Best Web-Based Cluster Management Software of 2025 - Page 2

NVIDIA Run:ai is a cutting-edge platform that streamlines AI workload orchestration and GPU resource management to accelerate AI development and deployment at scale. It dynamically pools GPU resources across hybrid clouds, private data centers, and public clouds to optimize compute efficiency and workload capacity. The solution offers unified AI infrastructure management with centralized control and policy-driven governance, enabling enterprises to maximize GPU utilization while reducing operational costs. Designed with an API-first architecture, Run:ai integrates seamlessly with popular AI frameworks and tools, providing flexible deployment options from on-premises to multi-cloud environments. Its open-source KAI Scheduler offers developers simple and flexible Kubernetes scheduling capabilities. Customers benefit from accelerated AI training and inference with reduced bottlenecks, leading to faster innovation cycles. Run:ai is trusted by organizations seeking to scale AI initiatives efficiently while maintaining full visibility and control. This platform empowers teams to transform resource management into a strategic advantage with zero manual effort.

Tungsten Clustering is the only fully-integrated, fully-tested, fully-tested MySQL HA/DR and geo-clustering system that can be used on-premises or in the cloud. It also offers industry-leading, fastest, 24/7 support for Percona Server, MariaDB and MySQL applications that are business-critical. It allows businesses that use business-critical MySQL databases to achieve cost-effective global operations with commercial-grade high availabilty (HA), geographically redundant disaster relief (DR), and geographically distributed multimaster. Tungsten Clustering consists of four core components: data replication, cluster management, and cluster monitoring. Together, they handle all of the messaging and control of your Tungsten MySQL clusters in a seamlessly-orchestrated fashion.

Rancher empowers you to provide Kubernetes-as-a-Service across various environments, including datacenters, cloud, and edge. This comprehensive software stack is designed for teams transitioning to container technology, tackling both operational and security issues associated with managing numerous Kubernetes clusters. Moreover, it equips DevOps teams with integrated tools to efficiently handle containerized workloads. With Rancher’s open-source platform, users can deploy Kubernetes in any setting. Evaluating Rancher against other top Kubernetes management solutions highlights its unique delivery capabilities. You won’t have to navigate the complexities of Kubernetes alone, as Rancher benefits from a vast community of users. Developed by Rancher Labs, this software is tailored to assist enterprises in seamlessly implementing Kubernetes-as-a-Service across diverse infrastructures. When it comes to deploying critical workloads on Kubernetes, our community can rely on us for exceptional support, ensuring they are never left in the lurch. In addition, Rancher's commitment to continuous improvement means that users will always have access to the latest features and enhancements.

Oracle's Container Engine for Kubernetes (OKE) serves as a managed container orchestration solution that significantly minimizes both the time and expenses associated with developing contemporary cloud-native applications. In a departure from many competitors, Oracle Cloud Infrastructure offers OKE as a complimentary service that operates on high-performance and cost-efficient compute shapes. DevOps teams benefit from the ability to utilize unaltered, open-source Kubernetes, enhancing application workload portability while streamlining operations through automated updates and patch management. Users can initiate the deployment of Kubernetes clusters along with essential components like virtual cloud networks, internet gateways, and NAT gateways with just a single click. Furthermore, the platform allows for the automation of Kubernetes tasks via a web-based REST API and a command-line interface (CLI), covering all aspects from cluster creation to scaling and maintenance. Notably, Oracle does not impose any fees for managing clusters, making it an attractive option for developers. Additionally, users can effortlessly and swiftly upgrade their container clusters without experiencing any downtime, ensuring they remain aligned with the latest stable Kubernetes version. This combination of features positions Oracle's offering as a robust solution for organizations looking to optimize their cloud-native development processes.

Manage infrastructure across various locations with the support of Azure Arc. Utilize Azure Local, a distributed infrastructure solution, to operate virtual machines (VMs), containers, and specific Azure services seamlessly. You can deploy both modern container applications and traditional virtualized applications simultaneously on the same hardware setup. Choose the appropriate solution tailored to your needs from a list of reliable hardware partners. Establish and oversee your on-premises and cloud infrastructure while enjoying a more uniform Azure experience. Additionally, protect your workloads through advanced security measures that come standard in all validated hardware options. This approach ensures that your operations are not only efficient but also secure across diverse environments.

