Kubernetes cluster
chaoskube periodically kills random pods in your Kubernetes cluster. Test how your system behaves under arbitrary pod failures. -
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Kubent
Easily check your clusters for use of deprecated APIs
Kubernetes 1.16 is slowly starting to roll out, not only across various managed Kubernetes offerings, and with that come to a lot of API deprecations. Kube No Trouble (Kubent) is a simple tool to check whether you're using any of these API versions in your cluster and therefore should upgrade your workloads first, before upgrading your Kubernetes cluster. This tool will be able to detect deprecated APIs depending on how you deploy your resources, as we need the original manifest to be stored somewhere. -
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KubeKey
Install Kubernetes/K3s only, both Kubernetes/K3s and KubeSphere
KubeKey is an open-source lightweight tool for deploying Kubernetes clusters. It provides a flexible, rapid, and convenient way to install Kubernetes/K3s only, both Kubernetes/K3s and KubeSphere, and related cloud-native add-ons. It is also an efficient tool to scale and upgrade your cluster. In addition, KubeKey also supports a customized Air-Gap package, which is convenient for users to quickly deploy clusters in offline environments. -
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Linux Cluster Management Console (LCMC) is a GUI that helps to configure Pacemaker, DRBD and KVM clusters.
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Faiss
Library for efficient similarity search and clustering dense vectors
Faiss is a library for efficient similarity search and clustering of dense vectors. It contains algorithms that search in sets of vectors of any size, up to ones that possibly do not fit in RAM. It also contains supporting code for evaluation and parameter tuning. Faiss is written in C++ with complete wrappers for Python/numpy. Some of the most useful algorithms are implemented on the GPU. It is developed by Facebook AI Research. Faiss contains several methods for similarity search. It assumes that the instances are represented as vectors and are identified by an integer, and that the vectors can be compared with L2 (Euclidean) distances or dot products. Vectors that are similar to a query vector are those that have the lowest L2 distance or the highest dot product with the query vector. It also supports cosine similarity, since this is a dot product on normalized vectors. -
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MicroK8s
Single-package Kubernetes for developers, IoT and edge
Low-ops, minimal production Kubernetes, for devs, cloud, clusters, workstations, Edge and IoT. MicroK8s automatically chooses the best nodes for the Kubernetes datastore. When you lose a cluster database node, another node is promoted. No admin needed for your bulletproof edge. MicroK8s is small, with sensible defaults that ‘just work’. A quick install, easy upgrades and great security make it perfect for micro clouds and edge computing. As the publishers of MicroK8s, we deliver the world’s most efficient multi-cloud, multi-arch Kubernetes. Under the cell tower. On the racecar. On satellites or everyday appliances, MicroK8s delivers the full Kubernetes experience on IoT and micro clouds. Fully containerized deployment with compressed over-the-air updates for ultra-reliable operations. MicroK8s will apply security updates automatically by default, defer them if you want. Upgrade to a newer version of Kubernetes with a single command. It’s really that easy. -
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kiosk
Multi-tenancy extension for Kubernetes
kiosk is a multi-tenancy extension For Kubernetes. Secure cluster sharing & self-service namespace provisioning. Accounts & account users to separate tenants in a shared Kubernetes cluster. Self-service namespace provisioning for account users. Account limits to ensure quality of service and fairness when sharing a cluster. Namespace templates for secure tenant isolation and self-service namespace initialization. Multi-cluster tenant management for sharing a pool of clusters. Kubernetes is designed as a single-tenant platform, which makes it hard for cluster admins to host multiple tenants in a single Kubernetes cluster. However, sharing a cluster has many advantages, e.g. more efficient resource utilization, less admin/configuration effort or easier sharing of cluster-internal resources among different tenants. -
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Open Source High Availability Middleware Generally Based on SA Forum Specifications
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Open HPI is an open source implementation of the SA Forum's Hardware Platform Interface (HPI). HPI provides an abstracted interface to managing computer hardware, typically for chassis and rack based servers. The new location for the project is https://github.com/open-hpi/openhpi
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Son of Grid Engine (SGE)
Community superset free distribution of gridengine/SGE batch system
Son of Grid Engine is a community continuation of the old Sun Grid Engine project. It aims to be a big superset of available free gridengine code and patches. The main site is currently https://arc.liv.ac.uk/trac/SGE/ and https://arc.liv.ac.uk/SGE/ but release files are inaccessible there and being hosted here. -
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EPSILON is a powerful Open Source wavelet image compressor. The project is aimed on parallel and robust image processing.
