Best Cluster Management Software for Cloud - Page 2

TKE is fully compatible with the entire range of Kubernetes capabilities and has been adapted to Tencent Cloud's fundamental IaaS capabilities such as CVM and CBS. In addition, Tencent Cloud’s Kubernetes-based cloud products such as CBS and CLB support one-click deployment to container clusters for a variety of open source applications, greatly improving deployment efficiency. Thanks to TKE, you can simplify the management of large-scale clusters and management and OPS of distributed applications without having to use cluster management software or design fault-tolerant cluster architecture. Simply launch TKE and specify the tasks you want to run, and then TKE will take care of all of the cluster management tasks, allowing you to focus on developing Dockerized applications.

Amazon EKS Anywhere is a new deployment option for Amazon EKS that enables you to easily create and operate Kubernetes clusters on-premises, including on your own virtual machines (VMs) and bare metal servers. EKS Anywhere provides an installable software package for creating and operating Kubernetes clusters on-premises and automation tooling for cluster lifecycle support. EKS Anywhere brings a consistent AWS management experience to your data center, building on the strengths of Amazon EKS Distro (the same Kubernetes that powers EKS on AWS.) EKS Anywhere saves you the complexity of buying or building your own management tooling to create EKS Distro clusters, configure the operating environment, update software, and handle backup and recovery. EKS Anywhere enables you to automate cluster management, reduce support costs, and eliminate the redundant effort of using multiple open source or 3rd party tools for operating Kubernetes clusters. EKS Anywhere is fully supported by AWS.

SUSE Rancher Prime addresses the needs of DevOps teams deploying applications with Kubernetes and IT operations delivering enterprise-critical services. SUSE Rancher Prime supports any CNCF-certified Kubernetes distribution. For on-premises workloads, we offer the RKE. We support all the public cloud distributions, including EKS, AKS, and GKE. At the edge, we offer K3s. SUSE Rancher Prime provides simple, consistent cluster operations, including provisioning, version management, visibility and diagnostics, monitoring and alerting, and centralized audit. SUSE Rancher Prime lets you automate processes and applies a consistent set of user access and security policies for all your clusters, no matter where they’re running. SUSE Rancher Prime provides a rich catalogue of services for building, deploying, and scaling containerized applications, including app packaging, CI/CD, logging, monitoring, and service mesh.

K3s is a highly available, certified Kubernetes distribution designed for production workloads in unattended, resource-constrained, remote locations or inside IoT appliances. Both ARM64 and ARMv7 are supported with binaries and multiarch images available for both. K3s works great from something as small as a Raspberry Pi to an AWS a1.4xlarge 32GiB server. Lightweight storage backend based on sqlite3 as the default storage mechanism. etcd3, MySQL, Postgres also still available. Secure by default with reasonable defaults for lightweight environments. Simple but powerful “batteries-included” features have been added, such as: a local storage provider, a service load balancer, a Helm controller, and the Traefik ingress controller. Operation of all Kubernetes control plane components is encapsulated in a single binary and process. This allows K3s to automate and manage complex cluster operations like distributing certificates.

IBM PowerHA SystemMirror provides a comprehensive high availability (HA) solution that ensures near-continuous application uptime with advanced failure detection, failover, and recovery features. It offers a simplified, integrated configuration that addresses storage and HA needs while allowing users to manage their clusters through a single pane of glass. Available for IBM AIX and IBM i operating systems, PowerHA supports multisite disaster recovery configurations and automation to reduce administrative effort. It incorporates IBM SAN storage systems like DS8000 and Flash Systems into HA clusters for robust data protection. Licensed per processor core with maintenance included for the first year, PowerHA delivers economic value for on-premises deployments. The technology helps enterprises eliminate planned and unplanned outages while monitoring system health proactively.

You can perform on-demand deployment and automatic scaling of the cluster, and focus on the big data processing, analysis, and reporting only. Thanks to many years’ of massively distributed computing technology accumulation, Our operations team can undertake the cluster operations. It automatically scales up clusters to improve the computing ability in peak periods and scales down clusters to reduce the cost in the valley period. It provides the management console to facilitate cluster management, template customization, task submission, and alarm monitoring. By deploying together with the BCC, it focuses on its own business in a busy time and helps the BMR to compute the big data in free time, reducing the overall IT expenditure.