EKS is a community-focused platform that offers support for the latest version of Kubernetes and facilitates native cluster management. It serves as a ready-to-use plugin designed for Tencent Cloud products, enhancing capabilities in areas such as storage, networking, and load balancing. Built upon Tencent Cloud's advanced virtualization technology and robust network architecture, EKS guarantees an impressive 99.95% availability of services. In addition, Tencent Cloud prioritizes the virtual and network isolation of EKS clusters for each user, ensuring enhanced security. Users can define network policies tailored to their needs using tools like security groups and network ACLs. The serverless architecture of EKS promotes optimal resource utilization while minimizing operational costs. With its flexible and efficient auto-scaling features, EKS dynamically adjusts resource consumption based on the current demand. Moreover, EKS offers a variety of solutions tailored to diverse business requirements and seamlessly integrates with numerous Tencent Cloud services, including CBS, CFS, COS, TencentDB products, VPC, and many others, making it a versatile choice for users. This comprehensive approach allows organizations to leverage the full potential of cloud computing while maintaining control over their resources.

TKE seamlessly integrates with the full spectrum of Kubernetes features and has been optimized for Tencent Cloud's core IaaS offerings, including CVM and CBS. Moreover, Tencent Cloud's Kubernetes-driven products like CBS and CLB facilitate one-click deployments to container clusters for numerous open-source applications, significantly enhancing the efficiency of deployments. With the implementation of TKE, the complexities associated with managing large clusters and the operations of distributed applications are greatly reduced, eliminating the need for specialized cluster management tools or the intricate design of fault-tolerant cluster systems. You simply initiate TKE, outline the tasks you wish to execute, and TKE will handle all cluster management responsibilities, enabling you to concentrate on creating Dockerized applications. This streamlined process allows developers to maximize their productivity and innovate without being bogged down by infrastructure concerns.

Amazon EKS Anywhere is a recently introduced option for deploying Amazon EKS that simplifies the process of creating and managing Kubernetes clusters on-premises, whether on your dedicated virtual machines (VMs) or bare metal servers. This solution offers a comprehensive software package designed for the establishment and operation of Kubernetes clusters in local environments, accompanied by automation tools for effective cluster lifecycle management. EKS Anywhere ensures a uniform management experience across your data center, leveraging the capabilities of Amazon EKS Distro, which is the same Kubernetes version utilized by EKS on AWS. By using EKS Anywhere, you can avoid the intricacies involved in procuring or developing your own management tools to set up EKS Distro clusters, configure the necessary operating environment, perform software updates, and manage backup and recovery processes. It facilitates automated cluster management, helps cut down support expenses, and removes the need for multiple open-source or third-party tools for running Kubernetes clusters. Furthermore, EKS Anywhere comes with complete support from AWS, ensuring that users have access to reliable assistance whenever needed. This makes it an excellent choice for organizations looking to streamline their Kubernetes operations while maintaining control over their infrastructure.

SUSE Rancher Prime meets the requirements of DevOps teams involved in Kubernetes application deployment as well as IT operations responsible for critical enterprise services. It is compatible with any CNCF-certified Kubernetes distribution, while also providing RKE for on-premises workloads. In addition, it supports various public cloud offerings such as EKS, AKS, and GKE, and offers K3s for edge computing scenarios. The platform ensures straightforward and consistent cluster management, encompassing tasks like provisioning, version oversight, visibility and diagnostics, as well as monitoring and alerting, all backed by centralized audit capabilities. Through SUSE Rancher Prime, automation of processes is achieved, and uniform user access and security policies are enforced across all clusters, regardless of their deployment environment. Furthermore, it features an extensive catalog of services designed for the development, deployment, and scaling of containerized applications, including tools for app packaging, CI/CD, logging, monitoring, and implementing service mesh solutions, thereby streamlining the entire application lifecycle. This comprehensive approach not only enhances operational efficiency but also simplifies the management of complex environments.

K3s is a robust, certified Kubernetes distribution tailored for production workloads that can operate efficiently in unattended, resource-limited environments, including remote areas and IoT devices. It supports both ARM64 and ARMv7 architectures, offering binaries and multiarch images for each. K3s is versatile enough to run on devices ranging from a compact Raspberry Pi to a powerful AWS a1.4xlarge server with 32GiB of memory. The system features a lightweight storage backend that uses sqlite3 as its default storage solution, while also allowing the use of etcd3, MySQL, and Postgres. By default, K3s is secure and comes with sensible defaults optimized for lightweight setups. It includes a variety of essential features that enhance its functionality, such as a local storage provider, service load balancer, Helm controller, and Traefik ingress controller. All components of the Kubernetes control plane are encapsulated within a single binary and process, streamlining the management of complex cluster operations like certificate distribution. This design not only simplifies deployment but also ensures high availability and reliability in diverse environments.