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Based on the source code of Sun Grid Engine, we are continuing the open source development effort here on sourceforge.
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CMAK
A tool for managing Apache Kafka clusters
CMAK (previously known as Kafka Manager) is a tool for managing Apache Kafka clusters. Easy inspection of cluster state (topics, consumers, offsets, brokers, replica distribution, partition distribution). Generate partition assignments with option to select brokers to use. Run reassignment of partition (based on generated assignments). Create a topic with optional topic configs (0.8.1.1 has different configs than 0.8.2+). Delete topic (only supported on 0.8.2+ and remember set delete.topic.enable=true in broker config). Topic list now indicates topics marked for deletion (only supported on 0.8.2+). Batch generate partition assignments for multiple topics with option to select brokers to use. Optionally enable JMX polling for broker level and topic level metrics. Optionally filter out consumers that do not have ids/ owners/ & offsets/ directories in zookeeper. -
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K8SGPT
Giving Kubernetes Superpowers to everyone
K8sGPT is a tool for scanning your Kubernetes clusters and diagnosing and triaging issues in simple English. It has SRE experience codified into its analyzers and helps to pull out the most relevant information to enrich it with AI. We have created analyzers that search your Kubernetes cluster for common problems and issues. These analyzers are based on SRE experience and are constantly being updated to keep up with the latest Kubernetes releases. Our ambition is to support multiple AI-powered backends. These serve as guides amid the noise of your cluster. They help you to focus on the most relevant information. -
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Zarf
DevSecOps for Air Gap & Limited-Connection Systems
Zarf eliminates the complexity of air gap software delivery for Kubernetes clusters and cloud-native workloads using a declarative packaging strategy to support DevSecOps in offline and semi-connected environments. -
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elasticsearch-head
A web front end for an elastic search cluster
elasticsearch-head is a web front end for browsing and interacting with an Elastic Search cluster. elasticsearch-head is hosted and can be downloaded or forked at github. There are two ways of running and installing elasticsearch-head. Running as a plugin of ElasticSearch (this is the preferred method). And running as a standalone webapp. By default es-head will immediately attempt to connect to a cluster node at http://localhost:9200/. Enter a different node address in the connect box and click 'Connect' if required. A ClusterOverview, which shows the topology of your cluster and allows you to perform index and node level operations. A couple of search interfaces that allow you to query the cluster a retrieve results in raw json or tabular format. Several quick access tabs that show the status of the cluster. An input section that allows arbitrary call to the RESTful API to be made. This interface includes several options that can be combined to produce interesting results. -
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kind
Kubernetes IN Docker - local clusters for testing Kubernetes
kind is a tool for running local Kubernetes clusters using Docker container “nodes”. kind was primarily designed for testing Kubernetes itself, but may be used for local development or CI. -
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kube-capacity
A simple CLI that provides an overview of the resource requests
This is a simple CLI that provides an overview of the resource requests, limits, and utilization in a Kubernetes cluster. It attempts to combine the best parts of the output from kubectl top and kubectl describe into an easy-to-use CLI focused on cluster resources. By default, kube-capacity will output a list of nodes with the total CPU and Memory resource requests and limits for all the pods running on them. For clusters with more than one node, the first line will also include cluster-wide totals. -
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kubenav
kubenav is the navigator for your Kubernetes clusters
kubenav is a mobile, desktop and web app to manage Kubernetes clusters. The app provides an overview of all resources in a Kubernetes clusters, including current status information for workloads. The details view for resources provides additional information. It is possible to view logs and events or to get a shell into a container. You can also edit and delete resources or scale your workloads within the app. The app is developed using Ionic Framework and Capacitor. The frontend part of the app is implemented using TypeScript and React functional components. The backend part uses Go mobile for communication with the Kubernetes API server and Cloud Providers. So it is possible to achieve nearly 100% code sharing between the mobile and desktop implementation of kubenav. Create a port-forwarding connection to one of your Pods and open the served page in your browser. -
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dispy
Distributed and Parallel Computing with/for Python.
dispy is a generic and comprehensive, yet easy to use framework for creating and using compute clusters to execute computations in parallel across multiple processors in a single machine (SMP), among many machines in a cluster, grid or cloud. dispy is well suited for data parallel (SIMD) paradigm where a computation (Python function or standalone program) is evaluated with different (large) datasets independently. dispy supports public / private / hybrid cloud computing, fog / edge computing.