Spectro Cloud’s Palette is a comprehensive Kubernetes management platform designed to simplify and unify the deployment, operation, and scaling of Kubernetes clusters across diverse environments—from edge to cloud to data center. It provides full-stack, declarative orchestration, enabling users to blueprint cluster configurations with consistency and flexibility. The platform supports multi-cluster, multi-distro Kubernetes environments, delivering lifecycle management, granular access controls, cost visibility, and optimization. Palette integrates seamlessly with cloud providers like AWS, Azure, Google Cloud, and popular Kubernetes services such as EKS, OpenShift, and Rancher. With robust security features including FIPS and FedRAMP compliance, Palette addresses needs of government and regulated industries. It offers flexible deployment options—self-hosted, SaaS, or airgapped—ensuring organizations can choose the best fit for their infrastructure and security requirements.

Deploy and orchestrate applications on a managed Kubernetes platform with centralized, SaaS-based management of distributed applications with a single pane of glass and rich observability. Simplify by managing deployments as one across on-prem, cloud, and edge locations. Achieve effortless management and scaling of applications across multiple k8s clusters (customer sites or F5 Distributed Cloud Regional Edge) with a single Kubernetes compatible API, unlocking the ease of multi-cluster management. Deploy, deliver, and secure applications to all locations as one ”virtual” location. Deploy, secure, and operate distributed applications with uniform production grade Kubernetes no matter the location, from private and public cloud to edge locations. Secure K8s Gateway with zero trust security all the way to the cluster with ingress services with WAAP, service policies management, network, and application firewall.

AWS ParallelCluster is an open-source cluster management tool that simplifies the deployment and management of High-Performance Computing (HPC) clusters on AWS. It automates the setup of required resources, including compute nodes, a shared filesystem, and a job scheduler, supporting multiple instance types and job submission queues. Users can interact with ParallelCluster through a graphical user interface, command-line interface, or API, enabling flexible cluster configuration and management. The tool integrates with job schedulers like AWS Batch and Slurm, facilitating seamless migration of existing HPC workloads to the cloud with minimal modifications. AWS ParallelCluster is available at no additional charge; users only pay for the AWS resources consumed by their applications. With AWS ParallelCluster, you can use a simple text file to model, provision, and dynamically scale the resources needed for your applications in an automated and secure manner.

NVIDIA Base Command Manager offers fast deployment and end-to-end management for heterogeneous AI and high-performance computing clusters at the edge, in the data center, and in multi- and hybrid-cloud environments. It automates the provisioning and administration of clusters ranging in size from a couple of nodes to hundreds of thousands, supports NVIDIA GPU-accelerated and other systems, and enables orchestration with Kubernetes. The platform integrates with Kubernetes for workload orchestration and offers tools for infrastructure monitoring, workload management, and resource allocation. Base Command Manager is optimized for accelerated computing environments, making it suitable for diverse HPC and AI workloads. It is available with NVIDIA DGX systems and as part of the NVIDIA AI Enterprise software suite. High-performance Linux clusters can be quickly built and managed with NVIDIA Base Command Manager, supporting HPC, machine learning, and analytics applications.

IBM Spectrum LSF Suites is a workload management platform and job scheduler for distributed high-performance computing (HPC). Terraform-based automation to provision and configure resources for an IBM Spectrum LSF-based cluster on IBM Cloud is available. Increase user productivity and hardware use while reducing system management costs with our integrated solution for mission-critical HPC environments. The heterogeneous, highly scalable, and available architecture provides support for traditional high-performance computing and high-throughput workloads. It also works for big data, cognitive, GPU machine learning, and containerized workloads. With dynamic HPC cloud support, IBM Spectrum LSF Suites enables organizations to intelligently use cloud resources based on workload demand, with support for all major cloud providers. Take advantage of advanced workload management, with policy-driven scheduling, including GPU scheduling and dynamic hybrid cloud, to add capacity on demand.

Red Hat Advanced Cluster Management for Kubernetes controls clusters and applications from a single console, with built-in security policies. Extend the value of Red Hat OpenShift by deploying apps, managing multiple clusters, and enforcing policies across multiple clusters at scale. Red Hat’s solution ensures compliance, monitors usage and maintains consistency. Red Hat Advanced Cluster Management for Kubernetes is included with Red Hat OpenShift Platform Plus, a complete set of powerful, optimized tools to secure, protect, and manage your apps. Run your operations from anywhere that Red Hat OpenShift runs, and manage any Kubernetes cluster in your fleet. Speed up application development pipelines with self-service provisioning. Deploy legacy and cloud-native applications quickly across distributed clusters. Free up IT departments with self-service cluster deployment that automatically delivers applications.