IBM PowerHA SystemMirror is an advanced high availability solution designed to keep critical applications running smoothly by minimizing downtime through intelligent failure detection, automatic failover, and disaster recovery capabilities. This integrated technology supports both IBM AIX and IBM i platforms and offers flexible deployment options including multisite configurations for robust disaster recovery assurance. Users benefit from a simplified management interface that centralizes cluster operations and leverages smart assists to streamline setup and maintenance. PowerHA supports host-based replication techniques such as geographic mirroring and GLVM, enabling failover to private or public cloud environments. The solution tightly integrates IBM SAN storage systems, including DS8000 and Flash Systems, ensuring data integrity and performance. Licensing is based on processor cores with a one-time fee plus a first-year maintenance package, providing cost efficiency. Its highly autonomous design reduces administrative overhead, while continuous monitoring tools keep system health and performance transparent. IBM’s investment in PowerHA reflects its commitment to delivering resilient and scalable IT infrastructure solutions.

You have the ability to deploy clusters as needed and automatically manage their scaling, allowing you to concentrate solely on processing, analyzing, and reporting big data. Leveraging years of experience in massively distributed computing, our operations team expertly handles the intricacies of cluster management. During peak demand, clusters can be automatically expanded to enhance computing power, while they can be contracted during quieter periods to minimize costs. A user-friendly management console is available to simplify tasks such as cluster oversight, template customization, task submissions, and monitoring of alerts. By integrating with the BCC, it enables businesses to focus on their core operations during busy times while assisting the BMR in processing big data during idle periods, ultimately leading to reduced overall IT costs. This seamless integration not only streamlines operations but also enhances efficiency across the board.

Spectro Cloud’s Palette platform provides enterprises with a powerful and scalable solution for managing Kubernetes clusters across multiple environments, including cloud, edge, and on-premises data centers. By leveraging full-stack declarative orchestration, Palette allows teams to define cluster profiles that ensure consistency while preserving the freedom to customize infrastructure, container workloads, OS, and Kubernetes distributions. The platform’s lifecycle management capabilities streamline cluster provisioning, upgrades, and maintenance across hybrid and multi-cloud setups. It also integrates with a wide range of tools and services, including major cloud providers like AWS, Azure, and Google Cloud, as well as Kubernetes distributions such as EKS, OpenShift, and Rancher. Security is a priority, with Palette offering enterprise-grade compliance certifications such as FIPS and FedRAMP, making it suitable for government and regulated industries. Additionally, the platform supports advanced use cases like AI workloads at the edge, virtual clusters, and multitenancy for ISVs. Deployment options are flexible, covering self-hosted, SaaS, or airgapped environments to suit diverse operational needs. This makes Palette a versatile platform for organizations aiming to reduce complexity and increase operational control over Kubernetes.

Manage and orchestrate applications seamlessly on a Kubernetes platform that is fully managed, utilizing a centralized SaaS approach for overseeing distributed applications through a unified interface and advanced observability features. Streamline operations by handling deployments uniformly across on-premises, cloud, and edge environments. Experience effortless management and scaling of applications across various Kubernetes clusters, whether at customer locations or within the F5 Distributed Cloud Regional Edge, all through a single Kubernetes-compatible API that simplifies multi-cluster oversight. You can deploy, deliver, and secure applications across different sites as if they were all part of one cohesive "virtual" location. Furthermore, ensure that distributed applications operate with consistent, production-grade Kubernetes, regardless of their deployment sites, which can range from private and public clouds to edge environments. Enhance security with a zero trust approach at the Kubernetes Gateway, extending ingress services backed by WAAP, service policy management, and comprehensive network and application firewall protections. This approach not only secures your applications but also fosters a more resilient and adaptable infrastructure.