In short, OKD is a very opinionated deployment of Kubernetes. Kubernetes is a collection of software and design patterns to operate applications at scale. We add some features directly as modifications into Kubernetes, but mostly we augment the platform by "preinstalling" a large amount of pieces of software called Operators into the deployed cluster. These operators then provide all of our cluster components (over 100 of them) that make up the platform, such as OS upgrades, web consoles, monitoring, and image-building. OKD is intended to be run at all scales from cloud to metal to edge. The installer is fully automated on some platforms (such as AWS) or supports configuration into custom environments (such as metal or labs). OKD adopts developing best practices and technology. A great platform for technologists and students to learn, experiment, and contribute across the cloud ecosystem.

Pipeshift is a modular orchestration platform designed to facilitate the building, deployment, and scaling of open source AI components, including embeddings, vector databases, large language models, vision models, and audio models, across any cloud environment or on-premises infrastructure. The platform offers end-to-end orchestration, ensuring seamless integration and management of AI workloads, and is 100% cloud-agnostic, providing flexibility in deployment. With enterprise-grade security, Pipeshift addresses the needs of DevOps and MLOps teams aiming to establish production pipelines in-house, moving beyond experimental API providers that may lack privacy considerations. Key features include an enterprise MLOps console for managing various AI workloads such as fine-tuning, distillation, and deployment; multi-cloud orchestration with built-in auto-scalers, load balancers, and schedulers for AI models; and Kubernetes cluster management.

Foundry is a new breed of public cloud, powered by an orchestration platform that makes accessing AI compute as easy as flipping a light switch. Explore the high-impact features of our GPU cloud services designed for maximum performance and reliability. Whether you’re managing training runs, serving clients, or meeting research deadlines. Industry giants have invested for years in infra teams that build sophisticated cluster management and workload orchestration tools to abstract away the hardware. Foundry makes this accessible to everyone else, ensuring that users can reap compute leverage without a twenty-person team at scale. The current GPU ecosystem is first-come, first-serve, and fixed-price. Availability is a challenge in peak times, and so are the puzzling gaps in rates across vendors. Foundry is powered by a sophisticated mechanism design that delivers better price performance than anyone on the market.

The Corosync Cluster Engine is a group communication system with additional features for implementing high availability within applications. The project provides four C application programming interface features. Closed process group communication model with extended virtual synchrony guarantees for creating replicated state machines; a simple availability manager that restarts the application process when it has failed; a configuration and statistics in-memory database that provides the ability to set, retrieve, and receive change notifications of information; and a quorum system that notifies applications when a quorum is achieved or lost. Our project is used as a high-availability framework by projects such as Pacemaker and Asterisk. We are always looking for developers or users interested in clustering or participating in our project.

ClusterVisor is an HPC cluster management system that provides comprehensive tools for deploying, provisioning, managing, monitoring, and maintaining high-performance computing clusters throughout their lifecycle. It offers flexible installation options, including deployment via an appliance, which decouples cluster management from the head node, enhancing system resilience. The platform includes LogVisor AI, an integrated log file analysis tool that utilizes AI to classify logs by severity, enabling the creation of actionable alerts. ClusterVisor facilitates node configuration and management with a suite of tools, supports user and group account management, and features customizable dashboards for visualizing cluster-wide information and comparing multiple nodes or devices. It provides disaster recovery capabilities by storing system images for node reinstallation, offers an intuitive web-based rack diagramming tool, and enables comprehensive statistics and monitoring.

NVIDIA Bright Cluster Manager offers fast deployment and end-to-end management for heterogeneous high-performance computing (HPC) and AI server clusters at the edge, in the data center, and in multi/hybrid-cloud environments. It automates provisioning and administration for clusters ranging in size from a couple of nodes to hundreds of thousands, supports CPU-based and NVIDIA GPU-accelerated systems, and enables orchestration with Kubernetes. Heterogeneous high-performance Linux clusters can be quickly built and managed with NVIDIA Bright Cluster Manager, supporting HPC, machine learning, and analytics applications that span from core to edge to cloud. NVIDIA Bright Cluster Manager is ideal for heterogeneous environments, supporting Arm® and x86-based CPU nodes, and is fully optimized for accelerated computing with NVIDIA GPUs and NVIDIA DGX™ systems.