AWS ParallelCluster is a free, open-source tool designed for efficient management and deployment of High-Performance Computing (HPC) clusters within the AWS environment. It streamlines the configuration of essential components such as compute nodes, shared filesystems, and job schedulers, while accommodating various instance types and job submission queues. Users have the flexibility to engage with ParallelCluster using a graphical user interface, command-line interface, or API, which allows for customizable cluster setups and oversight. The tool also works seamlessly with job schedulers like AWS Batch and Slurm, making it easier to transition existing HPC workloads to the cloud with minimal adjustments. Users incur no additional costs for the tool itself, only paying for the AWS resources their applications utilize. With AWS ParallelCluster, users can effectively manage their computing needs through a straightforward text file that allows for the modeling, provisioning, and dynamic scaling of necessary resources in a secure and automated fashion. This ease of use significantly enhances productivity and optimizes resource allocation for various computational tasks.

NVIDIA Base Command Manager provides rapid deployment and comprehensive management for diverse AI and high-performance computing clusters, whether at the edge, within data centers, or across multi- and hybrid-cloud settings. This platform automates the setup and management of clusters, accommodating sizes from a few nodes to potentially hundreds of thousands, and is compatible with NVIDIA GPU-accelerated systems as well as other architectures. It facilitates orchestration through Kubernetes, enhancing the efficiency of workload management and resource distribution. With additional tools for monitoring infrastructure and managing workloads, Base Command Manager is tailored for environments that require accelerated computing, making it ideal for a variety of HPC and AI applications. Available alongside NVIDIA DGX systems and within the NVIDIA AI Enterprise software suite, this solution enables the swift construction and administration of high-performance Linux clusters, thereby supporting a range of applications including machine learning and analytics. Through its robust features, Base Command Manager stands out as a key asset for organizations aiming to optimize their computational resources effectively.

IBM Spectrum LSF Suites serves as a comprehensive platform for managing workloads and scheduling jobs within distributed high-performance computing (HPC) environments. Users can leverage Terraform-based automation for the seamless provisioning and configuration of resources tailored to IBM Spectrum LSF clusters on IBM Cloud. This integrated solution enhances overall user productivity and optimizes hardware utilization while effectively lowering system management expenses, making it ideal for mission-critical HPC settings. Featuring a heterogeneous and highly scalable architecture, it accommodates both traditional high-performance computing tasks and high-throughput workloads. Furthermore, it is well-suited for big data applications, cognitive processing, GPU-based machine learning, and containerized workloads. With its dynamic HPC cloud capabilities, IBM Spectrum LSF Suites allows organizations to strategically allocate cloud resources according to workload demands, supporting all leading cloud service providers. By implementing advanced workload management strategies, including policy-driven scheduling that features GPU management and dynamic hybrid cloud capabilities, businesses can expand their capacity as needed. This flexibility ensures that companies can adapt to changing computational requirements while maintaining efficiency.

Red Hat Advanced Cluster Management for Kubernetes allows users to oversee clusters and applications through a centralized interface, complete with integrated security policies. By enhancing the capabilities of Red Hat OpenShift, it facilitates the deployment of applications, the management of multiple clusters, and the implementation of policies across numerous clusters at scale. This solution guarantees compliance, tracks usage, and maintains uniformity across deployments. Included with Red Hat OpenShift Platform Plus, it provides an extensive array of powerful tools designed to secure, protect, and manage applications effectively. Users can operate from any environment where Red Hat OpenShift is available and can manage any Kubernetes cluster within their ecosystem. The self-service provisioning feature accelerates application development pipelines, enabling swift deployment of both legacy and cloud-native applications across various distributed clusters. Additionally, self-service cluster deployment empowers IT departments by automating the application delivery process, allowing them to focus on higher-level strategic initiatives. As a result, organizations can achieve greater efficiency and agility in their IT operations.

In summary, OKD represents a highly opinionated version of Kubernetes. At its core, Kubernetes consists of various software and architectural patterns designed to manage applications on a large scale. While we incorporate some features directly into Kubernetes through modifications, the majority of our enhancements come from "preinstalling" a wide array of software components known as Operators into the deployed cluster. These Operators manage the over 100 essential elements of our platform, including OS upgrades, web consoles, monitoring tools, and image-building functionalities. OKD is versatile and suitable for deployment across various environments, from cloud infrastructures to on-premise hardware and edge computing scenarios. The installation process is automated for certain platforms, like AWS, while also allowing for customization in other environments, such as bare metal or lab settings. OKD embraces best practices in development and technology, making it an excellent platform for technologists and students alike to explore, innovate, and engage with the broader cloud ecosystem. Furthermore, as an open-source project, it encourages community contributions and collaboration, fostering a rich environment for learning and growth.

Pipeshift is an adaptable orchestration platform developed to streamline the creation, deployment, and scaling of open-source AI components like embeddings, vector databases, and various models for language, vision, and audio, whether in cloud environments or on-premises settings. It provides comprehensive orchestration capabilities, ensuring smooth integration and oversight of AI workloads while being fully cloud-agnostic, thus allowing users greater freedom in their deployment choices. Designed with enterprise-level security features, Pipeshift caters specifically to the demands of DevOps and MLOps teams who seek to implement robust production pipelines internally, as opposed to relying on experimental API services that might not prioritize privacy. Among its notable functionalities are an enterprise MLOps dashboard for overseeing multiple AI workloads, including fine-tuning, distillation, and deployment processes; multi-cloud orchestration equipped with automatic scaling, load balancing, and scheduling mechanisms for AI models; and effective management of Kubernetes clusters. Furthermore, Pipeshift enhances collaboration among teams by providing tools that facilitate the monitoring and adjustment of AI models in real-time.

Foundry represents a revolutionary type of public cloud, driven by an orchestration platform that simplifies access to AI computing akin to the ease of flipping a switch. Dive into the impactful features of our GPU cloud services that are engineered for optimal performance and unwavering reliability. Whether you are overseeing training processes, catering to client needs, or adhering to research timelines, our platform addresses diverse demands. Leading companies have dedicated years to developing infrastructure teams that create advanced cluster management and workload orchestration solutions to minimize the complexities of hardware management. Foundry democratizes this technology, allowing all users to take advantage of computational power without requiring a large-scale team. In the present GPU landscape, resources are often allocated on a first-come, first-served basis, and pricing can be inconsistent across different vendors, creating challenges during peak demand periods. However, Foundry utilizes a sophisticated mechanism design that guarantees superior price performance compared to any competitor in the market. Ultimately, our goal is to ensure that every user can harness the full potential of AI computing without the usual constraints associated with traditional setups.

The Corosync Cluster Engine serves as a robust group communication system equipped with features that facilitate high availability for various applications. This initiative offers four distinct application programming interface capabilities in C. It includes a closed process group communication model that ensures extended virtual synchrony, allowing for the creation of replicated state machines; a straightforward availability manager designed to restart application processes upon failure; an in-memory database for configuration and statistics that enables the setting, retrieval, and notification of changes in information; and a quorum system that alerts applications when a quorum is either established or lost. Our framework is utilized by several high-availability projects, including Pacemaker and Asterisk. We continuously seek developers and users who are passionate about clustering and wish to engage with our project, encouraging a collaborative environment for innovation and improvement.

ClusterVisor serves as an advanced system for managing HPC clusters, equipping users with a full suite of tools designed for deployment, provisioning, oversight, and maintenance throughout the cluster's entire life cycle. The system boasts versatile installation methods, including an appliance-based deployment that separates cluster management from the head node, thereby improving overall system reliability. Featuring LogVisor AI, it incorporates a smart log file analysis mechanism that leverages artificial intelligence to categorize logs based on their severity, which is essential for generating actionable alerts. Additionally, ClusterVisor streamlines node configuration and management through a collection of specialized tools, supports the management of user and group accounts, and includes customizable dashboards that visualize information across the cluster and facilitate comparisons between various nodes or devices. Furthermore, the platform ensures disaster recovery by maintaining system images for the reinstallation of nodes, offers an easy-to-use web-based tool for rack diagramming, and provides extensive statistics and monitoring capabilities, making it an invaluable asset for HPC cluster administrators. Overall, ClusterVisor stands as a comprehensive solution for those tasked with overseeing high-performance computing environments.

Bright Cluster Manager offers a variety of machine learning frameworks including Torch, Tensorflow and Tensorflow to simplify your deep-learning projects. Bright offers a selection the most popular Machine Learning libraries that can be used to access datasets. These include MLPython and NVIDIA CUDA Deep Neural Network Library (cuDNN), Deep Learning GPU Trainer System (DIGITS), CaffeOnSpark (a Spark package that allows deep learning), and MLPython. Bright makes it easy to find, configure, and deploy all the necessary components to run these deep learning libraries and frameworks. There are over 400MB of Python modules to support machine learning packages. We also include the NVIDIA hardware drivers and CUDA (parallel computer platform API) drivers, CUB(CUDA building blocks), NCCL (library standard collective communication routines).